Automated calibration of somatosensory stimulation using reinforcement learning

• Published in: Journal of neuroengineering and rehabilitation Vol. 20; no. 1; pp. 1 - 16
• Main Authors: Borda, Luigi, Gozzi, Noemi, Preatoni, Greta, Valle, Giacomo, Raspopovic, Stanisa
• Format: Journal Article
• Language: English
• Published: London BioMed Central 26.09.2023; BMC
• Subjects: Algorithms; Amputation; Artificial intelligence; Automatic calibration; Automation; Bioengineering; Calibration; Closed loop systems; Electrical stimulation; Electrical stimuli; Electrodes; Feedback; Graphical user interface; Machine learning; Mapping; Neural prostheses; Neuromodulation; Optimization techniques; Parameter identification; Peripheral nerves; Peripheral neuropathy; Prostheses; Prosthetics; Reinforcement; Reinforcement learning; Sensation; Sensory feedback; Stimulation; TENS

BackgroundThe identification of the electrical stimulation parameters for neuromodulation is a subject-specific and time-consuming procedure that presently mostly relies on the expertise of the user (e.g., clinician, experimenter, bioengineer). Since the parameters of stimulation change over time (d...