Mitsuhiro Hayashibe

Tohoku University | Tohokudai · Graduate School of Engineering

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...

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...

Distilling physical laws autonomously from data has been of great interest in many scientific areas. The sparse identification of nonlinear dynamics (SINDy) and its variations have been developed to extract the underlying governing equations from observation data. However, SINDy faces certain difficulties when the dynamics contain rational function...

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...

The current gold standard for gait analysis involves performing the gait experiments in a laboratory environment with a constrained space. However, there is growing interest in using flexible, efficient, and inexpensive wearable sensors as tools to perform gait analysis. This review aimed to identify and summarize the current advances in wearable s...

Transcranial direct current stimulation (tDCS) has been shown to evoke hemodynamics response; however, the mechanisms have not been investigated systematically using systems biology approaches. Our study presents a grey-box linear model that was developed from a physiologically detailed multi-compartmental neurovascular unit model consisting of the...

The state-of-the-art reinforcement learning (RL) techniques have made innumerable advancements in robot control, especially in combination with deep neural networks (DNNs), known as deep reinforcement learning (DRL). In this article, instead of reviewing the theoretical studies on RL, which were almost fully completed several decades ago, we summar...

Robotic devices with soft actuators have been developed to realize the effective rehabilitation of patients with motor paralysis by enabling soft and safe interaction. However, the control of such robots is challenging, especially owing to the difference in the individual deformability occurring in manual fabrication of soft actuators. Furthermore,...

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, limite...

To obtain biologically inspired robotic control, the architecture of central pattern generators (CPGs) has been extensively adopted to generate periodic patterns for locomotor control. This is attributed to the interesting properties of nonlinear oscillators. Although sensory feedback in CPGs is not necessary for the generation of patterns, it play...

A self-balancing wheel-legged robot provides higher maneuverability and mobility than legged biped robots. For this reason, wheel-legged systems have attracted enormous interest from academia and commercial sectors in recent years. Most of the past works in this field mainly focused on lower body stabilization. Motivated by the human ability to mai...

In the aging society, the number of people suffering from vascular disorders is rapidly increasing and has become a social problem. The death rate due to stroke, which is the second leading cause of global mortality, has increased by 40% in the last two decades. Stroke can also cause paralysis. Of late, brain-computer interfaces (BCIs) have been ga...

Full-dimensional natural arm manipulation is a challenging task in the field of model-based control due to its high degree of freedom and unknown dynamics of the given system. Deep reinforcement learning (DRL) offers a promising model-free approach for handling high-dimensional robotics problems. Although impressive results for the arm manipulation...

Background Tracking the whole body center of mass (CoM) trajectory of balance-impaired individuals with a personalized model is useful in the development of customized fall prevention strategies. A personalized CoM estimate can be obtained using the statically equivalent serial chain (SESC) method, but the subject has to perform an identification p...

In Deep Reinforcement Learning (DRL) for robotics application, it is important to find energy-efficient motions. For this purpose, a standard method is to set an action penalty in the reward to find the optimal motion considering the energy expenditure. This method is widely used for the simplicity of implementation. However, since the reward is a...

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) hi...

The rimless wheel is investigated as the most simplified model of passive dynamic walking. Previous researchers lay emphasis on the mechanical design of the passive rimless wheel. Controller design that enables adaptive locomotion to the environment has rarely been studied so far. This paper investigated whether the rimless wheel can realize both a...

The use of myoelectric control for prosthetic hand devices is very popular and many sophisticated prostheses have been developed, owing to the advancements in sensor and actuator technologies. However, for transhumeral amputees, EMG based control strategies still lack to provide intuitive solution as they need a prosthetic device with higher degree...

Because of the aging society with a declining birthrate, labor shortage for people who need rehabilitation is one of serious problems in Japan. On the rehabilitation site, physical therapists care patients one‐to‐one and determinate their conditions based on experience and memory. Therefore, we need to develop systems which evaluate automatically a...

This work presents a framework for the kinetics and kinematics estimation of the human knee joints in natural movements. In this study, we employed the long short-term memory (LSTM), a special recurrent neural network (RNN) architecture, as an estimation algorithm by using electromyography (EMG) features. The results suggest a potential application...

