InBody
Technologie

Item 1

Item 2

Item 3

Item 4

Item 5

Item 6

What is Bio-Electrical
Impedance Analysis (BIA)?

Behind the scenes

InBody devices use a method called Bio-electrical Impedance Analysis (BIA) to measure body composition, which divides your weight into different components such as lean body mass and fat mass to assess health and nutrition.

What is Bio-Electrical
Impedance Analysis (BIA)?

Behind the scenes

InBody devices use a method called Bio-electrical Impedance Analysis (BIA) to measure body composition, which divides your weight into different components such as lean body mass and fat mass to assess health and nutrition.

The Human Body and Impedance

Bioelectrical Impedance Analysis (BIA) measures impedance by applying alternating currents on the human body.

The Concept of Resistance

To better illustrate how this works, imagine the flow of cars in traffic. Your car is the voltage source or current, and the highway you’re on is body water. If there were no other cars, you could zoom past the highway, just as if the human body were full of body water and nothing else, there would be no resistance.

But water is not the only element in the human body, just like you’re not the only car on the freeway. As more cars get onto the freeway, the longer it takes for you to get through the path, creating resistance. Other elements such as fat, muscle, bone, and minerals create resistance to the electrical current that is going through your body.

In BIA, the more water that is in your body, the lesser the resistance. The muscle in your body contains water, unlike fat, so the more muscle you have, the more body water. And the more body water you have, the lesser the resistance on the electrical current.

The Human Body and Impedance

Bioelectrical Impedance Analysis (BIA) measures impedance by applying alternating currents on the human body.

The Concept of Resistance

To better illustrate how this works, imagine the flow of cars in traffic. Your car is the voltage source or current, and the highway you’re on is body water. If there were no other cars, you could zoom past the highway, just as if the human body were full of body water and nothing else, there would be no resistance.

But water is not the only element in the human body, just like you’re not the only car on the freeway. As more cars get onto the freeway, the longer it takes for you to get through the path, creating resistance. Other elements such as fat, muscle, bone, and minerals create resistance to the electrical current that is going through your body.

In BIA, the more water that is in your body, the lesser the resistance. The muscle in your body contains water, unlike fat, so the more muscle you have, the more body water. And the more body water you have, the lesser the resistance on the electrical current.

The Concept of Reactance

Reactance , also known as capacitive resistance,

is the opposition to the instantaneous flow of electric current caused by capacitance. Reactance helps measure the cell’s ability to store energy and is an indirect measurement of cellular strength and integrity.

Putting It All Together
Impedance is the vector sum of resistance and reactance and is the measurement BIA devices use to determine your body composition. BIA applies a cylinder model for the relationship between impedance and a human body.

Putting It All Together

Impedance is the vector sum of resistance and reactance and is the measurement BIA devices use to determine your body composition. BIA applies a cylinder model for the relationship between impedance and a human body.

Impedance is calculated by using two formulas:

Calculating the volume of a cylinder (Volume = Length x Area)
Characteristic of impedance: impedance is inversely proportional to cross-sectional area and directly proportional to length.

By knowing the impedance and the length of the cylinder, we can measure the volume of total body water.

In the human body, the same formula applies, where the length would be the height of the person. Therefore, we can calculate the volume of the total body water just by knowing the impedance and the height of individuals. This is also why it is imperative to have an accurate height measurement.

InBody timeline

1969

Hoffer and the Impedance Index

In 1969, Hoffer carried out a series of experiments to prove that total body water and biological impedance were highly correlated, suggesting that impedance measurement could be used for determining total body water.

He showed the squared value of height divided by impedance was highly correlated with total body water.

Hoffer took impedance measurements of the right half of the body including the right arm, torso, and right leg.

The squared value divided by impedance showed correlation coefficient of 0.92 with total body water, which was higher than other indices including body weight. The equation Hoffer proved is the impedance index used in BIA today.

1969

Hoffer and the Impedance Index

In 1969, Hoffer carried out a series of experiments to prove that total body water and biological impedance were highly correlated, suggesting that impedance measurement could be used for determining total body water.

He showed the squared value of height divided by impedance was highly correlated with total body water.

Hoffer took impedance measurements of the right half of the body including the right arm, torso, and right leg.

The squared value divided by impedance showed correlation coefficient of 0.92 with total body water, which was higher than other indices including body weight. The equation Hoffer proved is the impedance index used in BIA today.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1976

RJL Systems and the first impedance meter

In 1979, RJL Systems commercialized the impedance meter for the first time and the BIA method began to gain popularity.

The device measured impedance by attaching electrodes on the back of the right hand and a top of the right foot of a patient and conducting a current of 50kHz through the right half of the body.

