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Traditional evaluations of handwriting assistive devices have primarily relied on user satisfaction surveys. While recent advancements in computer technologies and digital devices have enabled more objective evaluations, these methods often lack comprehensiveness. This study introduces a scientific and systematic evaluation method for evaluating handwriting assistive devices used by individuals with upper limb dysfunction. The proposed method incorporates both writing and drawing tasks, utilizing advanced computer technology and sophisticated sensors in tablets and digital pens to measure key handwriting parameters across ten indicators. These indicators are synthesized into a comprehensive score using the entropy weight method (EWM). Additionally, objective scores were compared with subjective evaluations from participants. A strong positive correlation between objective and subjective evaluations confirms the reliability of our objective method. However, statistical analysis revealed a significant mean difference between the two scoring methods, indicating that the objective method provides a more standardized and quantifiable evaluation, effectively minimizing the influence of personal biases inherent in subjective evaluations. This comprehensive evaluation method not only offers a holistic evaluation of handwriting assistive devices but also addresses the limitations of existing objective methods that tend to focus on singular aspects of performance.

The global demand for assistive devices to support individuals with disabilities is increasing, yet their accessibility remains limited. Self-help devices (SHDs), particularly for handwriting tasks, play a pivotal role in enhancing independence. This study presents a semi-automated method for producing personalized handwriting SHDs, thereby reducing the need for occupational therapists (OTs) to possess advanced technical skills and enabling them to concentrate on patient care. Ten healthy participants, simulating upper limb dysfunctions by restricting their finger joint mobility with bandages, are recruited for the study. OTs assess measurements that encompass manual measurements, automatic joint recognition, and 3D scanning for digital representation. This process facilitates the development of a personalized SHD 3D model, utilizing 3D CAD software. The SHD model is designed to be adaptable, allowing adjustments based on the individual's unique hand measurements. The 3D model, composed of six primary components, is then fabricated using 3D printing technology. The streamlined process, from measurement to production, reduces design and printing time to approximately two hours. Testing focuses on handwriting speed and letter legibility, with participants reporting enhanced comfort and a significant increase in handwriting speed using our SHD compared to conventional SHDs. Furthermore, users experienced improved letter legibility in addition to a significant increase in handwriting speed with our SHD. The study's innovation promises to broaden the reach of personalized assistive devices and allows OTs to better focus on patient care, improving therapy outcomes.

Recent advancements in motion measurement systems have facilitated the analysis of kinematic techniques in sports, emphasizing the importance of motion control for performance enhancement. Ground reaction forces and moments are crucial in biomechanical analysis, and are typically measured using force plates. However, conventional force plates pose limitations in winter sports due to their impracticality on ice. To address this, various methods have been explored, including skates equipped with strain gauges and pressure-sensitive insoles. Despite advancements, simultaneous measurement of forces and moments in three axes remains a challenge. In this study, we developed a new wearable system capable of comprehensively measuring the forces and moments during skating by attaching three wearable force plates between the boot and the blade. The precision of this measurement system was validated through an experiment employing a conventional force plate, demonstrating its high accuracy. On-ice trials confirmed the system's efficacy in capturing dynamic movements like forward sliding and half-turn jumps. The six-component force was successfully measured during skating motions, a task that is challenging with conventional systems. This system offers a promising avenue for nuanced biomechanical analysis in figure skating, facilitating insights into performance optimization and injury prevention.

Abstract Excessive hip flexion torque to prioritize leg swings in the elderly is likely to be a factor that reduces their propulsive force and gait stability, but the mechanism is not clear. To understand the mechanism, we investigated how propulsive force, hip flexion torque, and margin of stability (MoS) change when only the hip spring stiffness is increased without changing the walking speed in the simple walking model, and verified whether the relationship holds in human walking. The results showed that at walking speeds between 0.50 and 1.75 m/s, increasing hip spring stiffness increased hip flexion torque and decreased the propulsive force and MoS in both the model and human walking. Furthermore, it was found that the increase in hip flexion torque was explained by the increase in spring stiffness, and the decreases in the propulsive force and MoS were explained by the increase in step frequency associated with the increase in spring stiffness. Therefore, the increase in hip flexion torque likely decreased the propulsive force and MoS, and this mechanism was explained by the intervening hip spring stiffness. Our findings may help in the control design of walking assistance devices, and in improving our understanding of elderly walking strategies.

