
Mitsuhiro HayashibeTohoku University | Tohokudai · Graduate School of Engineering
Mitsuhiro Hayashibe
PhD, Habilitation
About
264
Publications
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Introduction
Additional affiliations
September 2008 - March 2017
January 2007 - present
Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM)
April 2001 - December 2006
Education
April 2001 - March 2005
Publications
Publications (264)
Four-legged robots are becoming increasingly pivotal in navigating challenging environments, such as construction sites and disaster zones. While substantial progress in robotic mobility has been achieved using reinforcement learning techniques, quadruped animals exhibit superior agility by employing fundamentally different strategies. Bio-inspired...
Reliable proprioception and feedback from soft sensors are crucial for enabling soft robots to function intelligently in real-world environments. Nevertheless, soft sensors are fragile and are susceptible to various damage sources in such environments. Some researchers have utilized redundant configuration, where healthy sensors compensate instanta...
Humans exploit motor synergies for motor control; however, how they emerge during motor learning is not clearly understood. Few studies have dealt with the computational mechanism for generating synergies. Previously, optimal control generated synergistic motion for the upper limb; however, it has not yet been applied to the high-dimensional whole-...
The Hybrid Brain Computer Interface system (hBCI), which combines two or more Electroencephalography(EEG) modes, has flourished due to the development of instruments and methods. In particular, hBCI combining Steady State Visually Evoked Potentials (SSVEP) and Motor Imagery (MI) has attracted attention for its detection stability and multi-class cl...
In Japan, the aging population has led to a concerning decline in motor function, particularly evident in activities like driving, where cognitive abilities and motor skills are crucial. This decline has resulted in an increase in accidents involving elderly drivers, emphasizing the need for rehabilitation. Research indicates that tactile and propr...
Many studies have shown that complex tasks such as walking are controlled by groups of coactive muscles or joints, or synergies. In the analysis of muscle synergies, it is important to reveal their biomechanical functions for specific tasks. However, how the function of muscle synergies is altered by walking speed has not been studied in detail. In...
Walking and cycling are vital motor activities in rehabilitation and athletic training. Its in-depth movement analysis is essential in understanding muscle control because it provides insights into how muscles are coordinated during daily activities. Electromyography (EMG) offers measures regarding multiple muscles’ spatiotemporal activity patterns...
Introduction
When humans grasp an object, they are capable of recognizing its characteristics, such as its stiffness and shape, through the sensation of their hands. They can also determine their level of confidence in the estimated object properties. In this study, we developed a method for multi-fingered hands to estimate both physical and geomet...
The joint moment is a key measurement in locomotion analysis. Transferable prediction across different subjects is advantageous for calibration-free, practical clinical applications. However, even for similar gait motions, intersubject variance presents a significant challenge in maintaining reliable prediction performance. The optimal deep learnin...
This paper proposes a fixture-free 2D sewing system using a dual-arm manipulator, i.e., the seam lines of the top and bottom fabric parts are the same. The proposed 2D sewing system sews two stacked fabric parts together along a desired seam line printed on the top fabric part without the use of a fixture by applying a novel vision-based seam line...
Humans have many redundancies in their bodies and can make effective use of them to adapt to changes in the environment while walking. They can also vary their walking speed in a wide range. Human-like walking in simulation or by robots can be achieved through imitation learning. However, the walking speed is typically limited to a scale similar to...
How our central nervous system efficiently controls our complex musculoskeletal system is still debated. The muscle synergy hypothesis is proposed to simplify this complex system by assuming the existence of functional neural modules that coordinate several muscles. Modularity based on muscle synergies can facilitate motor learning without compromi...
Vertebrates possess a biomechanical structure with redundant muscles, enabling adaptability in uncertain and complex environments. Harnessing this inspiration, musculoskeletal systems offer advantages like variable stiffness and resilience to actuator failure and fatigue. Despite their potential, the complex structure presents modelling challenges...
Policy learning enables agents to learn how to map states to actions, thus enabling adaptive and flexible behavioral generation in complex environments. Policy learning methods are fundamental to reinforcement learning techniques. However, as problem complexity and the requirement for motion flexibility increase, traditional methods that rely on ma...
Humans can generate and sustain a wide range of walking velocities while optimizing their energy efficiency. Understanding the intricate mechanisms governing human walking will contribute to the engineering applications such as energy-efficient biped robots and walking assistive devices. Reflex-based control mechanisms, which generate motor pattern...