Prior to this, body composition could only be measured by caliper or underwater weighing. Such methods needed to be carried out by skilled people and installation was not easy. Also, only specific types of patients could benefit from them.

BIA however, was easy, fast, less expensive and less intrusive. Therefore, many body composition researchers, nutritionists, and medical experts began to use BIA.

1976

RJL Systems and the first impedance meter

In 1979, RJL Systems commercialized the impedance meter for the first time and the BIA method began to gain popularity.

The device measured impedance by attaching electrodes on the back of the right hand and a top of the right foot of a patient and conducting a current of 50kHz through the right half of the body.

Prior to this, body composition could only be measured by caliper or underwater weighing. Such methods needed to be carried out by skilled people and installation was not easy. Also, only specific types of patients could benefit from them.

BIA however, was easy, fast, less expensive and less intrusive. Therefore, many body composition researchers, nutritionists, and medical experts began to use BIA.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Discovering limitations to BIA with empirical data

Research by Lukaski, Segal and other scholars accelerated the evolution of BIA. Studies proved BIA had high correlation with gold standard methods like underwater weighing and DEXA. But technical limitations of BIA began to surface in the late 1980s.

One limitation was that BIA assumed the human body to be in the shape of one cylinder and used a single frequency (50 kHz).

This may have worked for patients with standard body types, but it wasn’t as accurate for other populations.

So, researchers came up with various equations in addition to the impedance index so as to complement the technical limitation of BIA and achieve greater accuracy for patient groups of different age, gender etc.

1980

Discovering limitations to BIA with empirical data

Research by Lukaski, Segal and other scholars accelerated the evolution of BIA. Studies proved BIA had high correlation with gold standard methods like underwater weighing and DEXA. But technical limitations of BIA began to surface in the late 1980s.

One limitation was that BIA assumed the human body to be in the shape of one cylinder and used a single frequency (50 kHz).

This may have worked for patients with standard body types, but it wasn’t as accurate for other populations.

So, researchers came up with various equations in addition to the impedance index so as to complement the technical limitation of BIA and achieve greater accuracy for patient groups of different age, gender etc.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Lukaski and Kushner develop empirical equations

To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Lukaski and Kushner develop empirical equations

To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Discovering limitions to BIA with empirical data

Research by Lukaski, Segal and other scholars accelerated the evolution of BIA.

Studies proved BIA had high correlation with gold standard methods like underwater weighing and DEXA. But technical limitations of BIA began to surface in the late 1980s.

One limitation was that BIA assumed the human body to be in the shape of one cylinder and used a single frequency (50 kHz).

This may have worked for patients with standard body types, but it wasn’t as accurate for other populations.

So, researchers came up with various equations in addition to the impedance index so as to complement the technical limitation of BIA and achieve greater accuracy for patient groups of different age, gender etc.

1980

Discovering limitions to BIA with empirical data

Research by Lukaski, Segal and other scholars accelerated the evolution of BIA.

Studies proved BIA had high correlation with gold standard methods like underwater weighing and DEXA. But technical limitations of BIA began to surface in the late 1980s.

One limitation was that BIA assumed the human body to be in the shape of one cylinder and used a single frequency (50 kHz).

This may have worked for patients with standard body types, but it wasn’t as accurate for other populations.

So, researchers came up with various equations in addition to the impedance index so as to complement the technical limitation of BIA and achieve greater accuracy for patient groups of different age, gender etc.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Home-use BIA Devices

Due to technological constraints, BIA devices became home-use devices rather than hospital devices.

In the late 1980s, Japanese manufacturers released various types of BIA-based body composition devices that could easily be used by the general public.

Some devices measured the impedance between two feet as the user stands on the scale, while another would measure the impedance between two hands while holding the device.

1980

Home-use BIA Devices

Due to technological constraints, BIA devices became home-use devices rather than hospital devices.

In the late 1980s, Japanese manufacturers released various types of BIA-based body composition devices that could easily be used by the general public.

Some devices measured the impedance between two feet as the user stands on the scale, while another would measure the impedance between two hands while holding the device.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1992

The History of BIA Technology

Since the inaccuracy of BIA is due to technical limitations, many argued that this could be improved upon. In 1992, Kushner claimed that the human body is made up of five cylinders (right arm, left arm, torso, right leg, left leg) instead of one.

While the thin limbs affect the total impedance, the torso, which has the largest cross-sectional area, has little impact on impedance. However, since the torso makes up 50% of lean body mass, Kushner emphasized that measuring the impedance of the body torso separately would be very important.

