Papers by Mitsuhiro Hayashibe
2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011
In current biomechanics approach, the assumptions are commonly used in body-segment parameters an... more In current biomechanics approach, the assumptions are commonly used in body-segment parameters and muscle strength parameters due to the difficulty in accessing those subject-specific values. Especially in the rehabilitation and sports science where each subject can easily have quite different anthropometry and muscle condition due to disease, age or training history, it would be important to identify those parameters to take benefits correctly from the recent advances in computational musculoskeletal modeling. In this paper, Mass Distribution Identification to improve the joint torque estimation and Muscle Strength Identification to improve the muscle force estimation were performed combined with previously proposed methods in muscle tension optimization. This first result highlights that the reliable muscle force estimation could be extracted after these identifications. The proposed framework toward subject-specific musculoskeletal modeling would contribute to a patient-oriented computational rehabilitation.
2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), 2012
In order to understand the human motion control strategies and to restore these functions, or to ... more In order to understand the human motion control strategies and to restore these functions, or to artificially generate limbs motion it is necessary to have an accurate understanding of the limb dynamics. The inertial parameters can be identify easily, however the joint dynamics is still difficult to model due to the time change with muscle contraction level, fatigue and non-linear dynamics. Using Functional Electrical Stimulation (FES) we propose to identify the joint active dynamics with the pendulum test and to establish a relationship between the level of muscle contraction induced by the stimulation and the visco-elasticity. We measure the data of 2 healthy subjects and propose a model for the knee joint visco-elasticity changes. Authors acknowledge the support provided by the INRIA-JSPS joint program AYAME (2010-2012). Gentiane Venture and Seiya Sakaguchi are with the Depart
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012
Functional electrical stimulation (FES) is able to restore motor function of spinal cord injured ... more Functional electrical stimulation (FES) is able to restore motor function of spinal cord injured (SCI) patients. To make adaptive FES control taking into account the actual muscle state with muscular feedback information, torque estimation and prediction are important to be provided beforehand. Evoked EMG (eEMG) has been found to be highly correlated with FES-induced torque under various muscle conditions, indicating that it can be an useful tool for torque/force prediction. To better construct the relationship between eEMG and stimulated muscular torque, nonlinear-arx-type (NARXtype) model is preferred. This paper presents and exploits a NARX-type recurrent neural network (NARX-RNN) model for identification and prediction of FES-induced muscular dynamics with eEMG. Such NARX-RNN model is with a novel architecture for prediction, with robust prediction performance. To make fast convergence for identification of such NARX-RNN, directly-learning pattern is exploited during the learning phase. Due to difficulty of choosing a proper forgetting factor of Kalman filter for predicting time-variant torque with eEMG, such NARX-RNN may be considered to be a better alternative as torque predictor. Data gathered from two SCI patients is used to evaluate the proposed NARX-RNN model. The NARX-RNN model shows promising estimation and prediction performance only based on eEMG.
2020 3rd International Conference on Control and Robots (ICCR)
The computational study of human balance recovery strategy is crucial for revealing effective str... more The computational study of human balance recovery strategy is crucial for revealing effective strategy in human balance rehabilitation and humanoid robot balance control. In this context, many efforts have been made to improve the ability of quiet standing human balance. There are three main strategies for human balance including (i) ankle, (ii) hip, and (iii) stepping strategies. Besides, arm usage was considered for balance control of human walking. However, there exist few works about effectiveness assessment of arm strategy for quiet standing balance recovery. In this paper, we proposed a nonlinear model predictive control (NMPC) for human balance control on a simplified model with sagittal arm rotation. Three case studies including (i) active arms, (ii) passive arms, and (iii) fixed arms were considered to discuss the effectiveness of arm usage for human balance recovery during quiet standing. Besides, the total root mean square (RMS) deviation of joint angles was computed as an index of human motion intensity quantification. The proposed solution has been implemented for a human-like balance recovery with arm usages during quiet standing under perturbation and shows the effectiveness of arm strategy.
