This work introduces LIBS, a light-weight and inexpensive wearable sensing system, that can capture electrical activities of human brain, eyes, and facial muscles with two pairs of custom-built flexible electrodes each of which is embedded on an off-the-shelf foam earplug. A supervised nonnegative matrix factorization algorithm to adaptively analyze and extract these bioelectrical signals from a single mixed in-ear channel collected by the sensor is also proposed. While LIBS can enable a wide class of low-cost selfcare, human computer interaction, and health monitoring applications, the work demonstrates its medical potential by developing an autonomous whole-night sleep staging system utilizing LIBS’s outputs. A hardware prototype is constructed from off-the-shelf electronic components and used to conduct 38 hours of sleep studies on 8 participants over a period of 30 days. Evaluation results show that LIBS can monitor biosignals representing brain activities, eye movements, and muscle contractions with excellent fidelity such that it can be used for sleep stage classification with an average of more than 95% accuracy.

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