Measuring the total impedance alone would not be sufficient but all five parts must be measured separately at different frequencies, making a distinction between extracellular water and intracellular water.

In other words, the technical limitations of BIA should be overcome by measuring different parts at different frequencies.

1992

The History of BIA Technology

Since the inaccuracy of BIA is due to technical limitations, many argued that this could be improved upon. In 1992, Kushner claimed that the human body is made up of five cylinders (right arm, left arm, torso, right leg, left leg) instead of one.

While the thin limbs affect the total impedance, the torso, which has the largest cross-sectional area, has little impact on impedance. However, since the torso makes up 50% of lean body mass, Kushner emphasized that measuring the impedance of the body torso separately would be very important.

Measuring the total impedance alone would not be sufficient but all five parts must be measured separately at different frequencies, making a distinction between extracellular water and intracellular water.

In other words, the technical limitations of BIA should be overcome by measuring different parts at different frequencies.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1996

Dr. Cha creates the InBody body composition analyzer

In 1996, Dr. Kichul Cha, a bioengineering major at Harvard Medical School, developed the world’s first 8-point tactile electrode system with direct segmental analysis which measures impedance for the five different parts of the body at multiple frequencies.

Measuring impedance by applying currents of multi-frequencies on the five parts of the body took a separate impedance measurement. Moreover, it allows separately checking torso impedance. This yielded highly accurate results without using empirical data. Thus, InBody body composition analyzers became a precise medical device. Impedance values for all cylinders, including the torso, can be found on the InBody Result Sheet.

Many BIA products today provide muscle mass for each section of the body. However, most of such products are unable to take sectional impedance measurements, especially the torso impedance.

However, as shown on an InBody Result Sheet, you can see the impedance values of all five parts of the body including the torso with the use of both high and low frequencies.

1996

Dr. Cha creates the InBody body composition analyzer

In 1996, Dr. Kichul Cha, a bioengineering major at Harvard Medical School, developed the world’s first 8-point tactile electrode system with direct segmental analysis which measures impedance for the five different parts of the body at multiple frequencies.

Measuring impedance by applying currents of multi-frequencies on the five parts of the body took a separate impedance measurement. Moreover, it allows separately checking torso impedance. This yielded highly accurate results without using empirical data. Thus, InBody body composition analyzers became a precise medical device. Impedance values for all cylinders, including the torso, can be found on the InBody Result Sheet.

Many BIA products today provide muscle mass for each section of the body. However, most of such products are unable to take sectional impedance measurements, especially the torso impedance.

However, as shown on an InBody Result Sheet, you can see the impedance values of all five parts of the body including the torso with the use of both high and low frequencies.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1969

Hoffer and the Impedance Index

In 1969, Hoffer carried out a series of experiments to prove that total body water and biological impedance were highly correlated, suggesting that impedance measurement could be used for determining total body water.

He showed the squared value of height divided by impedance was highly correlated with total body water.

Hoffer took impedance measurements of the right half of the body including the right arm, torso, and right leg.

The squared value divided by impedance showed correlation coefficient of 0.92 with total body water, which was higher than other indices including body weight. The equation Hoffer proved is the impedance index used in BIA today.

1969

Hoffer and the Impedance Index

In 1969, Hoffer carried out a series of experiments to prove that total body water and biological impedance were highly correlated, suggesting that impedance measurement could be used for determining total body water.

He showed the squared value of height divided by impedance was highly correlated with total body water.

Hoffer took impedance measurements of the right half of the body including the right arm, torso, and right leg.

The squared value divided by impedance showed correlation coefficient of 0.92 with total body water, which was higher than other indices including body weight. The equation Hoffer proved is the impedance index used in BIA today.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1976

RJL Systems and the first impedance meter

In 1979, RJL Systems commercialized the impedance meter for the first time and the BIA method began to gain popularity.

The device measured impedance by attaching electrodes on the back of the right hand and a top of the right foot of a patient and conducting a current of 50kHz through the right half of the body.

Prior to this, body composition could only be measured by caliper or underwater weighing. Such methods needed to be carried out by skilled people and installation was not easy. Also, only specific types of patients could benefit from them.

BIA however, was easy, fast, less expensive and less intrusive. Therefore, many body composition researchers, nutritionists, and medical experts began to use BIA.

1976

RJL Systems and the first impedance meter

In 1979, RJL Systems commercialized the impedance meter for the first time and the BIA method began to gain popularity.

The device measured impedance by attaching electrodes on the back of the right hand and a top of the right foot of a patient and conducting a current of 50kHz through the right half of the body.

Prior to this, body composition could only be measured by caliper or underwater weighing. Such methods needed to be carried out by skilled people and installation was not easy. Also, only specific types of patients could benefit from them.

