JawLink: An In-Ear Optical Interface for Orofacial Movement Monitoring and Speech Detection

Voice prostheses such as the tracheoesophageal prosthesis (TEP) and electrolarynx (EL) restore speech after total laryngectomy but rely on manual activation, limiting autonomy and usability. This study investigates an in-ear proximity sensing approach for hands-free detection of speech intent, leveraging soft tissue deformation within the external auditory canal during mandibular motion. Ten healthy participants were fitted with bilateral, custom-fitted ear devices incorporating infrared sensors to record deformation patterns during structured speech and non-speech tasks. Signals were preprocessed using low-pass filtering, wavelet transforms, and temporal smoothing. A feature set combining time- and frequency-domain descriptors was extracted and ranked using minimum redundancy-maximum relevance selection criteria. Classifiers, including boosted trees and wide neural networks, were trained to distinguish speech from confounding orofacial behaviors. Results revealed consistent pre-phonatory and post-phonatory activation phases in the proximity signal, indicating detection of articulatory intent beyond acoustic onset. The best model for detecting speech with respect to baseline achieved an average F1 score of 84.04% $\pm ~$ 4.48% in a leave-one-subject-out cross-validation. An additional validation demonstrated a high F1 score of 94.49% $\pm ~$ 2.49% for distinguishing speech from clustered non-speech activities (e.g. chewing, yawning, smiling). These results support the robustness of the proposed system against false triggers. This work provides the first evidence that in-ear deformation signals can be used for robust speech detection in healthy controls, setting the stage for real-time, hands-free control of voice prostheses. The system offers a discreet, wearable platform for assistive communication technologies in patients with profound voice impairments.