Forward dynamics simulations can significantly reduce the development costs associated with new wearable assistive devices by minimizing the need for prototyping and experimentation. However, current model-based methods rely on experimental data to define the model posture for the simulation, making it challenging to design the wearer's posture suitable for reducing physical load with passive lower-limb assistive devices. To address this challenge, this study proposes a forward dynamics simulation method that focuses on optimizing physical posture. This simulation approach calculates human-device interactions, including reaction forces, physical posture, and physical load, based on the physical posture optimized by a cost function that evaluates both the physical load and the suitability of the posture for work, which contributes to estimating the impact of the device on the physical load of the wearer. To investigate the validation and advantage of the proposed simulation, this study compared the simulation and experimental results for existing and new passive lower-limb assistive devices. The results show that although the proposed method did not accurately simulate the individual human-device interactions for a given participant using the passive lower-limb assistive device, it accurately estimated the average reaction forces and lower limb posture across all participants. Additionally, the proposed method correctly represented the differences in reaction forces and lower limb posture resulting from changes in device structure. Consequently, the proposed simulation has advantages in computationally evaluating the device’s performance in reducing the lower limb loads and contributes to the development of effective assistive devices for preventing musculoskeletal disorders.

Predicting the ground reaction force (GRF) and ground reaction moment (GRM) with a biomechanical model-based approach has an advantage for biomechanical gait analysis in situations where a statistical model cannot be used due to a lack of training data. However, the current prediction methods using a biomechanical model have some issues for clinical application. The present study developed a new inertial measurement unit (IMU)-based method to predict the GRF, the GRM, and the joint kinematics and kinetics with a 3D biomechanical model and simple system. The present method predicts them using a 3D forward dynamics model that computationally generates human movements that minimize the hybrid cost function defined by physical loads and errors between the motion of the model and that of the participants recorded by six IMUs, which allows the prediction system to use only a relatively small number of IMUs. We investigated the prediction accuracy during walking by comparing the new method with a conventional analysis using a force plate and motion capture system. As a result, we observed strong and excellent correlations between the prediction and measurement of the anterior GRF, vertical GRF, sagittal GRM, hip flexion angle, knee flexion angle, hip flexion torque, and ankle dorsiflexion torque. Considering the accuracy of previous studies and that required for gait analysis, the present method could predict them with practical accuracy due to estimated biomechanically valid motions based on optimization using the hybrid cost function that includes a biomechanical evaluation. Moreover, the prediction system has an advantage for clinical applications because the present method observed practical accuracy that has the potential to be applied to some sports analysis and can analyze 3D motion with a simple system consisting of a small number of hardware components and a software.

Rotational jumps are crucial techniques in sports competitions. Estimating ground reaction forces (GRFs), a constituting component of jumps, through a biomechanical model-based approach allows for analysis, even in environments where force plates or machine learning training data would be impossible. In this study, rotational jump movements involving twists on land were measured using inertial measurement units (IMUs), and GRFs and body loads were estimated using a 3D forward dynamics model. Our forward dynamics and optimization calculation-based estimation method generated and optimized body movements using cost functions defined by motion measurements and internal body loads. To reduce the influence of dynamic acceleration in the optimization calculation, we estimated the 3D orientation using sensor fusion, comprising acceleration and angular velocity data from IMUs and an extended Kalman filter. As a result, by generating cost function-based movements, we could calculate biomechanically valid GRFs while following the measured movements, even if not all joints were covered by IMUs. The estimation approach we developed in this study allows for measurement condition- or training data-independent 3D motion analysis.

The biomechanical-model-based approach with a contact model offers advantages in estimating ground reaction forces (GRFs) and ground reaction moments (GRMs), as it does not rely on the need for training data and gait assumptions. However, this approach faces the challenge of long computational times due to the inclusion of optimization processes. To address this challenge, the present study developed a new optical motion capture (OMC)-based method to estimate GRFs, GRMs, and joint torques without prolonged computational times. The proposed approach performs the estimation process by distributing external forces, as determined by a multibody model, between the left and right feet based on foot deformations, thereby predicting the GRFs and GRMs without relying on optimization techniques. In this study, prediction accuracies during level walking were confirmed by comparing a general analysis using a force plate with the estimation results. The comparison revealed excellent or strong correlations between the prediction and the measurements for all GRFs, GRMs, and lower-limb-joint torques. The proposed method, which provides practical estimation with low computational cost, facilitates efficient biomechanical analysis and rapid feedback of analysis results, contributing to its increased applicability in clinical settings.