In this study, we investigated a control algorithm for a semi-active prosthetic knee based on reinforcement learning (RL). Model-free reinforcement Q-learning control with a reward shaping function was proposed as the voltage controller of a magnetorheological damper based on the prosthetic knee. The reward function was designed as a function of th...

Transcranial direct current stimulation (tDCS) has been shown to evoke hemodynamics response; however, the mechanisms have not been investigated systematically using systems biology approaches. We postulate that such a mechanistic understanding of the hemodynamics response, called cerebrovascular reactivity (CVR) to tDCS, can facilitate adequate de...

Transcranial direct current stimulation (tDCS) has been shown to evoke hemodynamics response; however, the mechanisms have not been investigated systematically using systems biology approaches. We postulate that such a mechanistic understanding of the hemodynamics response, called cerebrovascular reactivity (CVR) to tDCS, can facilitate adequate de...

The mechanism of action for the cerebral vasculature hemodynamic response to the electric field effects during transcranial direct current stimulation (tDCS) has been less explored. We postulate that such a mechanistic understanding of the cerebrovascular reactivity (CVR) to tDCS can facilitate adequate tDCS dosing to facilitate cognitive rehabilit...

Motor imagery (MI) tasks of different body parts have been successfully decoded by conventional classifiers, such as LDA and SVM. On the other hand, decoding MI tasks within the same limb is a challenging problem with these classifiers; however, it would provide more options to control robotic devices. This work proposes to improve the hand MI task...

The importance of gait analysis in medical applications, such as in rehabilitation, has been widely studied. Wearable sensors have gained popularity owing to their convenience of use in a flexible environment, while providing accuracy and reliability, in comparison with the gold standard system, i.e., motion capture. In this study, we proposed a fr...

The most common cause of injuries among older adults is falling. Recently, there have been numerous developments in assistive and exoskeleton systems. However, comparatively little work is being done on systems that may help people to keep an upright position and avoid falling over. In this preliminary work, we investigate the feasibility of the wh...

When we face a super-aging society, there is a drastically increased need for efficient systems in terms of time and cost that can improve rehabilitation standards for the elderly people and other motor-impaired subjects. Human balance ability depends largely on the control of the full body center of mass (CoM), fall risks can be evaluated by estim...

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...

The most common cause of injuries among older adults is falling. Recently, there have been numerous developments in assistive and exoskeleton systems. However, comparatively little work is being done on systems that may help people to keep an upright position and avoid falling over. In this preliminary work, we investigate the feasibility of the wh...

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 experimental data. In contrast to neural-network-based methods, these methods are designed to obtain white-box analyt...

As human motor learning is hypothesized to use the motor synergy concept, we investigate if this concept could also be observed in deep reinforcement learning for robotics. From this point of view, we carried out a joint-space synergy analysis on multi-joint running agents in simulated environments trained using two state-of-the-art deep reinforcem...

Japan is facing the problem of super aging society and the necessity of assistive system for the elderly has increased. In order to decrease the human resource and cost, we need to develop the technology to predict and support human motion. Conventional motion prediction system uses force plate or motion capture but these system is limited by the e...

Synchronization is one of most significant phenomena observed in the collective behavior of coupled oscillators such as nervous system. Although some researches have been conducted thus far for understanding the theoretical aspects of the dynamics in coupled oscillators systems, few studies have tried to predict and control the synchronization in t...

Brain-computer Interfaces (BCI) and Functional electrical stimulation (FES) contribute significantly to induce cortical learning and to elicit peripheral neuronal activation processes and thus, are highly effective to promote motor recovery. This study aims at understanding the effect of FES as a neural feedback and its influence on the learning pr...

Functional connectivity of cognitive tasks allows researchers to analyse the interaction mapping occurring between different regions of the brain using electroencephalography (EEG) signals. Standard practice in functional connectivity involve studying the electrode pair interactions across several trials. As the cognitive task always involves the h...

Muscle synergies, which is the concept of modular activation of a set of muscles for producing complex motor behaviors, have been studied for a long time. Several definitions of muscle synergies have been proposed, and different algorithms have identified synergies in a large number of contexts. However, most of the studies so far used the dataset...

Differentiating muscle fatigue induced hand tremor of surgeons into different discernible levels is important in laparoscopic surgery. Systematic clustering can be used as a method to assess the risk of hand tremor which can largely affect the surgical performance. The prime challenges lying here are the detection of fatigue onset and classificatio...