Author: Che-Chang Yang(2006-09-01);
recommendation: Yeh-Liang Hsu (2006-09-01).
Note: This article is Chapter 1 of Che-Chang Yang’s Master thesis “Development
of a Portable System for Physical Activity Assessment in a Home Environment.”
Chapter 1. Introduction
Motivation of the research
1.1.1 Assessment of physical
activity can be regarded as any movement or posture that is produced by
skeletal muscles and results in energy expenditure [Capspersen et al.,
1985]. Various health conditions such as heart disease, senile dementia, degeneration
in mobility will directly affect one’s physical activity level. The quantitative
assessment of daily physical activity at home is a determinant in the evaluation
of health and the quality of life of subjects with limited mobility and chronic
diseases, such as elderly persons [Foerster et
of physical activity is difficult due to the subtle and complex nature of body
movement which requires precise and reliable measuring techniques. Standard
human motion capturing techniques based on optical, magnetic and ultrasonic
systems allow a complete kinematic analysis but require a dedicated laboratory
[Aminian et al., 2004]. In a magnetic
motion capturing system, the body positions and joint rotations can be measured
by several sensors placed on the body of the subjects in a magnetic field
[Bodenheimer et al., 1997]. Dickstein
et al.  presented the
application of a kinematic measurement system based on ultrasonic technique to
assess stance balance in a clinic. As for the optical sensing technique,
subjects are asked to place several passive reflective markers or active
markers (e.g. LED, infrared) on different body parts while cameras are installed
around the interior of the room to capture their motion.
From a technological
point of view, these techniques mentioned above can precisely capture human
motions and have been used in the applications of computer animation and
virtual reality. However, for the assessment of daily physical activity in a
home environment the cost of such techniques is unacceptable for common use.
Moreover, the subjects must be restrained inside a laboratory-like space, which
is entirely different from a free-living home environment. Therefore,
acquisition of body movement using portable measuring devices or body-fixed
motion sensors is an appropriate alternative for physical activity assessment
in ambulation and home environments.
In the past,
mechanical motion sensors have been used for various physical activity
assessments. Saris  used pedometers and actometers to study daily
physical activity. Energy expenditure related to various physical activities has
also been estimated using this technology [Verschuur et al., 1980]. Meanwhile, the use of accelerometers to measure body
movement began as early as the 1970s. Morris  developed an
accelerometry-based technique to measure human body movement. Meijier et al.,  proposed a method to
assess physical activity with motion sensors and accelerometers. They also
developed a small data acquisition unit with a solid state memory in place of a
large tape recorder which discouraged subjects from wearing it. Veltink et al.  investigated the
feasibility of distinguishing several static and dynamic activities (standing,
sitting, lying, walking, ascending stairs and descending stairs) in a domestic
environment using a small set of two or three uniaxial accelerometers. Bouten et al.  also presented a tri-axial
accelerometer which consists of three separate orthogonal uniaxial
accelerometers to measure body movement.
Najafi et al.  developed a portable data
processing unit for the off-line acquisition, processing, and storage of the
acceleration data. An ambulatory system was presented for daily physical
activity monitoring of the elderly using a kinematic sensor which consists of a
miniature gyroscope and two dual-axial accelerometers. The angular velocity of the
trunk, accelerations from the trunk and frontal-trunk were all measured for
body motion analysis. Wavelet transformation, in conjunction with a simple
kinematics model, was used to detect various postural transitions and walking
periods during daily physical activity. In addition, fall risk evaluation was
proposed. Aminian et al.  also
developed an off-line ambulatory gait analysis system. In this system, as shown
in Figure 1.1, four miniature gyroscopes are attached respectively to each
shank and each thigh for angular rotation measurement. Sensing data are stored
in a portable data logger (Physilog system). With this configuration, the lower
limb movement during walking can be measured.
Figure 1.1 Measurement configuration of a gait
analysis system [Aminian, 2002]
1.1.2 Tele-homecare Systems
According to the
UN’s definition, a society in which more than 7 percent of the total population
is aged 65 or over is referred to as an aging society. Taiwan has become an aging society
since 1993. Currently in 2005 the population aged 65 or older is over 2 million
(9.74%). The needs of health care and management for the elderly has become an
important issue. The increasing needs for elderly care cannot be solved by merely
increasing the number of care-givers.
The home has
become the centerpiece of health delivery systems today. Tele-homecare can be
defined as the use of information and communication technologies to enable
effective delivery and management of health services at a patient’s residence [Office
of Health and Information
1998]. Tele-homecare differs from tele-medicine in the sense that people who
transmit and receive medical information are not necessarily medical doctors
but the patients themselves and their families, nurses, care-givers,
home-helpers and medical technical experts [Tsuji, 2002]. Koch  gave an
overview about the current state and future trends in research on home
telehealth in an international perspective.
Tele-homecare Monitoring System (PTMS) has currently been under development by the
Gerontechnology Research Center,
at Yuan Ze University. Instead of using a centralized database structure that
gathers data from many households, in PTMS a household is the fundamental unit
for data transmission, storage, and analysis. Equipped with different sensors,
PTMS can be used for long-term personal health data management of the elderly
in a home environment. PTMS also provides care-givers with convenient access to
the health data of the elderly, and real time event-driven messages in urgent
situations. Several PTMS applications are demonstrated, including environment
and daily behavior monitoring, an RFID-based entrance guard system, sleep
quality monitoring, vital sign monitoring, and a tele-presence robot.
1.1.3 Purpose of the Research
The purpose of
this research is to develop a wearable system for physical activity assessment
based upon the PTMS infrastructure. Figure 1.2 shows the structure of the
system. A tri-axial accelerometer is used for motion detection of body
movement. A dedicated body movement algorithm embedded in the microcontrollers
is developed to actively recognize human still postures (sitting, standing and lying), posture transitions (sit-stand
type or lie-sit type) and locomotion (walking) in a home environment. The tri-axial
accelerometer and the microcontroller are integrated with a wireless
communication module to form a wearable data acquisition unit (DAU), which
transmits the signals of body movements to the distributed data server (DDS),
which is the core of the PTMS.
wirelessly receives the identified signals of body movements from the wearable
data acquisition unit in real time. These events are classified and then stored
in the Multi-Media Card (MMC). Users can access the DDS using an Internet
browser or a dedicated VB program to retrieve historical data and perform data
management. Quantitative assessments of one’s health condition such as a vitality
index, regular routines, daily behaviors and senile dementia will be reported
by analyzing the long-term historical data. With the event-driven capabilities
of the DDS, caregivers are informed automatically of any possible emergencies
by cell phone text message or E-mail.
Figure 1.2 System structure
Structure of the Thesis
Chapter 2 of the
thesis reviews the accelerometry for human body movements. Related literature
referring to motion sensors, sensor attachment and measurement techniques are
discussed. Preliminary description of acceleration patterns including human
postures, posture transitions and locomotion is demonstrated.
describes the design of the newly developed 3rd generation DDS. In
Chapter 4, the design of a portable data acquisition unit composed of a
tri-axial accelerometer, microcontrollers and an RF wireless transmission
module will be presented. An algorithm for body movement recognition and a method
for quantitative assessment are discussed in Chapter 5. System integration and ambulatory
tests in a residential space will also be reported in this chapter 6.
concludes this study. Possible extensions of this research, for example, Physical
activity assessment with ubiquitous computation network in existing PTMS
infrastructure is discussed, is also discussed.
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