BIA however, was easy, fast, less expensive and less intrusive. Therefore, many body composition researchers, nutritionists, and medical experts began to use BIA.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Discovering limitations to BIA with empirical data

Research by Lukaski, Segal and other scholars accelerated the evolution of BIA. Studies proved BIA had high correlation with gold standard methods like underwater weighing and DEXA. But technical limitations of BIA began to surface in the late 1980s.

One limitation was that BIA assumed the human body to be in the shape of one cylinder and used a single frequency (50 kHz).

This may have worked for patients with standard body types, but it wasn’t as accurate for other populations.

So, researchers came up with various equations in addition to the impedance index so as to complement the technical limitation of BIA and achieve greater accuracy for patient groups of different age, gender etc.

1980

Discovering limitations to BIA with empirical data

Research by Lukaski, Segal and other scholars accelerated the evolution of BIA. Studies proved BIA had high correlation with gold standard methods like underwater weighing and DEXA. But technical limitations of BIA began to surface in the late 1980s.

One limitation was that BIA assumed the human body to be in the shape of one cylinder and used a single frequency (50 kHz).

This may have worked for patients with standard body types, but it wasn’t as accurate for other populations.

So, researchers came up with various equations in addition to the impedance index so as to complement the technical limitation of BIA and achieve greater accuracy for patient groups of different age, gender etc.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Lukaski and Kushner develop empirical equations

To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Lukaski and Kushner develop empirical equations

To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Discovering limitions to BIA with empirical data

Research by Lukaski, Segal and other scholars accelerated the evolution of BIA.

Studies proved BIA had high correlation with gold standard methods like underwater weighing and DEXA. But technical limitations of BIA began to surface in the late 1980s.

One limitation was that BIA assumed the human body to be in the shape of one cylinder and used a single frequency (50 kHz).

This may have worked for patients with standard body types, but it wasn’t as accurate for other populations.

So, researchers came up with various equations in addition to the impedance index so as to complement the technical limitation of BIA and achieve greater accuracy for patient groups of different age, gender etc.

1980

Discovering limitions to BIA with empirical data

Research by Lukaski, Segal and other scholars accelerated the evolution of BIA.

Studies proved BIA had high correlation with gold standard methods like underwater weighing and DEXA. But technical limitations of BIA began to surface in the late 1980s.

One limitation was that BIA assumed the human body to be in the shape of one cylinder and used a single frequency (50 kHz).

This may have worked for patients with standard body types, but it wasn’t as accurate for other populations.

So, researchers came up with various equations in addition to the impedance index so as to complement the technical limitation of BIA and achieve greater accuracy for patient groups of different age, gender etc.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Home-use BIA Devices

Due to technological constraints, BIA devices became home-use devices rather than hospital devices.

In the late 1980s, Japanese manufacturers released various types of BIA-based body composition devices that could easily be used by the general public.

Some devices measured the impedance between two feet as the user stands on the scale, while another would measure the impedance between two hands while holding the device.

1980

Home-use BIA Devices

Due to technological constraints, BIA devices became home-use devices rather than hospital devices.

In the late 1980s, Japanese manufacturers released various types of BIA-based body composition devices that could easily be used by the general public.

Some devices measured the impedance between two feet as the user stands on the scale, while another would measure the impedance between two hands while holding the device.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1992

The History of BIA Technology

Since the inaccuracy of BIA is due to technical limitations, many argued that this could be improved upon. In 1992, Kushner claimed that the human body is made up of five cylinders (right arm, left arm, torso, right leg, left leg) instead of one.

While the thin limbs affect the total impedance, the torso, which has the largest cross-sectional area, has little impact on impedance. However, since the torso makes up 50% of lean body mass, Kushner emphasized that measuring the impedance of the body torso separately would be very important.

Measuring the total impedance alone would not be sufficient but all five parts must be measured separately at different frequencies, making a distinction between extracellular water and intracellular water.

In other words, the technical limitations of BIA should be overcome by measuring different parts at different frequencies.

1992

The History of BIA Technology

Since the inaccuracy of BIA is due to technical limitations, many argued that this could be improved upon. In 1992, Kushner claimed that the human body is made up of five cylinders (right arm, left arm, torso, right leg, left leg) instead of one.

While the thin limbs affect the total impedance, the torso, which has the largest cross-sectional area, has little impact on impedance. However, since the torso makes up 50% of lean body mass, Kushner emphasized that measuring the impedance of the body torso separately would be very important.

Measuring the total impedance alone would not be sufficient but all five parts must be measured separately at different frequencies, making a distinction between extracellular water and intracellular water.

