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Interpretation of Sensory Information from Skeletal Muscle Receptors for External Control Milan Djilas

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Interpretation of Sensory Information from Skeletal Muscle Receptors for External Control Milan Djilas Interpretation of Sensory Information From Skeletal Muscle Receptors For External Control Milan Djilas To cite this version: Milan Djilas. Interpretation of Sensory Information From Skeletal Muscle Receptors For External Control. Automatic. Université Montpellier II - Sciences et Techniques du Languedoc, 2008. English. tel-00333530 HAL Id: tel-00333530 https://tel.archives-ouvertes.fr/tel-00333530 Submitted on 23 Oct 2008 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. UNIVERSITE MONTPELLIER II SCIENCES ET TECHNIQUES DU LANGUEDOC T H E S E pour obtenir le grade de DOCTEUR DE L'UNIVERSITE MONTPELLIER II Formation doctorale: SYSTEMES AUTOMATIQUES ET MICROELECTRONIQUES Ecole Doctorale: INFORMATION, STRUCTURES ET SYSTEMES présentée et soutenue publiquement par Milan DJILAS le 13 octobre 2008 Titre: INTERPRETATION DES INFORMATIONS SENSORIELLES DES RECEPTEURS DU MUSCLE SQUELETTIQUE POUR LE CONTROLE EXTERNE INTERPRETATION OF SENSORY INFORMATION FROM SKELETAL MUSCLE RECEPTORS FOR EXTERNAL CONTROL JURY Jacques LEVY VEHEL Directeur de Recherches, INRIA Rapporteur Xavier NAVARRO Professeur, Université Autonome de Barcelone Rapporteur André CROSNIER Professeur, Université Montpellier II Examinateur Régis GUILLEMAUD Ingénieur, CEA Léti / Minatec Examinateur Serge PICAUD Directeur de Recherches, INSERM Examinateur Guy CATHEBRAS Professeur, Université Montpellier II Directeur de Thèse Christine AZEVEDO-COSTE Chargé de Recherches, INRIA Co-encadrante Ken YOSHIDA Associate Professor, IUPUI / Aalborg University Co-encadrant Preface This manuscript has been written to document my research work as a doctoral candidate in the DEMAR team at the Laboratory of Computer Science, Microelectronics and Control in Montpellier (LIRMM), during the period from October 2005 to October 2008. DEMAR (D´embulation et Mouvement Artificiel) is a joint project between the French National Institute in Computer Science and Control (INRIA), the French National Cen- ter for Scientific Research (CNRS), and Universities of Montpellier I and II. The team’s research activities are modeling and controlling the human sensory motor system, and im- planted neuroprosthetic devices. International collaboration between DEMAR and the Center for Sensory-Motor Inter- action (SMI) at the University of Aalborg in Denmark exists since 2003, and the research proposal for this thesis is the result of this collaboration. The proposal concerns the reha- bilitation of movement of paralyzed limbs through functional electrical stimulation (FES), an interdisciplinary field that requires joint efforts of scientists with backgrounds in neuro- physiology, robotics, and microelectronics. The objective of the project is to explore the possibility of using information from sensory nerve fibers of muscle receptors as feedback in closed-loop FES systems. Challenges involve theoretical, experimental, and technical aspects. Financial support for the duration of the thesis was insured by INRIA on the basis of funding provided by the European Aeronautic Defense and Space (EADS) corporate foundation. i Acknowledgements I would like to express my gratitude to everyone at the Laboratory of Computer Science, Robotics and Microelectronics in Montpellier (LIRMM) and its director, Michel Robert, for welcoming me and having me here for the last three years. I am also grateful to the European Aeronautic Defense and Space company (EADS) and their foundation for the funding provided for this thesis. Without their financial support, this thesis would have not been possible. I wish to express my deepest and sincere gratitude to my supervisors Christine Azevedo-Coste, permanent research scientist in the DEMAR project team, part of the French National Institute for Research in Computer Science and Control (INRIA), Guy Cath´ebras, professor at the University of Montpellier II, and Ken Yoshida, associate profes- sor at the Department of Biomedical Engineering at Indiana University - Purdue University Indianapolis (IUPUI), and also Associate Professor at the Center for Sensory-Motor Inter- action at the Department of Health Science and Technology at Aalborg University, for their never failing interest in discussing and commenting on research directions and manuscript drafts, and also for helping out with the animal experiments. Special thanks goes to David Guiraud, project leader of the DEMAR team, for his invaluable advise and support