Algorithm Design for Real-time Physical Activity Identification with Accelerometry Measurement

Characteristics of physical activity are indicative of one's mobility level, latent chronic diseases and aging process. Current research has been oriented to provide quantitative assessment of physical activity with ambulatory monitoring approaches. This study presented the design of algorithm integrated with a portable microprocessor-based accelerometry measuring device to implement real-time physical activity identification. This algorithm processes real-time tri-axial acceleration signals produced by human movement to identify targeted still postures, postural transitions or walking. Fall detection is also featured in this algorithm to meet the increasing needs for elderly care. High identification accuracy was obtained during the preliminary test phase and the observed limitations regarding real-time processing was also discussed. The result reveals that this developed algorithm is technically viable for real-time identification in ambulatory monitoring to provide sufficient information in evaluating a person's activity of daily living (ADL) and the status of physical mobility. Possible system integration and applications in the future were also discussed.