In other words, the technical limitations of BIA should be overcome by measuring different parts at different frequencies.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1996

Dr. Cha creates the InBody body composition analyzer

In 1996, Dr. Kichul Cha, a bioengineering major at Harvard Medical School, developed the world’s first 8-point tactile electrode system with direct segmental analysis which measures impedance for the five different parts of the body at multiple frequencies.

Measuring impedance by applying currents of multi-frequencies on the five parts of the body took a separate impedance measurement. Moreover, it allows separately checking torso impedance. This yielded highly accurate results without using empirical data. Thus, InBody body composition analyzers became a precise medical device. Impedance values for all cylinders, including the torso, can be found on the InBody Result Sheet.

Many BIA products today provide muscle mass for each section of the body. However, most of such products are unable to take sectional impedance measurements, especially the torso impedance.

However, as shown on an InBody Result Sheet, you can see the impedance values of all five parts of the body including the torso with the use of both high and low frequencies.

1996

Dr. Cha creates the InBody body composition analyzer

In 1996, Dr. Kichul Cha, a bioengineering major at Harvard Medical School, developed the world’s first 8-point tactile electrode system with direct segmental analysis which measures impedance for the five different parts of the body at multiple frequencies.

Measuring impedance by applying currents of multi-frequencies on the five parts of the body took a separate impedance measurement. Moreover, it allows separately checking torso impedance. This yielded highly accurate results without using empirical data. Thus, InBody body composition analyzers became a precise medical device. Impedance values for all cylinders, including the torso, can be found on the InBody Result Sheet.

Many BIA products today provide muscle mass for each section of the body. However, most of such products are unable to take sectional impedance measurements, especially the torso impedance.

However, as shown on an InBody Result Sheet, you can see the impedance values of all five parts of the body including the torso with the use of both high and low frequencies.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

InBody timeline

1969

Hoffer and the Impedance Index

In 1969, Hoffer carried out a series of experiments to prove that total body water and biological impedance were highly correlated, suggesting that impedance measurement could be used for determining total body water.

He showed the squared value of height divided by impedance was highly correlated with total body water.

Hoffer took impedance measurements of the right half of the body including the right arm, torso, and right leg.

The squared value divided by impedance showed correlation coefficient of 0.92 with total body water, which was higher than other indices including body weight. The equation Hoffer proved is the impedance index used in BIA today.

1969

Hoffer and the Impedance Index

In 1969, Hoffer carried out a series of experiments to prove that total body water and biological impedance were highly correlated, suggesting that impedance measurement could be used for determining total body water.

He showed the squared value of height divided by impedance was highly correlated with total body water.

Hoffer took impedance measurements of the right half of the body including the right arm, torso, and right leg.

The squared value divided by impedance showed correlation coefficient of 0.92 with total body water, which was higher than other indices including body weight. The equation Hoffer proved is the impedance index used in BIA today.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1976

RJL Systems and the first impedance meter

In 1979, RJL Systems commercialized the impedance meter for the first time and the BIA method began to gain popularity.

The device measured impedance by attaching electrodes on the back of the right hand and a top of the right foot of a patient and conducting a current of 50kHz through the right half of the body.

Prior to this, body composition could only be measured by caliper or underwater weighing. Such methods needed to be carried out by skilled people and installation was not easy. Also, only specific types of patients could benefit from them.

BIA however, was easy, fast, less expensive and less intrusive. Therefore, many body composition researchers, nutritionists, and medical experts began to use BIA.

1976

RJL Systems and the first impedance meter

In 1979, RJL Systems commercialized the impedance meter for the first time and the BIA method began to gain popularity.

The device measured impedance by attaching electrodes on the back of the right hand and a top of the right foot of a patient and conducting a current of 50kHz through the right half of the body.

Prior to this, body composition could only be measured by caliper or underwater weighing. Such methods needed to be carried out by skilled people and installation was not easy. Also, only specific types of patients could benefit from them.

BIA however, was easy, fast, less expensive and less intrusive. Therefore, many body composition researchers, nutritionists, and medical experts began to use BIA.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Discovering limitations to BIA with empirical data

Research by Lukaski, Segal and other scholars accelerated the evolution of BIA. Studies proved BIA had high correlation with gold standard methods like underwater weighing and DEXA. But technical limitations of BIA began to surface in the late 1980s.

One limitation was that BIA assumed the human body to be in the shape of one cylinder and used a single frequency (50 kHz).

This may have worked for patients with standard body types, but it wasn’t as accurate for other populations.

So, researchers came up with various equations in addition to the impedance index so as to complement the technical limitation of BIA and achieve greater accuracy for patient groups of different age, gender etc.

