Virtual reality interactions via a user-generic ultrasound human-machine interface for wrist and hand tracking.

ABSTRACT: As computers move from desktop screens into our glasses, traditional controllers such as keyboards and mice have proven impractical. A control interface for immersive experiences needs to seamlessly transport intention from the real to the virtual world while remaining portable, accurate, and robust. Here, we present an easy-to-wear, dry-contact and portable ultrasound armband that can decode morphological information and act as a virtual reality controller by predicting hand and wrist kinematics. Using our armband, we collected a large dataset of paired ultrasound and hand kinematics and used it to train supervised deep-learning models capable of predicting hand kinematics from ultrasound. We explored how diverse intra-session, cross-session, and cross-participant data shifts affect model

SUBMITTER: Grandi Sgambato B 

PROVIDER: S-EPMC12699032 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature