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Dear sucscribers,
Some time ago I posted the following question on BIOMCH-L. I received
two responses which are listed below.
Thanks
Carlijn Bouten
-------------------------------------------------------------
Question:
I am looking for research relating body acceleration (measured with
accelerometers or obtained from kinematic data in movement analysis)
to mechanical energy expenditure or power during human locomotion.
This to find a theoretical basis for the experimentally established
linear relationship between metabolic energy expenditure and accele-
ration, measured with accelerometers on the human body. This relation-
ship is demonstrated by many authors - including myself - in studies
on the assessment of (daily) physical activity. In these studies
accelerations are usually measured on the low back, near the body
centre of mass, and converted to the time integral of absolute accele-
ration ('activity counts').
In order to relate metabolic energy expenditure to the mechanical
parameter 'activity count', we now focus on the relationship between
mechanical energy expenditure or power and 'activity count', assuming
a direct correlation between metabolic and mechanical energy for a
given activity (i.e. mechanical efficiency).
Carlijn Bouten
Eindhoven University of Technology
Division of Fundamentals
P.O.Box 513
NL-5600 MB EINDHOVEN
The Netherlands
e-mail: carlijn@WFW.WTB.TUE.NL
------------------------------------------------------------------
Date: Wed, 11 May 1994 16:19:06 -0700
From: sabelman@roses.Stanford.EDU (Eric Sabelman)
Subject: body motion accelerometry
In response to your posting, we offer the following information on the
use of accelerometers for human body motion analysis. Our experience
has been mainlyv with micro-machined silicon piezoresistive accelero-
meters. We do not recommend using silicon accelerometers made by
older methods (e.g.: Entran and others) because of high cost, fragile
wiring and change in electrical characteristics after impact loading.
Suppliers of micromachined devices include IC Sensors, NovaSensor and
SenSym. (SenSym, I have been told, has been bought and may leave
the field.) Each uses slightly different chip design and packaging.
Note also that piezoresistive sensors detect the steady-state pull of
gravity as well as inertial acceleration due to the start and stop of
motion. Piezoelectric sensors can detect only the latter, with a
low-frequency cutoff typically about 10 Hz, causing slow motion data
to be lost. The gravitational component superimposed on the inertial
component prevents simple integration to calculate change in position,
but has the advantage of providing a continuous vertical reference.
Integration is also made difficult by a 1 to 2% error due to gravity
in the non-sensitive axis direction. These constraints led us to
decide upon pattern-matching, peak-detection and Fourier spectrum
analytical methods, rather than try to derive absolute position by
double integration. We also use the sensors as tilt-meters, by fil-
tering out signals above about 0.2 Hz, on the assumption that higher
frequencies represent the inertial component (valid only for con-
strained motions). If the signal is high-pass-filtered, these ac-
celerometers are equivalent to piezoelectric ones, but without need
for charge amplifiers.
Our experience has been mainly with 15 G range IC Sensors devices,
most recently in the model 3031 surface mount package. At 0.3 X 0.3 X
0.14 inches, these are small enough for unobtrusive mounting on the
body, even after assembly of three sensors for multi-axis sensing.
Cost is very reasonable ($58/channel) compared to piezoelectric
devices. The company supplies a calibration sheet for each sensor
only at extra cost; since there are significant variations in offset
and slope of the voltage-to-acceleration curve within a batch of
sensors; we calibrate each sensor periodically in a fixture that
places it with its sensitive axis up, down and horizontal (11 and 0
G). Two out of about 40 sensors have failed (showing uncontrolled
drift, probably due to oxide in an internal connection) and were
replaced by the company under warranty. The company has a long lead
time (90 days) before delivery of 15 G 3031 accelerometers, due to
selection for high sensitivity out of batches of 120 G sensors; the
company plans to produce batches specifically for 15 G range as
demand increases and techniques improve.
Presently, the cables from the sensors are plugged into a custom-made
amplifier board inside a self-contained wearable computer/recorder.
This allows the wearer to move about without being tethered to a fixed
computer. The cost and complexity of a radio telemetry system for 12
data channels, and the need to acquire data outside the laboratory,
precluded transmitting the sensor outputs to a fixed receiver. After
40 to 180 minutes of data collection, a telephone-type modular cable
is plugged into the wearable recorder to send the stored data to a
fixed computer.
While the wearable recorder's microcomputer is slow and thus cannot
perform the real-time signal analysis we eventually want to do, it
functions quite well for taking data at up to 50 samples per second
with 12 channels per sample accurate to one part in 1024. Recording
is started, stopped and coded for identification of the wearer's
activity using an infrared remote control, so the experimenter
does not have to have physical contact.
The need for 12 channels arises because we are trying to describe both
translational and rotational motion of the head and trunk, requiring a
minimum of 6 degrees-of-freedom assuming each is a rigid body (not
exactly true, but close enough). Fewer channels leads to ambiguity and
a high number of false alarms if the system is used as a fall detec-
tor. We anticipate clinical use of accelerometric instrumentation to
occur in three stages: first, as a diagnostic tool to quantify hither-
to qualitative measures of balance; second, as a biofeedback device
during therapy; and third, as a fall-prevention aid P which might be
called a Rbalance orthosisS P for continuous use by institutionalized
and community-living fall-prone elderly.
