Author: Che-Chang Yang (2006-09-01); recommended:
Yeh-Liang Hsu (2006-09-01).
Note: This article is Chapter 7 of Che-Chang Yang’s Master thesis “Development
of a Portable System for Physical Activity Assessment in a Home Environment.”
Chapter 7. Discussion and
In this study, a
system for human physical activity assessment using only one portable sensing
device was developed for real-time ambulatory monitoring in a home environment.
This system is able to distinguish rests from activities and further identify
several target posture transitions and movements. Although the nature of actual
human postures and activities of daily living are more complex than what is
considered and assumed in the algorithm, this algorithm still exhibits
acceptable performance in determining those target postures and activities.
Despite some limitations in the configuration for real-time data processing,
this system is technically viable to perform long-term ambulatory monitoring in
a home environment and to provide sufficient information in evaluating a person’s
activities of daily living (ADL) and his status of physical mobility.
activity assessment system which utilizes only one wearable sensing device has
been developed and demonstrated in ambulatory tests. This system also achieves good
performance in still posture and dynamic activity identification. However, some
inherent limitations are worth discussing here.
capacitance tri-axial accelerometer was used in this study to measure the acceleration
and trunk tilt of the human body. In fact, the most precise tilt sensing can be
maintained when the accelerometer is at static, or under constant acceleration.
However, tilt sensing using accelerometers still has limited performance in
accuracy. Degradation of tilt sensing accuracy in changing acceleration magnitude
is an inevitable problem. For example, Equation 7.1 is a formula for this
accelerometer to calculate tilt angle relative to the Y axis when rotating about the X
axis. This equation is a function of the three acceleration components (aX, aY and aZ). Consider a case, for example, where
the accelerometer is moving upward (positive Z direction) without any rotation (tilt). Obviously, there must be
no change except the Z axis
acceleration component aZ. However, an unreasonable
tilt angle will be obtained for such a case according to this equation.
explains a possible paradox probably encountered in empirical uses. In Elble’s
report on gravitational artifact in accelerometric measurement , it was
stated that the interference of gravitational artifact cannot be solved using
either bi-axial or tri-axial accelerometers. Therefore, the acceleration data
acquired in this study cannot be used to precisely interpret the complex nature
of human motions. In spite of this constraint, tilt sensing and acceleration
measurement using one tri-axial accelerometer is still valid for physical
activity because the resulting outputs still preserve apparent characteristics
for either trunk tilt and acceleration patterns.
The wearable DAU
The wearable DAU
has been designed to measure human body movement. It is designed to be clipped
onto a waist belt for minimizing discomfort and inconvenience in use. However,
carrying the DAU might limit posture and movement when lying down and therefore
further influences the subject’s comfort.
As for wireless
data transmission, power capacity has a significant influence on the effective
distance and stability of data delivery. In low power status, the transmitter
fails to function properly whereas the other parts, such as PIC microcontroller
and accelerometer still function normally. To extend the time for use, a battery
cartridge with (3×AA alkaline batteries) can be used instead of the AAA batteries.
The antenna configuration has a great influence on the performance of wireless
data delivery, as well. However, the antenna design has not been further
evaluated. In the future, the onboard antenna and optimization must be taken
in computation capability and memory capacity of the microcontroller used in
this study, coupled with the fact that human events must be identified simultaneously
to keep up with the next data acquisition process, limit the identification
performance. Most other off-line systems use powerful PC-based computation
software such as MATLAB to analyze the recorded data. Therefore, identification
accuracy of those systems is usually higher than that of the real-time systems
durations of posture transitions or movement are not the same each time, even for
the same person. People usually perform mixed and combined movements in their normal
activities of living. Due to the complex nature of human movement and
limitations in instrumentation, identification accuracy for such a real-time
system can be limited when applied in real ambulatory and home uses, despite
that fact that it achieves good performance for laboratory-set tests.
7.2 Future work
system for physical activity identification and assessment has been technically
proven to be feasible. The results from the ambulatory tests also show that
this system can provide significant information on the subject’s activities of
daily living. In the future, there are still some improvements and potential
developments to be considered:
Application fields of the
system needs to be identified
developed in this study may find applications in various fields, such as
elderly care at home or in nursing homes, physical rehabilitation, etc. The
application fields and the usefulness of this system need to be identified and
justified, and the system may need to be adjusted for different application
Further improvement in instrumentation
system uses conventional 433.92MHz RF transmission module. However, the ZigBee
wireless communication module in IEEE 802.15.4 application is a better
alternative for its advancement in data “hopping” capability and low power
consumption. It is also possible to miniaturize the device, both the wearable
DAU and the DDS, towards a more commercialized level product design. In
addition, human factors also need to be considered, for example, the device
attachment design, etc.
System robustness, reliability
and performance ambulatory evaluation
validate the robustness and reliability of the system and the performance of
the algorithm, this study still requires more information from large-scale
ambulatory evaluation in home environments. For the potential target user
group, e.g. older adults, their responses to the use of the system as well as
the identification accuracy needs to be further investigated.
To further enhance
accuracy, a technique such as rule-based event classification can be employed
[Mathie et al., 2004]. In addition, it was observed that one set of parameters
in the algorithm were not applicable to all the users with different mobility
capabilities. Therefore, multi-mode parameter functions in the algorithm should
be implemented to fit the users with various mobility characteristics.
Toward a ubiquitous computing
activity assessment is one branch of the human ADL-related research field. We
should further investigate the possibility to integrate the information of environmental
sensors (e.g., temperature, humidity, luminance, etc.), space-embedded activity
sensors and vital sign devices (sphygmomanometer,
glucose-meter, weight scale, etc.) together to
establish the platform of a ubiquitous computing system.
Rodger, 2005. “Gravitational artifact in accelerometric measurements of
tremour,” Clinical Neurophysiology,
vol. 116, pp. 1638-1643.
M., Narayanan, Michael R., Mathie, Merryn., Lovell, Nigel H., Celler, Branko
G., 2006. “Implementation of a Real-Time Human Movement Classifier Using a
Triaxial Accelerometer for Ambulatory Monitoring,” IEEE Trans. Info. Tech
Biomed., vol. 10, No. 1, pp. 156-167.
Mathie, M. J.,
Celler, B. G., Coster, A. C. F., Lovell, N. H., 2004. “Classification of basic
daily movements using a triaxial accelerometer,” Medical & Biological Engineering & Computing, vol. 42, pp.