Developing an Integrated Measurement System to Assess Physical Activity
Patty Freedson, PhD
Professor, Graduate Program Director and Chair
Department of Kinesiology
University of Massachusetts, Amherst
psf@kin.umass.edu
What's the problem?
The measurement of physical activity over varying recent time periods or in the past
has, by necessity, relied on self-report instruments. A variety of such instruments exist,
but they can be cognitively difficult for respondents and prone to varying degrees of
measurement error depending on the time period considered, the instrument's ease of use,
and the ethnic and demographic characteristics of the respondents. To overcome some of
these limitations, investigators are working to develop improved measures using wearable
devices to assess physical activity.
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How will this research address the problem?
The goal of this new study is to combine an accelerometer, which is commonly used in
physical activity assessment research to measure body motion, with two additional sensors
that capture characteristics of breathing and the environmental context (i.e., indoor or
outdoor activity). Including these additional sensors ensures that the measurement system
will increase the precision and validity of estimates of the physical activity intensity
and associated energy expenditure. To validate the modeled estimates of physical activity
intensity and energy expenditure that result from using all three sensors simultaneously,
Dr. Freedson has assembled a multidisciplinary team representing the fields of exercise
physiology, electrical engineering, signal processing, statistics, and mechanotronics
(this field involves the integration of mechanical, electrical, and software engineering
to yield simpler, more versatile, and economical systems). The varied expertise of the
team will be used to design and fabricate the sensors; validate and calibrate the sensors
during light, moderate, and vigorous activity; and develop appropriate statistical models
to evaluate the performance of the various sensors. The results of this research will
inform future efforts to develop and test activity pattern recognition systems to identify
physical activity intensity.
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Significance of the study & results
This study breaks new ground because it is creating and validating the next generation
of physical activity assessment tools. A rigorous process of design optimization will be
employed so that the final integrated measurement system (IMS) will be appropriate for use
in large-scale epidemiological studies at a reasonable cost and with minimal subject
burden.
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Recent publications of interest
Liu S, He Q, Gao RX, Freedson P. Empirical mode decomposition applied to tissue
artifact removal from respiratory signal. In: Proceedings of the 30th Annual IEEE
Engineering in Medicine and Biology Society (IEEE EMBS) Conference. Vancouver, Canada;
2008 Aug 21-24, p. 3624-7.
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