Accelerometers are becoming one of the most popular tools for physical activity assessment across different populations. Although most evidence suggests that accelerometry is a reliable and valid tool, there are limitations to using traditional accelerometry for physical activity assessment (e.g., identifying low-activity tasks and inability to detect different postures). At the same time, multi-sensor technology within the context of wireless networks is emerging as a promising tool for monitoring of various health-related characteristics. The purposes of this interdisciplinary study are: a) to develop a wearable wireless sensor network for distributed physical activity context detection, b) to validate the network for detecting various physical activities, and c) to assess physical activity energy expenditure using sensor-identified activity and postures. Limitations of traditional accelerometry are addressed in this proposed system by a) using additional sensing modalities that can capture low-activity tasks, and b) networking multiple sensors so that data can be collated for identifying a broader range of activities and postures. A final objective of the proposed project is to test how well the output from the device predicts energy expenditure when compared to the gold standard of indirect calorimetry. Results from this investigation will lead to future R01 proposals in which the networked system will be extended for advanced features including on-body statistical processing and real-time feedback to participants.
The proposed study will address the fact that commercially available accelerometers do not provide activity type or contextual information that is necessary to better capture physical activity behaviors. Enhanced measurement of physical activity and postures using the proposed wireless sensing and networking technology will in turn improve the efforts of public health researchers to effectively conduct surveillance activities and determine the effects of intervention research.
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