The steady increase in the aging population worldwide is expected to cause a shortage of doctors and therapists for older people. This demographic shift requires more efficient and automated systems for rehabilitation and physical ability evaluations. Rehabilitation using mixed reality (MR) technology has attracted much attention in recent years. M...
This paper proposes a fixture-free 2D sewing system using a dual-arm manipulator, i.e., the seam lines of the top and bottom fabric parts are the same. The proposed 2D sewing system sews two stacked fabric parts together along a desired seam line printed on the top fabric part without the use of a fixture. In the proposed system, the set of aligned...
Advancements in neuroscience and artificial intelligence are propelling rapid progress in brain–computer interfaces (BCIs). These developments hold significant potential for decoding motion intentions from brain signals, enabling direct control commands without reliance on conventional neural pathways. Growing interest exists in decoding bimanual m...
Accurate estimation of gait phases during walking is a crucial prerequisite for both extracting clinically meaningful gait parameters and delivering gait-based feedback control information to rehabilitation devices. In addition, speed variation appears in our daily walking locomotion. However, most existing IMU-related methods based on heuristic al...
p>This paper proposes a fixture-free 2D sewing system using a dual-arm manipulator, i.e., the seam lines of the top and bottom fabric parts are the same. The proposed 2D sewing system sews two stacked fabric parts together along a desired seam line printed on the top fabric part without the use of a fixture by applying a novel vision-based seam lin...
We propose a novel approach for estimating ground reaction forces (GRFs) during walking in stroke patients using a markerless motion capture (MMC) system, specifically the Azure Kinect, and a long short-term memory (LSTM) network. GRFs are crucial indicators of walking ability, but their measurement typically requires force plates, which are not re...
The use of neurofeedback is an important aspect of effective motor rehabilitation as it offers real-time sensory information to promote neuroplasticity. However, there is still limited knowledge about how the brain’s functional networks reorganize in response to such feedback. To address this gap, this study investigates the reorganization of the b...
The pneumatic and hydraulic dual actuation of pressure-driven soft actuators (PSAs) is promising because of their potential to develop novel practical soft robots and expand the range of soft robot applications. However, the physical characteristics of air and water are largely different, which makes it challenging to quickly adapt to a selected ac...
The lack of intuitive controllability remains a primary challenge in enabling transhumeral amputees to control a prosthesis for arm reaching with residual limb kinematics. Recent advancements in prosthetic arm control have focused on leveraging the predictive capabilities of artificial neural networks (ANNs) to automate elbow joint motion and wrist...
A self-organized phenomenon in postural coordination is essential for understanding the auto-switching mechanism of in-phase and anti-phase postural coordination modes during standing and related supra-postural activities. Previously, a model-based approach was proposed to reproduce such self-organized phenomenon. However, if we set this problem in...
Navigation among pedestrians is a crucial capability of service robots; however, it is a challenge to manage time-varying environments stably. Recent deep reinforcement learning (DRL)-based approaches to crowd navigation have yielded numerous promising applications. However, they rely heavily on initial imitation learning and colossal positive data...
The autonomous distillation of physical laws only from data is of great interest in many scientific fields. Data-driven modeling frameworks that adopt sparse regression techniques, such as sparse identification of nonlinear dynamics (SINDy) and its modifications, are developed to resolve difficulties in extracting underlying dynamics from experimen...
Transhumeral amputees experience considerable difficulties with controlling a multifunctional prosthesis (powered hand, wrist, and elbow) due to the lack of available muscles to provide electromyographic (EMG) signals. The residual limb motion strategy has become a popular alternative for transhumeral prosthesis control. It provides an intuitive wa...
Motion prediction based on kinematic information such as body segment displacement and joint angle has been widely studied. Because motions originate from forces, it is beneficial to estimate dynamic information, such as the ground reaction force (GRF), in addition to kinematic information for advanced motion prediction. In this study, we proposed...
One of the fundamental limitations in human biomechanics is that we cannot directly obtain joint moments during natural movements without affecting the motion. However, estimating these values is feasible with inverse dynamics computation by employing external force plates, which can cover only a small area of the plate. This work investigated the...
Recently, soft robotics has gained considerable attention as it promises numerous applications thanks to unique features originating from the physical compliance of the robots. Biomimetic underwater robots are a promising application in soft robotics and are expected to achieve efficient swimming comparable to the real aquatic life in nature. Howev...
Generating multimodal locomotion in underactuated bipedal robots requires control solutions that can facilitate motion patterns for drastically different dynamical modes, which is an extremely challenging problem in locomotion-learning tasks. Also, in such multimodal locomotion, utilizing body morphology is important because it leads to energy-effi...