through- out the thesis. I would like to thank and J´erˆome Bourien, at the Institute of Neurosciences in Montpellier, for his valuable advise. I sincerely thank Xavier Navarro, professor at the Autonomous University of Barcelona, Jacques L´evy V´ehel, permanent research scientist in the APIS project team at INRIA, R´egis Guillemaud, head of the Laboratory of Microelectronics for Health (LE2S) at the French Atomic Energy Commission in Grenoble (CEA-LETI), Andr´eCrosnier, professor at the University of Montpellier II, and Serge Picaud, director of research at the French National Institute for Health and Medical Research (INSERM), for kindly accepting to be jury mem- bers at my thesis defense. I wish to thank the staff at the two locations where animal experiments took place, for their technical assistance: Ole Sørensen, Torben Madsen, Jens Sørensen and Henrik iii Barlebo from the Department of Pathology at Aarhus University Hospital in Aalborg; and Hubert Taillades from the Laboratory of Experimental Surgery at the Institute of Biology in Montpellier. Additional thanks goes to Mathijs Kurstjens for helping out with experiments and giving me a crash course in how to make nerve cuff electrodes, at the Bioelectronics Laboratory at the Center for Sensory-Motor Interaction at Aalborg University in Denmark. I also thank Thierry Duquesne and Olivier Tempier, for providing me with access to the robotics and microelectronics workshops, and for their technical assistance. Special thanks also to Annie Aliaga and Elisabeth Greverie, for their help with solving the maze of French administration. I thank my colleagues and friends at the lab, for providing a positive and stimulat- ing work environment: Carla Aguiar, Andreea-Elena Ancuta, Yousra Ben Zaida, Mourad Benoussaad, Antonio Bo, Vincent Bonnet, Floor Campfens, Lotfi Chikh, David Corbel, Michel Dominici, Lionel Gouyet, Mitsuhiro Hayashibe, J´er´emy Laforet, Chao Liu, Jos´e- Marconi Rodrigues, Sebastien Lengagne, Kevin Loquin, Baptiste Magnier, Ionut Olaru, Rog´erio Richa, Ashvin Sobhee, Guillaume Souquet, Jean-Mathias Spiewak, Walid Zarrad, and Dingguo Zhang. Thank you all again. It has been a pleasure. A big thanks to a few very special people outside the lab: Maria Papaiordanidou, Szy- mon Stoma, and Karine Dennis. Thank you for your friendship. Lastly, and most importantly, I would like to thank my family, brother Marko and par- ents Slavko and Dana, for their support and encouragement throughout my graduate stud- ies. To them I dedicate this thesis. Abstract The topic of this thesis was the rehabilitation of movement of paralyzed limbs through functional electrical stimulation (FES). The objective of the project was to explore the possibility of using information from sensory nerve fibers of muscle receptors as feedback of the closed-loop control of FES systems using intrafascicular peripheral nerve electrodes. Acute animal experiments were performed to record afferent muscle spindle responses to passive stretch. The recordings were performed using the new thin-film Longitudinal Intra-Fascicular Electrode (tfLIFE), developed by Dr. Ken Yoshida at Aalborg University in Denmark. A first-order model of muscle spindle response to passive muscle stretch was proposed that manages to capture the non-linear properties of the afferent neural activity. Moreover, estimation of muscle state from the recorded multi-channel ENG provided more robust results compared to using single-channel recordings. For the abovementioned model to be usable in a estimator of muscle state, the rate of change of muscle length during movement must have negligible effect on model param- eters. A neural spike detection and classification scheme was developed for the purpose of isolating sensory neural activity of muscle receptors having minimal sensitivity to the velocity of muscle motion. The algorithm was based on the multi-scale continuous wavelet transform using complex wavelets. The detection scheme outperformes the commonly used simple threshold detection, especially with recordings having low SNR. Results of classifi- cation of units indicate that the developed classifier is able to isolate activity having linear relationship with muscle length, which is a step towards on-line model-based estimation of muscle length that can be used in a closed-loop FES system with natural sensory feedback. One of the main issues limiting the interpretation of ENG data is the low level of the neural signal compared to the level of noise in the recordings. Our hypothesis was that shielding the implant site would help improve signal-to-noise level. Experimental results from a preliminary study we had performed
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