Frontiers in Neurorobotics, 2021
The study of human balance recovery strategies is important for human balance rehabilitation and ... more The study of human balance recovery strategies is important for human balance rehabilitation and humanoid robot balance control. To date, many efforts have been made to improve balance during quiet standing and walking motions. Arm usage (arm strategy) has been proposed to control the balance during walking motion in the literature. However, limited research exists on the contributions of the arm strategy for balance recovery during quiet standing along with ankle and hip strategy. Therefore, in this study, we built a simplified model with arms and proposed a controller based on nonlinear model predictive control to achieve human-like balance control. Three arm states of the model, namely, active arms, passive arms, and fixed arms, were considered to discuss the contributions of arm usage to human balance recovery during quiet standing. Furthermore, various indexes such as root mean square deviation of joint angles and recovery energy consumption were verified to reveal the mechanis...
IEEE Access, 2020
The purpose of this study is to implement a human-like balance recovery controller and analyze it... more The purpose of this study is to implement a human-like balance recovery controller and analyze its robustness and energy consumption. Three main techniques to maintain balance can be distinguished in humans, namely (i) the ankle strategy, (ii) the hip-ankle strategy, (iii) the stepping strategy. Because we only consider quiet standing balance, then stepping is not included in our balance recovery study. Numerical model predictive control (N-MPC) is proposed to predict the best way to maintain balance against various disturbance forces. To simulate balance recovery, we build a three-link model including a foot with unilateral constraints, the lower body, and the upper body. Subsequently, we derive the dynamical equations of the model and linearize them. Based on human balance capabilities, we set bound constraints on our model, including angles and balance torques of the ankle and hip. Unilateral constraints are set on the foot, which makes our model more similar to the human quiet standing case. Finally, we implemented a simulation of the proposed ankle and hip-ankle strategy in simulation and analyzed the obtained results from kinematic and dynamic indices as well as from an energy consumption perspective. The robustness of the proposed controller was verified through the obtained simulation results. Thus, this study provides a better understanding of human quiet standing balance that could be useful for rehabilitation.
2A1-13-016 ガルバノスキャナと高速カメラを用いたリアルタイムレーザポインティング内視鏡
Medical Image Analysis, 2006
In laparoscopic surgery, surgeons find particular difficulties related to the operation technique... more In laparoscopic surgery, surgeons find particular difficulties related to the operation technique. Due to restricted view, lack of depth information from the monocular endoscope and limited degree of freedom, surgeons find their movements impeded. A support system that provides improved laparoscopic vision would help to overcome the difficulties. If real-time visualization of abdominal structures were feasible, more accurate procedures and improved quantitative evaluations in laparoscopic surgery might be possible. In this study, a laser-scan endoscope system was developed to acquire and visualize the shape and texture of the area of interest instantaneously. The intraoperative geometric information of deformable organ could be applied for robotic safety management via geometric computation of robot position and organ shape. Results of in vivo experiments on a pig liver verified effectiveness of the proposed system.
Brain Sciences
This study is aimed at the detection of single-trial feedback, perceived as erroneous by the use... more This study is aimed at the detection of single-trial feedback, perceived as erroneous by the user, using a transferable classification system while conducting a motor imagery brain–computer interfacing (BCI) task. The feedback received by the users are relayed from a functional electrical stimulation (FES) device and hence are somato-sensory in nature. The BCI system designed for this study activates an electrical stimulator placed on the left hand, right hand, left foot, and right foot of the user. Trials containing erroneous feedback can be detected from the neural signals in form of the error related potential (ErrP). The inclusion of neuro-feedback during the experiments indicated the possibility that ErrP signals can be evoked when the participant perceives an error from the feedback. Hence, to detect such feedback using ErrP, a transferable (offline) decoder based on optimal transport theory is introduced herein. The offline system detects single-trial erroneous trials from t...
ISRN Rehabilitation, 2013
Skeletal muscle system has nonlinear dynamics and subject-specific characteristics. Thus, it is e... more Skeletal muscle system has nonlinear dynamics and subject-specific characteristics. Thus, it is essential to identify the unknown parameters from noisy biomedical signals to improve the modeling accuracy in neuroprosthetic control. The objective of this work is to develop an experimental identification method for subject-specific biomechanical parameters of a physiological muscle model which can be employed to predict the nonlinear force properties of stimulated muscle. Our previously proposed muscle model, which can describe multiscale physiological system based on the Hill and Huxley models, was used for the identification. The identification protocols were performed on two rabbit experiments, where the medial gastrocnemius was attached to a motorized lever system to record the force by the nerve stimulation. The muscle model was identified using nonlinear Kalman filters: sigma-point and extended Kalman filter. The identified model was evaluated by comparison with experimental mea...