Imitation learning is a promising approach for robots to learn complex motor skills. Recent techniques allow robots to learn long-term movements comprising multiple sub-behaviors. However, learning the temporal structures of movements from a demonstration is challenging, particularly when sub-behaviors overlap and are not labeled in advance. This s...
The synchronization phenomenon refers to the gradual synchronization of simple elements with different rhythms due to mutual influence and is observed across various fields, e.g., natural sciences to humanities and social sciences. Synchronization can be observed at various levels in the human brain, for example, epilepsy due to the abnormal synchr...
Quadruped robots are promising mobile robots for practical applications due to their higher locomotor ability in adverse conditions such as construction and disaster sites. In recent years, previous studies have proposed many methods for controlling legged robots using deep reinforcement learning. Additionally, spiking neural networks (SNNs), which...
Image recognition and reinforcement learning have become increasingly essential for robot control. With image data, we can obtain information on the position and shape of an object without attaching sensors to robots. Reinforcement learning can be applied directly to non-linear systems, which makes it applicable to a wide range of robotic systems....
As Japan’s population ages, the incidence of falls due to decreased motor function among elderly people has increased. Consequently, there is a growing demand for balance rehabilitation to prevent falls. Traditionally rehabilitation has been conducted on a one-on-one basis between therapist and patient, with evaluations heavily dependent on the the...
Various fluids can actuate a Fluidic Elastomer Actuator (FEA) as long as fluid can pressurize an internal chamber of an FEA. The choice of the pressurizing fluid significantly affects the FEA characteristics. However, few studies have quantitatively evaluated the differences in FEA characteristics with different pressurizing fluids. Especially to o...
Walking is one of the most important physical activities. Many people suffer from gait disorders due to injuries or neurological diseases such as stroke. Therefore, the necessity of gait analysis has increased. In previous studies, electromyography was used to analyze gait. The muscle synergy hypothesis has been used as a method to reduce the dimen...
In gait analysis, ground reaction forces (GRFs) provide important information about gait function assessment. However, due to the financial and time-consuming costs, the use of force plates for gait assessment in the rehabilitation field is limited. To solve these problems, previous studies have conducted to estimate the GRFs without the force plat...
Snake-like robots are expected in disaster rescue, because they can go through narrow space that we cannot reach. Wild snakes behave various style of locomotion depending on their species or habitat. By providing feedback this feature, we must able to develop more versatile robots. We attempt to develop the robot that can locomote various terrain a...
Hand movement is an essential motor function in daily life, and maintaining the motor function of the hand is important to prevent a decline in quality of life. Hand exercises are effective in preventing dementia, promoting health, and improving motor functions, and are actively incorporated into rehabilitation. However, the accelerating aging of t...
Introduction
Emerging deep learning approaches to decode motor imagery (MI) tasks have significantly boosted the performance of brain-computer interfaces. Although recent studies have produced satisfactory results in decoding MI tasks of different body parts, the classification of such tasks within the same limb remains challenging due to the activ...
The synchronization phenomenon is common to many natural mechanical systems. Joint friction and damping in humans and animals are associated with energy dissipation. A coupled oscillator model is conventionally used to manage multiple joint torque generations to form a limit cycle in an energy dissipation system. The coupling term design and the fr...
Extracting motion information from videos is important for quantifying data from behavioral experiments to deepen the understanding of generation mechanisms of animal behavior. For insect walking, inter-leg coordination plays a crucial role, and the thorax-coxa (ThC) and femur-tibia (FTi) joint motions of six legs reflect the walking velocity and d...
Underwater snake robots have received attention because of their unique mechanics and locomotion patterns. Given their highly redundant degrees of freedom, designing an energy-efficient gait has been a main challenge for the long-term autonomy of underwater snake robots. We propose a gait design method for an underwater snake robot based on deep re...
A key problem in human balance recovery lies in understanding the mechanism of balance behavior with redundant bio-mechanical motors. Motor synergy has been known as an efficient tool to analyze characteristics of motion behavior and reconstruct control command. In this paper, motor synergy analysis for different control strategies is proposed to a...
In our aging world, the need to measure and evaluate motor and cognitive functions and to automate physical and occupational therapy will increase in the future. Many studies on VR-based rehabilitation systems are already underway. However, there are some issues such as the risk of falling or crashing due to the complete blockage of visual informat...