1980

Discovering limitations to BIA with empirical data

Research by Lukaski, Segal and other scholars accelerated the evolution of BIA. Studies proved BIA had high correlation with gold standard methods like underwater weighing and DEXA. But technical limitations of BIA began to surface in the late 1980s.

One limitation was that BIA assumed the human body to be in the shape of one cylinder and used a single frequency (50 kHz).

This may have worked for patients with standard body types, but it wasn’t as accurate for other populations.

So, researchers came up with various equations in addition to the impedance index so as to complement the technical limitation of BIA and achieve greater accuracy for patient groups of different age, gender etc.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Lukaski and Kushner develop empirical equations

To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Lukaski and Kushner develop empirical equations

To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Discovering limitions to BIA with empirical data

Research by Lukaski, Segal and other scholars accelerated the evolution of BIA.

Studies proved BIA had high correlation with gold standard methods like underwater weighing and DEXA. But technical limitations of BIA began to surface in the late 1980s.

One limitation was that BIA assumed the human body to be in the shape of one cylinder and used a single frequency (50 kHz).

This may have worked for patients with standard body types, but it wasn’t as accurate for other populations.

So, researchers came up with various equations in addition to the impedance index so as to complement the technical limitation of BIA and achieve greater accuracy for patient groups of different age, gender etc.

1980

Discovering limitions to BIA with empirical data

Research by Lukaski, Segal and other scholars accelerated the evolution of BIA.

Studies proved BIA had high correlation with gold standard methods like underwater weighing and DEXA. But technical limitations of BIA began to surface in the late 1980s.

One limitation was that BIA assumed the human body to be in the shape of one cylinder and used a single frequency (50 kHz).

This may have worked for patients with standard body types, but it wasn’t as accurate for other populations.

So, researchers came up with various equations in addition to the impedance index so as to complement the technical limitation of BIA and achieve greater accuracy for patient groups of different age, gender etc.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1980

Home-use BIA Devices

Due to technological constraints, BIA devices became home-use devices rather than hospital devices.

In the late 1980s, Japanese manufacturers released various types of BIA-based body composition devices that could easily be used by the general public.

Some devices measured the impedance between two feet as the user stands on the scale, while another would measure the impedance between two hands while holding the device.

1980

Home-use BIA Devices

Due to technological constraints, BIA devices became home-use devices rather than hospital devices.

In the late 1980s, Japanese manufacturers released various types of BIA-based body composition devices that could easily be used by the general public.

Some devices measured the impedance between two feet as the user stands on the scale, while another would measure the impedance between two hands while holding the device.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1992

The History of BIA Technology

Since the inaccuracy of BIA is due to technical limitations, many argued that this could be improved upon. In 1992, Kushner claimed that the human body is made up of five cylinders (right arm, left arm, torso, right leg, left leg) instead of one.

While the thin limbs affect the total impedance, the torso, which has the largest cross-sectional area, has little impact on impedance. However, since the torso makes up 50% of lean body mass, Kushner emphasized that measuring the impedance of the body torso separately would be very important.

Measuring the total impedance alone would not be sufficient but all five parts must be measured separately at different frequencies, making a distinction between extracellular water and intracellular water.

In other words, the technical limitations of BIA should be overcome by measuring different parts at different frequencies.

1992

The History of BIA Technology

Since the inaccuracy of BIA is due to technical limitations, many argued that this could be improved upon. In 1992, Kushner claimed that the human body is made up of five cylinders (right arm, left arm, torso, right leg, left leg) instead of one.

While the thin limbs affect the total impedance, the torso, which has the largest cross-sectional area, has little impact on impedance. However, since the torso makes up 50% of lean body mass, Kushner emphasized that measuring the impedance of the body torso separately would be very important.

Measuring the total impedance alone would not be sufficient but all five parts must be measured separately at different frequencies, making a distinction between extracellular water and intracellular water.

In other words, the technical limitations of BIA should be overcome by measuring different parts at different frequencies.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

1996

Dr. Cha creates the InBody body composition analyzer

In 1996, Dr. Kichul Cha, a bioengineering major at Harvard Medical School, developed the world’s first 8-point tactile electrode system with direct segmental analysis which measures impedance for the five different parts of the body at multiple frequencies.

Measuring impedance by applying currents of multi-frequencies on the five parts of the body took a separate impedance measurement. Moreover, it allows separately checking torso impedance. This yielded highly accurate results without using empirical data. Thus, InBody body composition analyzers became a precise medical device. Impedance values for all cylinders, including the torso, can be found on the InBody Result Sheet.

