M
Mitsuhiro Hayashibe
Researcher at Tohoku University
Publications - 191
Citations - 2009
Mitsuhiro Hayashibe is an academic researcher from Tohoku University. The author has contributed to research in topics: Computer science & Functional electrical stimulation. The author has an hindex of 21, co-authored 161 publications receiving 1645 citations. Previous affiliations of Mitsuhiro Hayashibe include University of Montpellier & French Institute for Research in Computer Science and Automation.
Papers
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Proceedings ArticleDOI
Joint angle estimation in rehabilitation with inertial sensors and its integration with Kinect
TL;DR: A new method based on Kalman filtering was developed in order to perform online calibration of sensor errors automatically whenever measurements from Kinect are available.
Journal ArticleDOI
Laser-scan endoscope system for intraoperative geometry acquisition and surgical robot safety management
TL;DR: A laser-scan endoscope system was developed to acquire and visualize the shape and texture of the area of interest instantaneously and could be applied for robotic safety management via geometric computation of robot position and organ shape.
Journal ArticleDOI
FES-Induced Torque Prediction With Evoked EMG Sensing for Muscle Fatigue Tracking
TL;DR: The assessment with experimental data reveals that the identified eEMG-to-torque model properly predicts fatiguing muscle behavior, and the performance of the time-varying parameter estimation is efficient, suggesting that real-time tracking is feasible with a Kalman filter and driven by e EMG sensing in the application of FES.
Journal ArticleDOI
Muscle Fatigue Tracking with Evoked EMG via Recurrent Neural Network: Toward Personalized Neuroprosthetics
TL;DR: A NARX recurrent neural network (NARX-RNN) model is presented for identification/prediction of FES-induced muscular dynamics with eEMG and the general importance regarding CI-based motor function modeling is introduced along with its potential impact in the rehabilitation domain.
Journal ArticleDOI
Evoked Electromyography-Based Closed-Loop Torque Control in Functional Electrical Stimulation
TL;DR: The nature of the predictive controller facilitates prediction of the muscle mechanical response and the system can therefore control joint torque from EMG feedback and also respond to time-variant muscle state changes.