In recent years, markerless motion capture using a depth camera or RGB camera without any restriction on the subject has been attracting attention. Especially, depth cameras such as Kinect and RealSense allow instantaneous motion capture even at home outside lab environment, which is attractive for rehabilitation usage. However, single depth camera...
Multiple tasks are simultaneously performed during walking in our daily life. Distracted walk by smartphone usage is recently getting a social problem. The term dual-task gait refers to the secondary task added to the walking. Attention demanding tasks may influence how a person walks. Since in-lab measurement may not accurately reflect the daily l...
In the field of rehabilitation, there is a great demand for an automatic and quantitative evaluation system. The balance ability is an essential factor for motor function evaluation related to posture control. Although balance ability is assessed using various indices in current clinical situations, most of previous studies developing an automatic...
This paper proposes the augmentation of an L1 adaptive controller with a feedback Linear Quadratic Regulator (LQR) to control a wheel-legged biped robot. The performance of linearized model-based controllers, such as LQR, depends on the accurate knowledge of model parameters, a priori information about input and output disturbances, and other unfor...
This presentation deals with a new L1 adaptive controller combined with a feedback Linear Quadratic Regulator (LQR) to control a wheel-legged biped robot.
Humans can rapidly adapt to new situations, even though they have redundant degrees of freedom (d.f.). Previous studies in neuroscience revealed that human movements could be accounted for by low-dimensional control signals, known as motor synergies . Many studies have suggested that humans use the same repertories of motor synergies among similar...
[This corrects the article DOI: 10.1371/journal.pcbi.1009386.].
Electroencephalography (EEG) is the most prevalent signal acquisition technique for brain-computer interface (BCI). However, the statistical distribution of EEG data varies across subjects and sessions, resulting in poor generalization of the domain-specific classifier. Although the collection of a large number of recordings may alleviate this issu...
We present a hierarchical deep reinforcement learning (DRL) framework with prominent sampling efficiency and sim-to-real transfer ability for fast and safe navigation: the low-level DRL policy enables the robot to move towards the target position and keep a safe distance to obstacles simultaneously; the high-level DRL policy is supplemented to furt...
Snake-like robots are expected to be utilized for disaster rescue because they can locomote through gaps that humans cannot go through by appropriately coordinating the large degrees of freedom (DoFs) in their bodies. However, when learning locomotion using reinforcement learning (RL), an increase in learning time due to the large degrees of action...
In the field of motor control, ”Synergy Hypothesis” is a concept that behaviors are constructed by a combination of the patterns of movement called synergy. A large number of studies have supported this hypothesis as an explanation for redundant body control in humans and animals. Although much research has been done on the concept of synergy, the...
Clarification of how our brain and central nervous system (CNS) control the human body is important for further development of engineering fields and medical fields. Although it remains an open problem due to its complexity, there is a hypothesis that our CNS controls modules which handles tasks or dynamics by activating several muscles synergicall...
In the future, it is expected that robots will collaborate with humans. Such robots for collaborative works need to perform a variety of movements. Therefore, it is necessary to develop a system that can efficiently generate various movements from limited training datasets. To develop such a system, we focus on latent variables that represent featu...
One of the factors declining the function of a paretic limb of stroke patients in chronic stage is a learned nonuse phenomenon, learning the disuse of the paretic limb due to clumsiness in daily-life usage of it.Learned non-use causes ”negative” use-dependent plasticity in the brain, hence the brain area involved in motor control of the hemiplegic...
Among end-effector robots for lower limb rehabilitation, systems based on Stewart–Gough platforms enable independent movement of each foot in six degrees of freedom. Nevertheless, control strategies described in recent literature have not been able to fully explore the potential of such a mechatronic system. In this work, we propose two novel appro...
In this study, we proposed a framework for extracting gait events and extensive temporal features, seamlessly, during walking and running on a treadmill by constructing a finite state machine (FSM) transition rules based on two IMU sensors attached to the back of the shoes. Detailed innerclass states were defined to recognize the double support pha...
Quadruped system is an animal-like model which has long been analyzed in terms of energy efficiency during its various gait locomotion. The generation of certain gait modes on these systems has been achieved by classical controllers which demand highly specific domain-knowledge and empirical parameter tuning. In this paper, we propose to use deep r...
Recently, emerging technologies are being used to solve state of the art problems in rehabilitation and physiotherapy. The increasing power of portable sensors is making a great choice for analysis of movements during daily activities. We previously developed a method to personalize the measure of balance only using kinematic data from Kinect. This...
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 nat...