Sensing physiological signals from the human head has long been used for medical diagnosis, human-computer interaction, meditation quality monitoring, among others. However, existing sensing techniques are cumbersome and not desirable for long-term studies and impractical for daily use. Due to these limitations, we explore a new form of wearable systems, called LIBS, that can continuously record biosignals such as brain wave, eye movements, and facial muscle contractions, with high sensitivity and reliability. Specifically, instead of placing numerous electrodes around the head, LIBS uses a minimal number of custom-built electrodes to record the biosignals from human ear canals. This recording is a combination of three signals of interest and unwanted noise. Therefore, we design an algorithm using a supervised Nonnegative Matrix Factorization (NMF) model to split the single-channel mixed signal into three individual signals representing electrical brain activities (EEG), eye movements (EOG), and muscle contractions (EMG). Through prototyping and implementation over a 30 day sleep experiment conducted on eight participants, our results prove the feasibility of concurrently extracting separated brain, eye, and muscle signals for fine-grained sleep staging with more than 95% accuracy. With this ability to separate the three biosignals without loss of their physiological information, LIBS has a potential to become a fundamental in-ear biosensing technology solving problems ranging from self-caring health to non-health and enabling a new form of human communication interfaces.
Physiological signals generated from human brain, eye, and facial muscle activities can reveal enormous insight into an individual's mental state and bodily functions. For example, acquiring these biosignals is critical to diagnose sleep quality for clinical reasons, among other auxiliary signals. Even though providing highly reliable brain signal Electroencephalography (EEG), eye signal Electrooculography (EOG), and muscle signal Electromyography (EMG), the gold-standard methodology, referred to as Polysomnography (PSG),9 has many limitations. Specifically, PSG attaches a large number of wired electrodes around human head, requires an expert sensor hookup at a laboratory, and provides a risk of losing sensor contact caused by body movements during sleep. Consequently, this gold-standard approach is uncomfortable, cumbersome to use, and expensive and time-consuming to set up.
As an effort to overcome the inherent limitations of PSG, there exist various wearable solutions developed to acquire the biosignals with high resolution and easy self-applicability. They involve electrode caps, commercial head-worn devices (e.g., EMOTIV, NeuroSky MindWave, MUSE, Kokoon, Neuroon Open, Aware, Naptime, Sleep Shepherd, etc.), and hearing aid-like research devices.6, 10 However, these solutions are stiff, unstable, and only suitable for either short-term applications or in-hospital use. In other words, they are still inconvenient and less socially acceptable for outdoor, long-term, and daily activities.
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