Drowsiness Detection with Wireless, User-Generic, Dry Electrode Ear EEG.

Drowsiness monitoring can reduce workplace and driving accidents. To enable a discreet device for drowsiness monitoring and detection, this work presents a drowsiness user-study with an in-ear EEG system, which uses two user-generic, dry electrode earpieces and a wireless interface for streaming data. Twenty-one drowsiness trials were recorded across five human users and drowsiness detection was implemented with three classifier models: logistic regression, support vector machine (SVM), and random forest. To estimate drowsiness detection performance across usage scenarios, these classifiers were validated with user-specific, leave-one-trial-out, and leave-one-user-out training. To our knowledge, this is the first wireless, multi-channel, dry electrode in-ear EEG to be used for drowsiness monitoring. With user-specific training, a SVM achieved a detection accuracy of 95.9%. When evaluating a never-before-seen user, a similar SVM achieved a 94.5% accuracy, comparable to the best performing state-of-the-art wet electrode in-ear and scalp EEG systems.

Wireless User-Generic Ear EEG.

In the past few years it has been demonstrated that electroencephalography (EEG) can be recorded from inside the ear (in-ear EEG). To open the door to low-profile earpieces as wearable brain-computer interfaces (BCIs), this work presents a practical in-ear EEG device based on multiple dry electrodes, a user-generic design, and a lightweight wireless interface for streaming data and device programming. The earpiece is designed for improved ear canal contact across a wide population of users and is fabricated in a low-cost and scalable manufacturing process based on standard techniques such as vacuum forming, plasma-treatment, and spray coating. A 2.5 × 2.5 cm2 wireless recording module is designed to record and stream data wirelessly to a host computer. Performance was evaluated on three human subjects over three months and compared with clinical-grade wet scalp EEG recordings. Recordings of spontaneous and evoked physiological signals, eye-blinks, alpha rhythm, and the auditory steady-state response (ASSR), are presented. This is the first wireless in-ear EEG to our knowledge to incorporate a dry multielectrode, user-generic design. The user-generic ear EEG recorded a mean alpha modulation of 2.17, outperforming the state-of-the-art in dry electrode in-ear EEG systems.