Author: Che-Chang Yang(2006-09-01);
recommendation: Yeh-Liang Hsu (2006-09-01).
Note: This article is Chapter 2 of Che-Chang Yang’s Master thesis “Development
of a Portable System for Physical Activity Assessment in a Home Environment.”
Chapter 2. Accelerometry for
human body movement
2.1 Motion sensors
activity assessment, body-fixed motion sensors have been accepted as the
preferred alternative to optical or magnetic sensors. Various motion sensors
have been designed for this purpose, ranging from mechanical pedometers and
actometers to electronic gyroscope and accelerometers.
2.1.1 Mechanical sensors
A pedometer, or
a step-counter, is one of the earliest mechanical motion sensors (Figure 2.1).
It is usually worn at the waist or at the ankle to count each step when jumping,
walking or running. The impulse of each step when landing is registered in a
counting mechanism. Although electrical pedometers are available, individual
calibrations of a stride length are still necessary. Moreover, the pedometer
cannot reflect and evaluate the intensity of movement and energy expenditure.
Actometers that have been designed to record physical activity are not always
the motion sensors in the metrological sense. They may differ largely from one
another to meet specific applications. Schulman and Reisman  proposed a
modified actometer which was designed as a wristwatch which provides
measurement correlating with energy expenditure.
Figure 2.1 mechanical pedometers
2.1.2 Electronic sensors
motion sensors, such as gyroscopes and accelerometers, are most commonly adopted
in place of mechanical motion sensors due to the superiority of precise
response to both frequency and intensity of body movement. Gyroscopes [Figure
2.2] are widely used in vehicle navigation. A gyroscope which consists of a
vibrating element coupled to a sensing element is used to detect angular
velocity. The operation principle of a gyroscope is based on the Coriolis
effect which is an apparent force that arises in a rotational reference frame
and is proportional to the angular rate of rotation. The advantage of using
gyroscopes is that the angular rate signal is less noisy than an acceleration
signal since acceleration is the derivative of velocity and involves higher
frequency components. Yet, signal drift and being sensitive to shock and impulse
are the major drawbacks of using a gyroscope [Najafi, 2002]. Aminian and Najafi
used a gyroscope as the kinematic sensor to measure trunk tilt for physical
Figure 2.2 A
gyroscope [Murata, Japan]
The use of
accelerometers to measure body movements dates back to the early 1970’s [Moris, 1973]. Operating
principles of electronic accelerometers are based on piezo-electric,
piezo-resistive and capacitive properties. The piezo-electric element which
behaves as a damped-spring generates an electrical charge in response to
external forces. In a piezo-resistive accelerometer, the actuating element is
replaced by a resistive silicon circuit that generates differential impedance
in response to external forces. A capacitive accelerometer functions on the
principle of differential capacitance. Acceleration causes displacement of a
silicon structure and results in a change in capacitance. Change in capacitance
is transduced into an analogue voltage which is proportional to acceleration.
Piezo-resistive or capacitive accelerometers are usually smaller than
piezo-electric ones. An important distinction is that piezo-resistive or
capacitive accelerometers respond to constant acceleration as well as AC
components while the piezo-electric accelerometers do not. Piezo-resistive or
capacitive accelerometers are preferable due to the DC-responsive property
which enables easier calibration. Most important of all, inclination angles of a
body segment with respect to its fixed joint axes at rest can be determined by
the response to the constant gravitational component. With MEMS manufacturing
technology, tri-axial accelerometers can be miniaturized in small packages as
shown in Figure 2.3.
Figure 2.3 Electronic accelerometers
In addition to those
motion sensors, the goniometer, electronic compass and foot pressure pad have
also been designed for this purpose. A goniometer is composed of a series of
strain gauges in the flexible tube which connects two end blocks. It can be
used to measure the angle between two segments as shown in Figure 2.4. An
electronic compass uses magnetic effect to measure the orientation of a
subject. Kemp et al.  have
proposed the possibilities of using an electronic compass to determine a body’s
position. Foot pressure pads (or resistive switch) attached to the sole are
used to analyze gait during locomotion [Zhu et
Figure 2.4 Goniometer [MindWare Technologies]
2.2 Introduction to Kionix KXM52-1050 tri-axial
2.2.1 Kionix KXM52-1050 tri-axial accelerometer
research, the motion sensor used was the KXM52-1050 tri-axial accelerometer. It was chosen as it has several
advantages over other accelerometers. The Kionix KXM52-1050 tri-axial
accelerometer, as shown in Figure 2.5, is a high performance silicon
micro-machined linear accelerometer consisting of a sensing element and a CMOS
signal conditioning Application Specific Integrated Circuit (ASIC) packaged in
a standard 5×5×1.8mm DFN(DualFlat
Non-lead). The device functions on the principle of differential capacitance.
