Seminar: Dr Mitsuhiro Hayashibe, INRIA

One of the challenging issues in computational rehabilitation is that there is a large variety of patient situations depending on the type of neurological disorder. To improve the performance of motor neuroprosthetics beyond the current limited use of such system, subject-specific modelling would be essential. In addition, human characteristics are basically time variant, for instance, neuromuscular dynamics may vary according to muscle fatigue. In order to correspond to time-varying characteristics, we believe that robust bio-signal processing and model-based control which can manage the nonlinearity and time variance of the system, would bring break-through and new modality in rehabilitation.

In order to predict FES-induced joint torque, evoked-Electromyography (eEMG) has been applied to correlate muscle electrical and mechanical activities. Although muscle fatigue represents time-variant, subject-specific and protocol-specific characteristics, the proposed Kalman filter-based adaptive identification method is able to predict the time-variant torque systematically.  The robustness of the torque prediction has been investigated in a fatigue tracking task in experiment with Spinal Cord Injured subjects. The results demonstrate good tracking performance of muscle variations in the presence of fatigue and against some other disturbances. A new control strategy, EMG-Feedback Predictive Control (EFPC), is proposed to adaptively control stimulation pattern compensating to time-varying muscle state changes.

This presentation will also introduce some recent results regarding volumetric muscle modelling and human posture measurement.

Bio:

Mitsuhiro Hayashibe received the B.S. degree in mechano-aerospace engineering from Tokyo Institute of Technology in 1999. M.S. and Ph.D. degrees from University of Tokyo, graduate school of engineering in 2001 and 2005 respectively. He was an assistant professor at Jikei University School of Medicine, Department of Medicine, Research Center for Medical Sciences from 2001 to 2006, and a postdoctoral fellow at INRIA Sophia Antipolis and LIRMM from 2007. Since 2008, he has been a research scientist with INRIA and LIRMM, Computational Medicine and neurosciences, DEMAR project. His research interests include modeling and identification of neuromuscular dynamics and biomechanics. He received Best Paper Award from Journal of Japanese Society for Computer-aided Surgery and CAS Young Investigator Award, Gold Prize from Hitachi Medical Systems. He is a member of IEEE Engineering in Medicine and Biology Society, and French side leader of Japan-France Integrated Action Program AYAME supported by JSPS and INRIA (2010-2012).