Continuous Body Monitoring - Ambient Intelligence for Scientific Discovery - page 216

In most cases researchers were willing to share their data and analysis, which
has helped BodyMedia to continually improve both the SenseWear armband and
the research software, to strengthen user and activity data pools, and to improve
BodyMedia's ability to train, choose, and develop more sophisticated algorithms.
Often, research specialists provide the first instance of focused group data
(e.g. obese, diabetic, cardiac and pulmonary subjects) affording unique opportu-
nities to realize previously undiscovered physiological information that can lead
to better understanding of typical and distinctive qualities in the data charac-
teristics of a group or activity set. We expect this cyclical exchange to continue,
improving the accuracy and scope of BodyMedia tools in both research and
diagnostic settings.
The SenseWear Armband is particularly interesting as a data collection de-
vice for medical applications because it allows data collection in free-living envi-
ronments without using cumbersome or invasive laboratory equipment (see for
example Fig. 6). Similarly, SenseWear is a useful tool for studying psychosocial
situations because of its noninvasive, constant, multisensor data logging capa-
bilities. This can enhance qualitative field notes with physiological information
overlays and, in some situations, reduce or eliminate note taking by hand. Fur-
thermore, with data streaming technologies in place, SenseWear provides the
potential for remote information collection, analysis, and synthesis.

6.1 Energy Expenditure and Exercise Physiology

Researchers have used BodyMedia Armbands in a variety of clinical studies often
in relation to energy expenditure and fitness studies. University of Pittsburgh
has collaborated with BodyMedia on a number of research initiatives including
energy expenditure, sleep, and eating disorders. Dr. Kupfer, Chief of Behavioral
Medicine at UPMC sees the armbands and associated software as an opportunity
to “get information. . . we could previously get only in a lab” and sees great
potential for using armbands for affordable public health studies.
Jakicic et al [9] and Fruin et al [6] tested the SenseWear PRO Armband
against indirect calorimetry measurements for energy expenditure during rest
and during use of multiple fitness machines such as treadmills and stationary bi-
cycles. The Jakacic study [9] found “When exercise specific algorithms are used,
the SenseWear Pro Armband provides an accurate estimate of energy expendi-
ture when compared to indirect calorimetry during exercise periods examined
in this study.” The Fruin study [6] found “The SWA provided valid and reliable
estimates of EE at rest and generated similar mean estimates of EE as IC on
the ergometer; however, individual error was large. The SWA overestimated the
EE of flat walking and underestimated inclined walking EE.”
King et al [11] studied multiple activity monitors including CSA, TriTrac-
R3D, RT3, BioTrainer-Pro accelerometers, and the SenseWear Armband. Their
study concluded that “The CSA was the best estimate of total EE at walking and
jogging speeds, the TriTrac-R3D was the best estimate of total EE at running
speeds, and the SenseWear Armband was the best estimate of total EE at most
speeds.”