In the era of expanding manned space missions, understanding the biomechanical impacts of zero gravity on human movement is pivotal. This study introduces a novel and cost-effective framework that demonstrates the application of Microsoft’s Azure Kinect body tracking technology as a motion input generator for subsequent OpenSim simulations in weightlessness. Testing rotations, locomotion, coordination, and martial arts movements, we validate the results’ realism under the constraints of angular and linear momentum conservation. While complex, full-body coordination tasks face limitations in a zero gravity environment, our findings suggest possible approaches to device-free exercise routines for astronauts and reveal insights into the feasibility of hand-to-hand combat in space. However, some challenges remain in distinguishing zero gravity effects in the simulations from discrepancies in the captured motion input or forward dynamics calculations, making a comprehensive validation difficult. The paper concludes by highlighting the framework’s practical potential for the future of space mission planning and related research endeavors, while also providing recommendations for further refinement.

A passive lower-limb assistive device that supports standing work has been developed to reduce lower limb loads in workers. The device effectively prevents lower limb musculoskeletal disorders such as osteoarthritis and contributes to the improvement of occupational health. However, previous studies have not clarified lumbar load when wearing the device. The present study investigated the effect of a passive lower-limb assistive device on lumbar load and verified the effectiveness of biomechanical analysis for evaluating the physical load while wearing the device. Twelve healthy male participants performed an assembly task under three conditions: standing and high and low sitting while wearing the device. We mainly analyzed the joint torque and joint compression force (JCF) computed using a full-body musculoskeletal model based on measurements obtained from a motion capture system and force platform. The present study concluded that the lumbar load increased when wearing the device because the lumbar joint torque was significantly larger than that for standing. In addition, the biomechanical analysis has the advantage of evaluating the lumbar load when wearing the device because the current method of analyzing muscular activity is not able to evaluate the lumbar load including the effects of passive resistance, such as those generated by ligament force and abdominal pressure. Furthermore, the present method is able to simultaneously investigate physical loads in the lower limb and neck joint based on the analysis of the JCFs in the lower limb and the neck joint torque, which is effective as an analytical method for the effect of the passive lower-limb assistive device on the risk of musculoskeletal disorders.

Previous studies have demonstrated that the central nervous system activates muscles in module patterns to reduce the complexity needed to control each muscle while producing a movement, which is referred to as muscle synergy. In previous musculoskeletal modeling-based muscle synergy analysis studies, as a result of simplification of the joints, a conventional rigid-body link musculoskeletal model failed to represent the physiological interactions of muscle activation and joint kinematics. However, the interaction between the muscle level and joint level that exists in vivo is an important relationship that influences the biomechanics and neurophysiology of the musculoskeletal system. In the present, a lower limb musculoskeletal model coupling a detailed representation of a joint including complex contact behavior and material representations was used for muscle synergy analysis using a decomposition method of non-negative matrix factorization (NMF). The complexity of the representation of a joint in a musculoskeletal system allows for the investigation of the physiological interactions in vivo on the musculoskeletal system, thereby facilitating the decomposition of the muscle synergy. Results indicated that, the activities of the 20 muscles on the lower limb during the stance phase of gait could be controlled by three muscle synergies, and total variance accounted for by synergies was 86.42%. The characterization of muscle synergy and musculoskeletal biomechanics is consistent with the results, thus explaining the formational mechanism of lower limb motions during gait through the reduction of the dimensions of control issues by muscle synergy and the central nervous system.

The biomechanical variation in the knee during walking that accompanies medial meniscal radial tears stemming from knee osteoarthritis (OA) has not been explored. This study introduced a finite element musculoskeletal model using concurrent lower limb musculoskeletal dynamics and knee joint finite element analysis in a single framework and expanded the models to include knees with medial meniscal radial tears and total medial meniscectomy. The radial tears involved three locations: anterior horn, midbody, and posterior horn with grades of 33%, 50%, and 83% of the meniscus width. The shear and hoop stresses of the tear meniscus and tibial cartilage contact load, accompanying tears, and postmeniscectomy were evaluated during the stance phase of the gait cycle using the models. In the 83% width midbody tear group, shear stress at the end of the tear was significantly greater than in the intact meniscus and other tear groups, and the maximum shear stress was increased by 310% compared to the intact meniscus. A medial meniscus radial tear has a much smaller effect on the tibial cartilage load (even though in the 83% width tear, the cartilage/total load ratio increased by only 9%). However, the contact force on the tibial cartilage with total postmeniscectomy was increased by 178.93% compared with a healthy intact meniscus, and the peak contact pressure after meniscectomy increased from 11.94 to 12.45 MPa to 17.64 and 13.76 MPa, at the maximum weight acceptance and push-off, respectively. Our study shows that radial tears with larger medial meniscus widths are prone to high stress concentrations at the end of the tears, leading to the potential risk of complete meniscal rupture. Furthermore, although the tears did not change the cartilage load distribution, they disrupted the circumferential stress-transmitting function of the meniscus, thus greatly increasing the likelihood of the onset of knee OA. The significant increase in the tibial cartilage load with total postmeniscectomy indicates a potential risk of OA flare-ups. This study contributes to a better understanding of meniscal tear-induced OA biomechanical changes during human activities and offers some potential directions for surgical guidance of meniscectomies and the prophylaxis and treatment of OA.

