Abstract
There has been a very rapid growth in wearable computers over the past few years. Assisted living applications leveraging wearable computers will enable a healthier lifestyle and independence in a variety of target populations, including those suffering from neurological disorders, patients in need of rehabilitation after surgical procedures or injury, the elderly, individuals who might be at high risk of emotional stress, and those who are looking for a healthier lifestyle. Application paradigms for assisted living include activities of daily living (ADLs) monitoring, indoor localization, emergency and fall detection, and rehabilitation. All of these applications require monitoring of movements and physical activities for individuals. Wearable inertial measurement unit (IMU)-based sensors can offer low-cost and ubiquitous monitoring solutions for physical activities. Signal processing techniques with a focus on enhancing accuracy, lowering computational complexity, reducing power consumption, and improving the unobtrusiveness of the wearable computers are of interest in this article, which constitutes the first attempt made at reviewing the literature of wearable IMU-based signal processing techniques for assisted living applications. Various signal processing techniques with the aforementioned performance metrics in mind are reviewed here.
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