TY - CHAP
T1 - NeuraLoop
T2 - A System for Bidirectional High-Bandwidth Interfacing Using Myoelectric Signals and Electrotactile Feedback
AU - Dosen, Strahinja
AU - Dalgaard, Hans Henrik
AU - Rey, Alice Ghislaine Colette
AU - Dam, Elias Thomassen
AU - Jorgovanovic, Nikola
AU - Strbac, Matija
AU - Murciego, Luis Pelaez
AU - Spaich, Erika Geraldina
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - Myoelectric control has been traditionally used in clinical applications, but from recently, there has been an increasing interest in applying this approach for more general human-machine interfacing. Here, we present NeuraLoop, a compact system for the simultaneous recording of electrical muscle activity (EMG) and delivery of electrotactile stimulation. The system uses a matrix electrode with 32 stimulation and 32 recording pads, thereby allowing high- resolution EMG recording for gesture recognition and spatially distributed stimulation for high-fidelity haptic feedback. We demonstrated the system by using NeuraLoop to detect and classify micro-gestures, which are quick, small, and transient movements, often used to interact with consumer devices. The preliminary results are encouraging although there is room for improvement. Future work will increase gesture classification performance and add haptic feedback, opening opportunities for many relevant applications of bidirectional human-machine interfacing using gesture recognition and electrotactile haptics.
AB - Myoelectric control has been traditionally used in clinical applications, but from recently, there has been an increasing interest in applying this approach for more general human-machine interfacing. Here, we present NeuraLoop, a compact system for the simultaneous recording of electrical muscle activity (EMG) and delivery of electrotactile stimulation. The system uses a matrix electrode with 32 stimulation and 32 recording pads, thereby allowing high- resolution EMG recording for gesture recognition and spatially distributed stimulation for high-fidelity haptic feedback. We demonstrated the system by using NeuraLoop to detect and classify micro-gestures, which are quick, small, and transient movements, often used to interact with consumer devices. The preliminary results are encouraging although there is room for improvement. Future work will increase gesture classification performance and add haptic feedback, opening opportunities for many relevant applications of bidirectional human-machine interfacing using gesture recognition and electrotactile haptics.
UR - http://www.scopus.com/inward/record.url?scp=86000635545&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-77588-8_67
DO - 10.1007/978-3-031-77588-8_67
M3 - Chapter
AN - SCOPUS:86000635545
T3 - Biosystems and Biorobotics
SP - 331
EP - 334
BT - Biosystems and Biorobotics
PB - Springer Science and Business Media Deutschland GmbH
ER -