Novel Application of Radar Technology in Human Movement Science and Physical Activities

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Loo, Marisa
Troy, Willis
Wang, Henry
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motion capture
exercise science
continuous wave
daily activities
physical activity
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The gold standard for human motion analysis in the field of biomechanics is an optical motion capture system that records human movement and kinematic data. Kinematics describes the motion of a subject with spatiotemporal parameters, including but not limited to position, duration, velocity, and acceleration. However, in recent years, movement scientists have explored other technologies that are typically cheaper and mobile. A prominent standalone system that is currently being investigated is RADAR. Predominately, research in this area has focused on employing radar to track and classify human movement for the purposes of search and rescue, surveillance, military operations, and fall detection. Most research has focused on gait classification and detection, with little research considering classification of other human movements. Given the increased need for movement analysis systems that can be utilized outside the lab, the purpose of this study is to determine whether the spatiotemporal kinematic variables provided by the radar are valid compared to the optical motion capture system during daily activities in healthy male and female adults. This study will examine a continuous wave (CW) Doppler radar system that was developed to analyze the signal of human gait. In order to validate and help determine the relationship of biomechanical motions to the resultant features in the radar spectrogram, motion data will be collected simultaneously with the radar system and the optical motion capture system. However, instead of focusing on general human gait, daily activity motions will be analyzed in this study, including stair walking, sit to stand movement, squats, lunges, and cycling. Most of these motions have not been analyzed using radar, but kinematic variables including cycle duration, phase duration, and cycle frequency will be considered. It is hypothesized that the daily movements will produce distinct and unique radar spectrograms. It is expected that the kinematic from the radar data will be validated against the optical motion capture data. The results of this study could better the understanding of how radar data can be used in movement science fields and can contribute to improved patient rehabilitation, injury prevention, and analysis of daily and sports-related movements outside of the lab environment.