  Smart earbuds are recognized as a new wearable platform for personal-scale
human motion sensing. However, due to the interference from head movement or
background noise, commonly-used modalities (e.g. accelerometer and microphone)
fail to reliably detect both intense and light motions. To obviate this, we
propose OESense, an acoustic-based in-ear system for general human motion
sensing. 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 in
an occluded ear canal) and inward-facing microphone, which naturally boosts the
sensing signal and suppresses external interference. We prototype OESense as an
earbud and evaluate its performance on three representative applications, i.e.,
step counting, activity recognition, and hand-to-face gesture interaction. With
data collected from 31 subjects, we show that OESense achieves 99.3% step
counting recall, 98.3% recognition recall for 5 activities, and 97.0% recall
for five tapping gestures on human face, respectively. We also demonstrate that
OESense is compatible with earbuds' fundamental functionalities (e.g. music
playback and phone calls). In terms of energy, OESense consumes 746 mW during
data recording and recognition and it has a response latency of 40.85 ms for
gesture recognition. Our analysis indicates such overhead is acceptable and
OESense is potential to be integrated into future earbuds.