Your interest is in deriving energy expenditure from body acceler-
ation, which also should be more precise if calculated from multiple
sites, not just at the center of mass. I am aware of one paper (Balo-
gun, J.A., Amusa, L.O., Onyewadume, I.U., Factors affecting 'Caltrac'
and 'Calcount' accelerometer output, Physical Therapy, 68:1500-1504,
1988) which describes large variations in "energy" depending on where
on the body a single accelerometer is placed. I would appreciate
receiving copies of your papers on the subject, especially if
you have overcome this difficulty.
The VA Rehabilitation R&D Center encourages establishing multi-center
collaborations for evaluation of devices we have developed, and a
number of such collaborations are explicitly included in the recently
approved 3-year extension of the grant under which this work is being
carried out. We are open to additional collaborations to the extent
of our resources. We are also open to negotiation of Cooperative R&D
Agreements with private industry for commercialization of this tech-
nology. If you are interested in pursuing either option, please
e-mail, write or call me at 415-493-5000 x 3345.
Eric E. Sabelman, PhD Section Chief, Human/Machine Integration Section
VA Rehabilitation R&D Center 3801 Miranda Ave #153 Palo Alto, CA 94304
----------------------------------------------------------------
Wed May 11 15:41:41 1994
From: Paul Guy
Hi Carlijn,
We have an ftp site where I have put some data (2D) of a typical
subject. This is one of the many hundreds that we have collected, and
is otherwise noteable in that is one of the sample subjects used in
Dr. Winter's textbook 'BIOMECHANICS and MOTOR CONTROL of HUMAN MOVEM-
ENT',2nd edition,John Wiley and Sons,1990.
The site is 'gaitlab1.uwaterloo.ca', and the file is
'/pub/foryou/wn35b.km'. You should look at the 'readme' file in the
same directory. This file is a listing from a fortran program, and
will be a lot more readable if you print it on a 132 column printer
(or standard printer in compressed mode). You can import this file
into a spreadsheet, just be careful of the positions of the column
titles..
Don't take this data as 'gospel', it was made under conditions that
might make it irrelevant for your purposes.
We have data that might be more relevant to your purposes, but I
thinkwe'd have to enter into a more formal correspondence before
satisfying any of your needs.
-Paul
-------------------------------------------------------------
Some time ago I posted the following question on BIOMCH-L. I received
two responses which are listed below.
Thanks
Carlijn Bouten
-------------------------------------------------------------
Question:
I am looking for research relating body acceleration (measured with
accelerometers or obtained from kinematic data in movement analysis)
to mechanical energy expenditure or power during human locomotion.
This to find a theoretical basis for the experimentally established
linear relationship between metabolic energy expenditure and accele-
ration, measured with accelerometers on the human body. This relation-
ship is demonstrated by many authors - including myself - in studies
on the assessment of (daily) physical activity. In these studies
accelerations are usually measured on the low back, near the body
centre of mass, and converted to the time integral of absolute accele-
ration ('activity counts').
In order to relate metabolic energy expenditure to the mechanical
parameter 'activity count', we now focus on the relationship between
mechanical energy expenditure or power and 'activity count', assuming
a direct correlation between metabolic and mechanical energy for a
given activity (i.e. mechanical efficiency).
Carlijn Bouten
Eindhoven University of Technology
Division of Fundamentals
P.O.Box 513
NL-5600 MB EINDHOVEN
The Netherlands
e-mail: carlijn@WFW.WTB.TUE.NL
------------------------------------------------------------------
Date: Wed, 11 May 1994 16:19:06 -0700
From: sabelman@roses.Stanford.EDU (Eric Sabelman)
Subject: body motion accelerometry
In response to your posting, we offer the following information on the
use of accelerometers for human body motion analysis. Our experience
has been mainlyv with micro-machined silicon piezoresistive accelero-
meters. We do not recommend using silicon accelerometers made by
older methods (e.g.: Entran and others) because of high cost, fragile
wiring and change in electrical characteristics after impact loading.
Suppliers of micromachined devices include IC Sensors, NovaSensor and
SenSym. (SenSym, I have been told, has been bought and may leave
the field.) Each uses slightly different chip design and packaging.
Note also that piezoresistive sensors detect the steady-state pull of
gravity as well as inertial acceleration due to the start and stop of
motion. Piezoelectric sensors can detect only the latter, with a
low-frequency cutoff typically about 10 Hz, causing slow motion data
to be lost. The gravitational component superimposed on the inertial
component prevents simple integration to calculate change in position,
but has the advantage of providing a continuous vertical reference.
