Wearable NIR Sensors for Hand Gesture Detection (2023)

Undergraduates: Gavin Lyda, Christopher Nguyen, Salil Pai

Faculty Advisor: Wubin Bai
Department: Applied Physics

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Photoplethysmography (PPG) is a non-invasive technology where a source emits light onto a tissue and a photodiode (PD) measures changes of blood volume from the reflected light. Using near-infrared (NIR) light emitting diodes (LED), light shined onto the skin can penetrate through the subcutaneous layer of fat to deeper parts of the body, such as to the muscles[1] and blood vessels. When the targeted muscles change in shape, motion artifacts (MA) caused by those movements are created and have large amplitudes in the PPG signal[2]. These artifacts arise mainly as a result of attenuation, which is unique for different muscular density profiles. As such, MA caused by bodily movements can be traced back via a machine learned algorithm to accurately identify which targeted muscles are being engaged. Here, we explore a wearable device that utilizes NIR LEDs and PDs placed over the digitorum muscles of the hand to monitor real-time PPG motion artifacts for gesture detection.

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