Acceleration causes displacement of a silicon structure resulting in a change
in capacitance. A signal-conditioning CMOS technology ASIC detects and
transforms changes in capacitance into an analogue voltage which is
proportional to acceleration. The general specification of Kionix KXM52-1050 is
listed in the Appendix.
Figure 2.5 Kionix KXM52 series accelerometers
Figure 2.6 shows
the functional diagram of KXM52. Three sensors measure the accelerations along
X, Y, and Z axes. The charge amplifiers transfer the differential capacitance
(charge) into an analog signal and then amplify the signal to a higher voltage
level. The oscillator generates differential charge and results in specific
outputs when the self-test mode is activated. The built-in 32kW resistors and
the external, user-defined bypass capacitors comprise low-pass filters for
Figure 2.6 The functional diagram of Kionix KXM52
2.2.2 Typical schematic
Figure 2.7 shows the typical
schematic that is used in the postural sensory module. The output will change
with supply voltage(Vdd)
variations ranging from 2.7(or 2.5)V to 5.5V. 3.3V is recommended as the output
of the KXM52-1050 is programmed and tested at 3.3V power supply. In this
schematic, a 0.1mF capacitor (C1)
cross Vdd to ground is recommended
to decouple the noise of the power supply. For more decoupling, a ferrite bead
or small resistors may be inserted into the supply line.
Figure 2.7 Typical schematic of KXM52
Capacitors C2 to C4 that cross the output pins to ground are used to
adjust the output bandwidth of each axis. These capacitors with the 32kW
resistor comprise RC low-pass filtering circuits. The desired bandwidth is determined by
the Equation (1):
The output bandwidth is an
important parameter when using the accelerometer. For KXM52-1050, the output
bandwidth of the X and Y axes ranges from DC to 3kHz, and that
of the Z axis is from DC to 1.5kHz.
The choice of desired bandwidth depends upon the application. For example, a
higher output bandwidth is advisable for the applications which require fast
and sensitive motion detection. As for human postural detection required in
this research, only low bandwidth is needed. In Figure 2.7, 0.1mF capacitors are
adopted, which limits the bandwidth at about 50Hz (Equation (2)).
Pin 9 of
KXM52-1050 is the power shutdown pin. When this pin is left floating or
grounded, the KXM52 is shut down and draws very little power. When tied to Vdd, the unit is fully
functional. Pin 10 is the self-test pin, and 0.25Vdd, 0.5Vdd
and Vdd can be fed
to it to check the output signals. If not in use, this pin must be tied to
ground. Figure2.8 shows the sensing module and its PCB layout whose size is 25×20mm. This small module can
be connected to specific receivers like DDS or any compatible devices.
Figure 2.8 The sensing module and its PCB Layout
2.2.3 Output response
illustrates the coordinates of acceleration in KXM52-1050, and Figure 2.10 and 2.11
show the response of this unit with respect to different directions of
accelerations and with respect to gravitational direction in different
positions, respectively. If there is no acceleration applied along an axis, the
output voltage Voff equals half Vdd. If acceleration exists towards a positive direction, the output
voltage increases (Vout> Voff) and vice versa.
range of KXM52-1050 of each axis is ±2g and the output varies with acceleration linearly at the rate of
660mV/g. Equation (3) shows the relation:
when KXM52-1050 is put horizontally and still, there are no gravitational
effects along X and Y axes, and VoutX=VoutY=Vdd. Only 1g vertical
acceleration along the negative direction of the Z-axis is detected whose
effect can be regarded as the accelerometer moving in the positive direction of
Z-axis. In this condition, the output voltage at pin 14 is VoutY>Voff+660mV(at 3.3V Vdd).