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2014
This paper presents a novel approach for simulating 3D muscle deformations with complex architect... more This paper presents a novel approach for simulating 3D muscle deformations with complex architectures. The approach consists in choosing the best model formulation in terms of computation cost and accuracy, that mixes a volumetric-tissue model based on finite element method (3D FEM), a muscle fiber model (Hill contractile 1D element) and a membrane model accounting for aponeurosis tissue (2D FEM). The separate models are mechanically binded using barycentric embeddings. Our approach allows the computation of several fiber directions in one coarse finite element, and thus, strongly decreases the required finite element resolution to predict muscle deformation during contraction. Using surface registration, fibers tracks of specific architecture can be transferred from a template to subject morphology, and then simulated. As a case study, three different architectures are simulated and compared to their equivalent one dimensional Hill wire model simulations.
Nonlinear identification of skeletal muscle dynamics with sigma-point kalman filter for model-based FES
Icra, May 19, 2008
Nonlinear identification of skeletal muscle dynamics with sigma-point kalman filter for model-based FES
Icra, May 19, 2008
Nonlinear identification of skeletal muscle dynamics with sigma-point kalman filter for model-based FES
2008 IEEE International Conference on Robotics and Automation, 2008
A robotic surgery system (da Vinci) with image guided function--system architecture and cholecystectomy application.
We have developed a data fusion system for the robotics surgery system" da Vinci". The data fusio... more We have developed a data fusion system for the robotics surgery system" da Vinci". The data fusion system is composed of an optical 3D location sensor and a digital video processing system. The 3D location sensor is attached to the da Vinci's laparoscope and measures its location and direction. The digital video processing system captures the laparoscope's view and superimposes 3D patient's organ models onto the captured view in real-time. We applied the system to" da Vinci" and examined this system during a cholecystectomy.
Development of a data fusion system using color information for real-time intraoperative liver surface measurement
Abstract. The goal of our study is to develop. 1 daa fusion system. winch enables surgeons to cas... more Abstract. The goal of our study is to develop. 1 daa fusion system. winch enables surgeons to casih Msiiali/cd ic inner smn. iun.-s of clastic organs during open sunken We chose the lrscr as the focus of this stixh due to its easiK detbnnable maure and complex\ ascular structures. To do so. we propose usmg prcoperab\ e data and supplcmcntary mtawperamc d* a.\\ l-captured a sequence of Incr surface cLiLi for the traraopcrame JH!
Experimental parameter identification of a multi-scale musculoskeletal model controlled by electrical stimulation: application to patients with spinal cord injury.
We investigated the parameter identification of a multi-scale physiological model of skeletal mus... more We investigated the parameter identification of a multi-scale physiological model of skeletal muscle, based on Huxley's formulation. We focused particularly on the knee joint controlled by quadriceps muscles under electrical stimulation (ES) in subjects with a complete spinal cord injury. A noninvasive and in vivo identification protocol was thus applied through surface stimulation in nine subjects and through neural stimulation in one ES-implanted subject.
Marker-less whole body skeletal motion analysis based on a body surface model constructed from multi-camera images
Medical virtual reality: an application to surgery simulation].
1. Fukuoka Igaku Zasshi. 2005 Feb;96(2):44-8. [Medical virtual reality: an application to surgery... more 1. Fukuoka Igaku Zasshi. 2005 Feb;96(2):44-8. [Medical virtual reality: an application to surgery simulation]. [Article in Japanese]. Suzuki S, Suzuki N, Hattori A, Hayashibe M, Otake Y, Konishi K, Kakeji Y, Hashizume M. Institute for High Dimensional Medical Imaging, The Jikei University School of Medicine. PMID: 15852662 [PubMed - indexed for MEDLINE]. MeSH Terms. Computer Simulation*; Surgical Procedures, Operative*; User-Computer Interface.
Development of a 3D Measurement System for Surgical Field Deformation with Geometric Pattern Projection
Abstract; Recently, navigation technologies for supporting acurate surgery by indicating the surg... more Abstract; Recently, navigation technologies for supporting acurate surgery by indicating the surgical field during the operation have been studied and applied to clinical fields. Navigation for soft tissues which easily change the form and position, require position sensor to enable the measurement of deformed state in time series. This study employs a system with real time capture using the geometric pattern projected by a PC projector on the object taken by DV cameras from many directions.
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Papers by Mitsuhiro Hayashibe