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Smart earbuds are recognized as a new wearable platform for personal-scalehuman motion sensing. However, due to the interference from head movement orbackground noise, commonly-used modalities (e.g. accelerometer and microphone)fail to reliably detect both intense and light motions. To obviate this, wepropose OESense, an acoustic-based in-ear system for general human motionsensing. The core idea behind OESense is the joint use of the occlusion effect(i.e., the enhancement of low-frequency components of bone-conducted sounds inan occluded ear canal) and inward-facing microphone, which naturally boosts thesensing signal and suppresses external interference. We prototype OESense as anearbud and evaluate its performance on three representative applications, i.e.,step counting, activity recognition, and hand-to-face gesture interaction. Withdata collected from 31 subjects, we show that OESense achieves 99.3% stepcounting recall, 98.3% recognition recall for 5 activities, and 97.0% recallfor five tapping gestures on human face, respectively. We also demonstrate thatOESense is compatible with earbuds' fundamental functionalities (e.g. musicplayback and phone calls). In terms of energy, OESense consumes 746 mW duringdata recording and recognition and it has a response latency of 40.85 ms forgesture recognition. Our analysis indicates such overhead is acceptable andOESense is potential to be integrated into future earbuds.

OESense: Employing Occlusion Effect for In-ear Human Sensing