Figure 2.9 The coordinates of acceleration of
Figure 2.10 Output response due to directions of
Figure 2.11 Output response due to gravitational
directions in different positions
sensing is a common application for low-g accelerometers. Figure 2.12 indicates
the tilt assignments (pitch and roll), where f, r, and q stand for the tilt angle with respect
to X, Y and Z axes relative to the
ground. Equation (4) identifies the relation between the tilt angles and
accelerations of each axis.
Figure 2.12 Pitch and roll assignments relative to
A simple test is
conducted when KXM52-1050 rotates about the X axis from 0o to 180o, and the data is shown in
Table 1 and Figure 2.13. In this figure, the bold blue curve is obtained by
actual test as compared with the narrow black curve which approximates a
sinusoidal form generated according to the specification. Referring to Equation
(3), 1g acceleration yields an
output of about 2.31V, and 0 g yields about 1.65V. When f, r and q equal 0o, the outputs of the X and Y
axes have the maximum sensitivity, while the Z axis has the minimum
sensitivity. Occurrence of slight signal deviation is probably due to the
offset effect caused by temperature variation and instrumentation variances.
Figure 2.14 shows a linear response to gravity (acceleration) from 0g to 1g.
Table 1. Output voltages of KXM52-1050 w.r.t
specific tilt angles (X axis)
Figure 2.13 Tilt angle vs. output voltage of
X-axis from 0˚ to 180˚
Figure 2.14 Acceleration (0~1g) vs. output voltage
2.3 Human body acceleration
2.3.1 Frequency and amplitude of the body motion
amplitude of the body motion are two major components when analyzing
acceleration data. In general, even for exercises such as running or jumping,
frequencies and amplitudes of accelerations caused by body movements are relatively
low. This implies that in data registration, it is not necessary to use high
sampling rate. When walking at normal velocity, the frequencies are higher in
vertical direction than that in both medio-lateral and antero-posterior
directions. Meanwhile, Cappozzo’s research showed that the acceleration at head
(cranial part) ranges from 0.8~5Hz whereas higher frequencies up to 60Hz may occur
at the foot (caudal part) when the heel striking [Cappozzo, 1982]. Bhattacharya
et al.  found the majority of frequency
components during running to fall between 1~18Hz in the vertical direction at the
ankle. Although frequencies up to 60Hz have been reported in Cappozzo’s
studies, these might be caused by external vibration as such high frequencies
seem irrational in normal body movement.
characteristics are similar to the frequency spectrum described above. The
amplitudes are higher in vertical direction than in both medio-lateral and
antero-posterior directions when walking and locomotion. The amplitudes
increase from the head toward the caudal part. During walking, -0.3~0.8g in the vertical direction, -0.2~2g at the head and -0.3~0.4g at the lower back have been observed
with a stereophotogrammetry in Cappozzo’s studies. During running or trampoline
jumping, peak amplitude up to 12g
at the ankle measured by skin-mounted accelerometers has been reported
[Bhattacharya et al., 1980].
acceleration registration, the frequency outputs from motion sensors are
limited for desirable sensitivity and signal integrity. High frequency
bandwidth yields a high sensitivity in response to body movements.
Consequently, an appropriate frequency bandwidth of sensor outputs should be
carefully selected to reduce interfering noises while preserving original acceleration
patterns. Bouten et al.  used a
low-pass filter (20Hz-9dB/octave), and a high-pass filter (0.11Hz-0.6dB/octave)
in order to eliminate DC response of piezo-resistive accelerometers. In
general, the cut-off frequencies of the low-pass filters are below 50Hz.
