Using an in-earwearable to annotate activity data across multiple inertial sensors

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Abstract

Wearable activity recognition research needs benchmark data, which rely heavily on synchronizing and annotating the inertial sensor data, in order to validate the activity classifiers. Such validation studies become challenging when recording outside the lab, over longer stretches of time. This paper presents a method that uses an inconspicuous, earworn device that allows the wearer to annotate his or her activities as the recording takes place. Since the ear-worn device has integrated inertial sensors, we use cross-correlation over all wearable inertial signals to propagate the annotations over all sensor streams. In a feasibility study with 7 participants performing 6 different physical activities, we show that our algorithm is able to synchronize signals between sensors worn on the body using cross-correlation, typically within a second. A comfort rating scale study has shown that attachment is critical. Button presses can thus define markers in synchronized activity data, resulting in a fast, comfortable, and reliable annotation method.

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Hoelzemann, A., Odoemelem, H., & Van Laerhoven, K. (2019). Using an in-earwearable to annotate activity data across multiple inertial sensors. In Proceedings of the 1st International Workshop on Earable Computing, EarComp 2019 (pp. 14–19). Association for Computing Machinery, Inc. https://doi.org/10.1145/3345615.3361136

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