Many BIA products today provide muscle mass for each section of the body. However, most of such products are unable to take sectional impedance measurements, especially the torso impedance.

However, as shown on an InBody Result Sheet, you can see the impedance values of all five parts of the body including the torso with the use of both high and low frequencies.

1996

Dr. Cha creates the InBody body composition analyzer

In 1996, Dr. Kichul Cha, a bioengineering major at Harvard Medical School, developed the world’s first 8-point tactile electrode system with direct segmental analysis which measures impedance for the five different parts of the body at multiple frequencies.

Measuring impedance by applying currents of multi-frequencies on the five parts of the body took a separate impedance measurement. Moreover, it allows separately checking torso impedance. This yielded highly accurate results without using empirical data. Thus, InBody body composition analyzers became a precise medical device. Impedance values for all cylinders, including the torso, can be found on the InBody Result Sheet.

Many BIA products today provide muscle mass for each section of the body. However, most of such products are unable to take sectional impedance measurements, especially the torso impedance.

However, as shown on an InBody Result Sheet, you can see the impedance values of all five parts of the body including the torso with the use of both high and low frequencies.

This is a sample timeline content. To increase the accuracy of the results, researchers came up with empirical equations that utilized empirical data such as gender and age to calculate a person’s body composition. Empirical data is knowledge acquired by means of observation or experimentation. By collecting data on a sample population that (hopefully) represents the variance of the entire population, researchers attempt to derive trends that may be used to predict outcomes. In body composition, researchers identify these trends in muscle and fat mass; they use this data to predict body composition based on specific variables (age, gender, ethnicity, etc.)

In 1986, Lukaski used the published equations using impedance index, body weight and reactance; and in 1986, Kushner published equations using the impedance index, body weight and gender. Although empirical estimations could give you an accurate estimate of a general user’s body composition, there are significant problems when they are used for medical purposes. Let’s suppose that there is a device that uses an empirical equation to calculate total body water. And there are two people who have same amount of lean body mass, but one person is 30 years old, and the other one is 40 years old.

Even though they have the same amount of lean body mass, the empirical equations will calculate that these two people will have 0.8 L difference in total body water only because of the age, which is neither fair nor accurate.

Revolutionizing BIA Technology with InBody

InBody’s medical-grade body composition analyzers rely on four pillars of technology to give you extremely accurate and precise BIA results that are highly correlated to gold-standard methods.

8-Point Tactile
Electrode System

Wanneer de impedantie wordt gemeten met behulp van elektroden, treedt contactweerstand op.

InBody pakt contactweerstand aan door het strategisch plaatsen van elektroden om de impedantie in het lichaam nauwkeurig te meten.

Wanneer de impedantie wordt gemeten met behulp van elektroden, treedt contactweerstand op.

InBody pakt contactweerstand aan door het strategisch plaatsen van elektroden om de impedantie in het lichaam nauwkeurig te meten.

8-Point Tactile
Electrode System

Wanneer de impedantie wordt gemeten met behulp van elektroden, treedt contactweerstand op.

InBody pakt contactweerstand aan door het strategisch plaatsen van elektroden om de impedantie in het lichaam nauwkeurig te meten.

8-puntige Elektrode Systeem

BIA Tech Problem

If the measurement starting position changes, impedance also changes and introduces error.

InBody Solution

8-Point Tactile Electrode System with Thumb Electrodes

Direct Segmental
Measurements

InBody levert afzonderlijke metingen voor elk van de 5 cilinders van het lichaam (linkerarm, rechterarm, linkerbeen, rechterbeen en romp) om nauwkeurige gegevens te leveren.

Wanneer de impedantie wordt gemeten met behulp van elektroden, treedt contactweerstand op.

InBody pakt contactweerstand aan door het strategisch plaatsen van elektroden om de impedantie in het lichaam nauwkeurig te meten.

Direct Segmental
Measurements

InBody levert afzonderlijke metingen voor elk van de 5 cilinders van het lichaam (linkerarm, rechterarm, linkerbeen, rechterbeen en romp) om nauwkeurige gegevens te leveren.

Geen empirische schattingen op meetwaarden

BIA Tech Problem

Traditional BIA views the human body as one cylinder.

However, the torso of the body needs to be measured separately because even an error of 1-2 ohms in measurement can lead to substantial error in total body water measurements.

InBody Solution

Direct segmental multi-frequency bioelectrical impedance analysis (DSM-BIA) views the human body as five cylinders: left arm, right arm, left leg, right leg and the torso.

InBody provides independent measurements for each cylinder to provide accurate measurements for the entire body.

Multiple
Frequencies

InBody maakt gebruik van verschillende stromen op verschillende frequenties om de meest precieze analyse van het lichaamsvocht te leveren.