Bouten et al.  also suggested that
body-fixed accelerometers must be able to register accelerations within the
amplitude range of -12 to 12g and
with frequency up to 20Hz in order to assess daily physical. High-g
accelerometers were suggested since they have taken the activities such as trampoline
jumping and running into considerations. However, for ambulatory monitoring at
home environment, it is not necessary to use high-g accelerometers because
these types of exercises are rare and the intensity is also quite low in such
situations. Bijan Najafi et al. used
two low-g accelerometers (ADXL202, ±2g) in the kinematic sensor for ambulatory monitoring.
placement on the human body is an important issue. Two major concerns are where
and how to fix the sensors. The sensor should be firmly fixed to the human body
to avoid the sensor from loosening, sliding and jolting which will cause
artifacts in the sensor outputs. Therefore, a sensor attached to clothing is
not feasible. The ideal mehtod is to fix the sensor directly on the skin of the
human body because the dislocation of the sensor would be minimal, and the
vibration or resonance induced by body movements would not significantly affect
the sensor outputs. However, this attachment causes discomfort and inconvenience
in use. A preferable way proposed in several studies is a wearable belt which
carries sensors. This attachment is convenient to the users and will not
significantly influence the physical activity in their activities of daily
from all skeletal parts of a body such as the head, trunk and extremities
differ from each other when most body movements occur. Meanwhile, different
accelerations can be distinguished from several local measuring points within the
same part of a body. For example, acceleration patterns from the sternum, waist
or back are not always the same. To acquire detailed information of body
movement and energy expenditure, it is necessary to place numerous motion
sensors on each part of a body. However, such a method can not be applied in
ambulatory uses due to the complex inter-instrumentation. In addition, not all
the acceleration data are related to the analysis on physical activity or
energy expenditure. Therefore, recent studies have been focusing on how to
measure the data only with a few, or even a single sensor for specific purposes.
Most studies have concluded that the sensor should be attached to the trunk
since this part of the body represents most of the body mass. Cavagna et al.  placed the accelerometer
at the lumbosacral level on the back as close as possible to the center of
gravity of the body, when studying external work in walking and running. As
shown in Figure 2.15, Gerwin, Meijer, Carlijn and Bouten et al, used a belt with an accelerometer worn on the waist of the
subject, located at the lower back (second lumbar vertebra) [Meijer et al, 1991; Bouten et al, 1997]. Najafi et al.
 used a piezoelectric gyroscope attached with a belt in front of the
sternum to determine postural transitions, as well as to evaluate fall risk in
the elderly. In their research for the ambulatory monitoring system, one
kinematic sensor package was directly attached to the chest under the assumption
that it will accurately detect postural transitions between standing, sitting,
and lying, as well as locomotion activity when standing (Figure 2.16) [K.Aminian
et al, 2003].
Figure 2.15 Sensor attachment with a belt on the
Figure 2.16 Sensor attached to the chest
2.4 Preliminary experiments on posture transitions
experiments were performed on several normal adult subjects. The cut-off
frequency of KXM52-1050 is 50Hz, and the following data acquisition was selected
at the rate of 100Hz to preserve the signal integrity of A/D conversion. The
accelerometer was attached firmly to the leather belt of the pants so that the
attachment would not loosen or dislocate during the experiments.
2.4.1 Sit-to-stand and stand-to-sit posture transitions
illustrates the process of sit-to-stand posture transition of a typical tester.
The reverse order in Figure 2.17 can also represent a stand-to-sit transition. As
shown in Figure 2.18, when sit-to-stand or stand-to-sit posture transitions occur,
there are few variations of accelerations along medio-lateral direction. Acceleration
along this direction does not provide significant information for posture
transitions, and therefore is not considered in this posture.
shows the tilt angle variation of the trunk with respect to vertical when
sit-to-stand transition occurs. Initially, trunk tilt of about 25 to 30 degrees
anteriorly is observed before standing up due to the autonomic balance for
center of gravity of the body. In this phase the time duration is about 0.75 to
0.8 seconds. As the subject stands up from the seat, the trunk reverses gently
to the original vertical posture within time duration of about 1.0 to 1.2
Figure 2.17 Illustration of trunk tilt angle
variation during sit-to-stand transition
Figure 2.18 Response in medio-lateral direction
when sit-to-stand and stand-to-sit posture transitions.
Figure 2.19 Trunk tilt angle variation during
To determine the
acceleration pattern of posture transition, two channels of the KXM52-1050 are
used to measure the accelerations along the vertical and antero-posterior
directions (Figure 20). In the vertical component acceleration of about 0.14g upwards is detected when the
subject stands up from the seat, and followed by a continuous deceleration up
to -0.2g downward. The
motion ends with a more gentle acceleration from -0.2g to 0g.
antero-posterior component results from the trunk tilt forward and the
following motion which generates a part of horizontal acceleration ahead.
