Speaking without vocal folds using a machine-learning-assisted wearable sensing-actuation system

Abstract Voice disorders resulting from various pathological vocal fold conditions or postoperative recovery of laryngeal cancer surgeries, are common causes of dysphonia. Here, we present a self-powered wearable sensing-actuation system based on soft magnetoelasticity that enables assisted speaking without relying on the vocal folds. It holds a lightweighted mass of approximately 7.2 g, skin-alike modulus of 7.83 × 10 5 Pa, stability against skin perspiration, and a maximum stretchability of 164%. The wearable sensing component can effectively capture extrinsic laryngeal muscle movement and convert them into high-fidelity and analyzable electrical signals, which can be translated into speech signals with the…

• AH
  American Heart Association

  Awards: 23SCEFIA1157587, 23IPA1054908, 23TPA1141360
• NI
  National Institutes of Health

  Awards: KL2TR001882, R01 CA287326
• UO
  University of California, Los Angeles
• OO
  Office of Naval Research

  Awards: N00014-24-1-2065, N00014
• CA
  Clinical and Translational Science Institute, University of California, Los Angeles

  Award: KL2TR001882