Integration is also made difficult by a 1 to 2% error due to gravity
in the non-sensitive axis direction. These constraints led us to
decide upon pattern-matching, peak-detection and Fourier spectrum
analytical methods, rather than try to derive absolute position by
double integration. We also use the sensors as tilt-meters, by fil-
tering out signals above about 0.2 Hz, on the assumption that higher
frequencies represent the inertial component (valid only for con-
strained motions). If the signal is high-pass-filtered, these ac-
celerometers are equivalent to piezoelectric ones, but without need
for charge amplifiers.
Our experience has been mainly with 15 G range IC Sensors devices,
most recently in the model 3031 surface mount package. At 0.3 X 0.3 X
0.14 inches, these are small enough for unobtrusive mounting on the
body, even after assembly of three sensors for multi-axis sensing.
Cost is very reasonable ($58/channel) compared to piezoelectric
devices. The company supplies a calibration sheet for each sensor
only at extra cost; since there are significant variations in offset
and slope of the voltage-to-acceleration curve within a batch of
sensors; we calibrate each sensor periodically in a fixture that
places it with its sensitive axis up, down and horizontal (11 and 0
G). Two out of about 40 sensors have failed (showing uncontrolled
drift, probably due to oxide in an internal connection) and were
replaced by the company under warranty. The company has a long lead
time (90 days) before delivery of 15 G 3031 accelerometers, due to
selection for high sensitivity out of batches of 120 G sensors; the
company plans to produce batches specifically for 15 G range as
demand increases and techniques improve.
Presently, the cables from the sensors are plugged into a custom-made
amplifier board inside a self-contained wearable computer/recorder.
This allows the wearer to move about without being tethered to a fixed
computer. The cost and complexity of a radio telemetry system for 12
data channels, and the need to acquire data outside the laboratory,
precluded transmitting the sensor outputs to a fixed receiver. After
40 to 180 minutes of data collection, a telephone-type modular cable
is plugged into the wearable recorder to send the stored data to a
fixed computer.
While the wearable recorder's microcomputer is slow and thus cannot
perform the real-time signal analysis we eventually want to do, it
functions quite well for taking data at up to 50 samples per second
with 12 channels per sample accurate to one part in 1024. Recording
is started, stopped and coded for identification of the wearer's
activity using an infrared remote control, so the experimenter
does not have to have physical contact.
The need for 12 channels arises because we are trying to describe both
translational and rotational motion of the head and trunk, requiring a
minimum of 6 degrees-of-freedom assuming each is a rigid body (not
exactly true, but close enough). Fewer channels leads to ambiguity and
a high number of false alarms if the system is used as a fall detec-
tor. We anticipate clinical use of accelerometric instrumentation to
occur in three stages: first, as a diagnostic tool to quantify hither-
to qualitative measures of balance; second, as a biofeedback device
during therapy; and third, as a fall-prevention aid P which might be
called a Rbalance orthosisS P for continuous use by institutionalized
and community-living fall-prone elderly.
Your interest is in deriving energy expenditure from body acceler-
ation, which also should be more precise if calculated from multiple
sites, not just at the center of mass. I am aware of one paper (Balo-
gun, J.A., Amusa, L.O., Onyewadume, I.U., Factors affecting 'Caltrac'
and 'Calcount' accelerometer output, Physical Therapy, 68:1500-1504,
1988) which describes large variations in "energy" depending on where
on the body a single accelerometer is placed. I would appreciate
receiving copies of your papers on the subject, especially if
you have overcome this difficulty.
The VA Rehabilitation R&D Center encourages establishing multi-center
collaborations for evaluation of devices we have developed, and a
number of such collaborations are explicitly included in the recently
approved 3-year extension of the grant under which this work is being
carried out. We are open to additional collaborations to the extent
of our resources. We are also open to negotiation of Cooperative R&D
Agreements with private industry for commercialization of this tech-
nology. If you are interested in pursuing either option, please
e-mail, write or call me at 415-493-5000 x 3345.
Eric E. Sabelman, PhD Section Chief, Human/Machine Integration Section
VA Rehabilitation R&D Center 3801 Miranda Ave #153 Palo Alto, CA 94304
----------------------------------------------------------------
Wed May 11 15:41:41 1994
From: Paul Guy
Hi Carlijn,
We have an ftp site where I have put some data (2D) of a typical
subject. This is one of the many hundreds that we have collected, and
is otherwise noteable in that is one of the sample subjects used in
Dr. Winter's textbook 'BIOMECHANICS and MOTOR CONTROL of HUMAN MOVEM-
ENT',2nd edition,John Wiley and Sons,1990.
The site is 'gaitlab1.uwaterloo.ca', and the file is
'/pub/foryou/wn35b.km'. You should look at the 'readme' file in the
same directory. This file is a listing from a fortran program, and
will be a lot more readable if you print it on a 132 column printer
(or standard printer in compressed mode). You can import this file
into a spreadsheet, just be careful of the positions of the column
titles..
Don't take this data as 'gospel', it was made under conditions that
might make it irrelevant for your purposes.
We have data that might be more relevant to your purposes, but I
thinkwe'd have to enter into a more formal correspondence before
satisfying any of your needs.
-Paul
-------------------------------------------------------------