Acceleration up to about 0.4g
is detected in this process. Note that the antero-posterior component begins
and ends in about the same time as that along the vertical direction. Besides,
signal outputs before and after posture transitions may not always be the same.
This is because the initial and final orientation of the sensor may not be
consistent due to the non-habitual posture of the subject or a slight
dislocation of the sensor attachment exists.
Figure 2.20 Acceleration patterns of sit-to-stand posture
characteristics of the acceleration pattern can be observed in stand-to-sit
transitions. Figure 2.21 shows the trunk tilt. In the vertical component in
Figure 2.22, an increasing acceleration downward begins with body motion when
sitting down. In this phase 0.1g
to 0.2g downward are measured.
While the buttocks approach the seat, deceleration begins to slow down the
motion. At the instant when the subject sits on the seat, a high, upward
acceleration bouncing 0.2g up
to 0.8g is detected due to
the reacting force exerted by the seat. Note that the vertical bouncing
acceleration upward may be different according to various materials of the
cushion on the seat. A stiff cushion may results in higher values in contrast
to lower values acquired with a soft cushion. Figure 2.23 reveals a high
bouncing acceleration over 1g
(up to 1.22g) when the
subject sits on flat, stiff chair during stand-to-sit transition.
Figure 2.21 Trunk tilt angle of stand-to-sit
Figure 2.22 Acceleration patterns of a normal stand-to-sit
Figure 2.23 Acceleration patterns of a fast stand-to-sit
2.4.2 Walking and lie-to-sit transition
shows the acceleration patterns when walking. In this figure walking begins at
T=0.5s. For the acceleration component in the antero-posterior direction, represented
by the narrow red curve, each stride results in an increasing acceleration
forward during the time interval of T=0.5s to T=1.1s. The maximum occurs at the
end of this time interval. After that instant, the acceleration decreases as the
foot is lowering down. As the foot steps on the ground whose peak value of
vertical component can be detected, the time interval is approximately 0.1s to
0.15s. The maximal deceleration (negative peak) occurs after each step in a
short time interval of about 0.1s.
For the vertical
component represented by the bold blue curve, each step results in
corresponding positive peak values about 0.3g
to 0.45g. However, negative
peak values are not obvious. Pairs of the two positive peak values whose
vertical component is always behind the antero-posterior component in a narrow
time intervals can be observed as indicated by the red arrows in Figure 2.24. When
that foot steps on the ground in turn, the cycle described above re-appears. Acceleration
patterns of faster walking pace registered in Figure 2.25 also shows the
identical and definite characteristics. The only significant distinction
reveals that faster walking pace results in higher positive peaks in vertical
component. Note that in the negative regions of Figure 2.24 and Figure 2.25 the
tendency of two pairs of negative peak values is not apparent compared with
that in positive region as the two arrows indicate. Moreover, positive peaks
values are higher than negative ones due to the effect of reactive force
exerted by the ground.
Figure 2.24 Acceleration patterns of walking
Figure 2.25 Acceleration patterns of walking
illustrates the shift of trunk orientation which coincides with the sensor
orientation. Figure 2.27 and Figure 2.28 show the gravity patterns of sit-to-lie
or lie-to-sit posture transitions, these movements can be regarded as rotations
of trunk with respect to the
lumbar vertebra. Therefore, in sit-to-lie posture transition the vertical
component of gravity decreases form 1g
to 0g. Antero-posterior
component (narrow line) of gravity varies from 0g to -1g.
Patterns of lie-to-sit posture transition can be observed in reverse order.
Figure 2.26 Shift of sensor orientation when
sit-to-lie posture transition
Figure 2.27 Gravity patterns of sit-to-lie
Figure 2.28 Gravity patterns of lie-to-sit
This section describes the preliminary tests on the
acquisition of acceleration patterns of posture transition and walking. These
postures and posture transitions can be clearly identified with several significant
properties distinguished from one another. These results are of great help for
the development of body movement algorithms which aimed to determine these
postures or posture transitions.
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