Wanneer de impedantie wordt gemeten met behulp van elektroden, treedt contactweerstand op.

InBody pakt contactweerstand aan door het strategisch plaatsen van elektroden om de impedantie in het lichaam nauwkeurig te meten.

Multiple
Frequencies

InBody maakt gebruik van verschillende stromen op verschillende frequenties om de meest precieze analyse van het lichaamsvocht te leveren.

Meerdere Frequenties

BIA Tech Problem

Most BIA devices only use one frequency at 50 kHz to measure total body water.

Since 50 kHz or lower frequencies barely pass through the cell membrane, accurate measurement of the impedance in the intracellular water was not possible.

The ability to measure accurate intracellular vs. extracellular water is important for those in nephrology or rehabilitation.

InBody Solution

InBody uses varying high and low frequencies to measure intracellular and extracellular water for the most precise total body water analysis.

The use of multiple frequencies make InBody devices accurate enough to be trusted for use in the medical field.

No
Estimations

De informatie over leeftijd en geslacht wordt alleen gebruikt om referentiebereiken of scores te geven op basis van statistische gegevens en heeft geen invloed op de gemeten waarden van de lichaamssamenstelling.

Wanneer de impedantie wordt gemeten met behulp van elektroden, treedt contactweerstand op.

InBody pakt contactweerstand aan door het strategisch plaatsen van elektroden om de impedantie in het lichaam nauwkeurig te meten.

No
Estimations

De informatie over leeftijd en geslacht wordt alleen gebruikt om referentiebereiken of scores te geven op basis van statistische gegevens en heeft geen invloed op de gemeten waarden van de lichaamssamenstelling.

Geen empirische schattingen op meetwaarden

BIA Tech Problem

Empirical equations were created and used to compensate for the lack of torso impedance (due to the whole-body impedance measurement).

These empirical equations plugged data in such as age, gender, and ethnicity to calculate a user’s body composition instead of measuring an individual’s actual body composition.

InBody Solution

No empirical estimations or equations are used to calculate your body composition.

InBody measures your impedance independently, so your results are not affected by your age, ethnicity, or gender.

High Correlation to
Gold Standard Methods

Because of its technology, InBody has become one of the most accurate BIA devices on the market and has been found to have a high correlation of 0.99 to DEXA for lean body mass in a population of adults.

Which InBody is
right for you?

Get in touch

"*" indicates required fields

Company

Support

How it works

Follow us

Body Composition Analyzers

Hand Dynamometer

Blood Pressure Monitors

Software Solutions

InBody Academy

Health And Wellness

Medical Applications

Body Composition Analyzers

Hand Dynamometer

Blood Pressure Monitors

Software Solutions

InBody Academy

Health And Wellness

Medical Applications

InBody Technologie

What is Bio-Electrical Impedance Analysis (BIA)?

Behind the scenes

What is Bio-Electrical Impedance Analysis (BIA)?

Behind the scenes

The Human Body and Impedance

The Human Body and Impedance

The Concept of Reactance

Putting It All Together

InBody timeline

1969

Hoffer and the Impedance Index

1969

Hoffer and the Impedance Index

1976

RJL Systems and the first impedance meter

1976

RJL Systems and the first impedance meter

1980

Discovering limitations to BIA with empirical data

1980

Discovering limitations to BIA with empirical data

1980

Lukaski and Kushner develop empirical equations

1980

Lukaski and Kushner develop empirical equations

1980

Discovering limitions to BIA with empirical data

1980

Discovering limitions to BIA with empirical data

1980

Home-use BIA Devices

1980

Home-use BIA Devices

1992

The History of BIA Technology

1992

The History of BIA Technology

1996

Dr. Cha creates the InBody body composition analyzer

1996

Dr. Cha creates the InBody body composition analyzer

1969

Hoffer and the Impedance Index

1969

Hoffer and the Impedance Index

1976

RJL Systems and the first impedance meter

1976

RJL Systems and the first impedance meter

1980

Discovering limitations to BIA with empirical data

1980

Discovering limitations to BIA with empirical data

1980

Lukaski and Kushner develop empirical equations

1980

Lukaski and Kushner develop empirical equations

1980

Discovering limitions to BIA with empirical data

1980

Discovering limitions to BIA with empirical data

InBody
Technologie

What is Bio-Electrical
Impedance Analysis (BIA)?

What is Bio-Electrical
Impedance Analysis (BIA)?

8-Point Tactile
Electrode System

8-Point Tactile
Electrode System

Direct Segmental
Measurements

Direct Segmental
Measurements

Multiple
Frequencies