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.

中文翻译：

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OESense：为入耳式人体感应采用遮挡效果

智能耳塞被认为是用于个人规模人体运动感应的新型可穿戴平台。然而，由于头部运动或背景噪声的干扰，常用的模式（例如加速度计和麦克风）无法可靠地检测强烈和轻微的运动。为了避免这种情况，我们提出了 OESense，这是一种基于声学的入耳式系统，用于一般人体运动感应。OESense背后的核心思想是结合使用闭塞效应（即增强闭塞耳道中骨传导声音的低频成分）和内向麦克风，自然提升传感信号并抑制外部干扰. 我们将 OESense 原型设计为耳塞，并评估其在三个有代表性的应用中的性能，即计步、活动识别和面对面手势交互。通过从 31 名受试者收集的数据，我们表明 OESense 分别实现了 99.3% 的计步召回率、98.3% 的 5 项活动的识别召回率和 97.0% 的人脸点击手势的召回率。我们还证明 OESense 与耳塞的基本功能（例如音乐播放和电话）兼容。能耗方面，OESense在数据记录和识别过程中的功耗为746 mW，手势识别的响应延迟为40.85 ms。我们的分析表明，这种开销是可以接受的，并且 OESense 有可能被集成到未来的耳塞中。我们还证明 OESense 与耳塞的基本功能（例如音乐播放和电话）兼容。能耗方面，OESense在数据记录和识别过程中的功耗为746 mW，手势识别的响应延迟为40.85 ms。我们的分析表明，这种开销是可以接受的，并且 OESense 有可能被集成到未来的耳塞中。我们还证明 OESense 与耳塞的基本功能（例如音乐播放和电话）兼容。能耗方面，OESense在数据记录和识别过程中的功耗为746 mW，手势识别的响应延迟为40.85 ms。我们的分析表明，这种开销是可以接受的，并且 OESense 有可能被集成到未来的耳塞中。