This study as primary research to propose a non-invasive technique to diagnose the Outerbridge grade of cartilage damage by impact signals. A knee model was experimented with the novel attempt instead of a real knee. The knee model is made by a 3D model converted from magnetic resonance images (MRI) and then assembled by true scale and position. The impact signal is input from the calf and output from the thigh, and the absorption of the impact signal is contended differently by different Outerbridge grades of cartilage. The absorbed impact signals collected by sensors were time-frequency analyzed by continuous Gabor transform (CGT). In addition, the absorbed jerk signal is interpreted by the singular spectrum analysis (SSA) for its oscillation components. The analysis of the signals in this study found that the features derived have abilities to distinguish Outerbridge classification. Therefore, the proposed method can be considered for carrying the experiment onto real knees. This study provides a novel idea to make the diagnostic technique of cartilage damage efficient. Combined with the feature engineering and classification technique, it will help in the clinical diagnosis of knees, this study expects that the method can be applied not only to the diagnosis of the overall knee, but also that the method can diagnose more tiny areas in the early stages of the knee disorder.

Cerebral palsy (CP) causes abnormal gait pattern due to increased stretch reflex and contracture in specific muscles. Increased stretch reflexes in CP are caused by increased activation of muscle spindles due to increased sensitivity of gamma motor neurons. Furthermore, these neurological abnormalities may cause abnormal postures such as crouching and scissoring. This study aimed to construct a system for supporting treatment and orthosis development in patients with CP by simulation using a three-dimensional neuromuscular skeleton model and evaluate the validity of motor function due to CP reproduced by gait simulation. By reproducing motor function due to CP, the simulation system was able to obtain gait and muscle activity patterns similar to the actual ones. Therefore, motor function in CP can be quantitatively evaluated using this simulation system. In the model of children with CP, gait factors and joint angles of hip, knee, and ankle resembled those of the experimental results; however, the results of muscle synergy analysis were different. Hence, although gait pattern might be highly involved in the enhancement of stretch reflex and muscle contraction, muscle interaction and single muscles influence muscle control in CP.

This study describes a new calibration procedure that provides a simple and accurate method to place and align an inertial measurement unit (IMU) sensor with the relative clinical bone frame on a developed lower limb skeletal model. The calibration can be easily replicated without the need for additional tools and, more importantly, it is independent of the joint attachment position. The proposed method was validated under realistic gait tests using eight healthy subjects in a motion capture system environment. Calculated results showed that the joint angles were correctly measured after applying the calibration method. Therefore, the proposed calibration procedure is an interesting alternative to solve the alignment problem when using IMU sensors for gait analysis.

The early-stage of knee osteoarthritis (OA) is usually asymptomatic. However, timely detection of osteoarthritis can prevent further cartilage degeneration via appropriate exercise prescription and behavioral change. In this article, a noninvasive method to diagnose the OA of a knee recording the knee vibroarthrographic (VAG) signals over the mid-patella during the standing movement is proposed. A method that combines empirical mode decomposition (EMD) and wavelet transform is developed to analyze the nonstationary VAG signals. The least squares support vector machine algorithm (LSSVM) that is a type of support vector machine is used to classify the knee joint VAG signals (26 normal and 25 abnormal) collected from healthy subjects and patients suffering from the knee OA using the Kellgren and Lawrence grading system III and IV (KLGS III and IV). The LSSVM classifier achieves an accuracy of 86.67% in differentiating the normal and abnormal subjects that proves the effectiveness of the autocorrelation function features and continuous wavelet transform (CWT) features. Therefore, the VAG signals can be clinically significant for the classification of healthy and OA subjects.

With the growing demand from elderly persons for alternative mobility solutions, motorized mobility scooters (MMSs) have been gaining importance as an essential assistive technology to aid independent living in local communities. The increased use of MMSs, however, has raised safety issues during driving and magnified the necessity to evaluate and improve user driving skills. This study is intended to develop a novel quantitative monitoring method for MMS driving operation using inertial measurement units (IMUs). The proposed method used coordinate transformations around the rotational axes of the steering wheel and the throttle lever to estimate the steering and throttle operating angles based on gravitational accelerations measured by IMUs. Consequently, these operating angles can be monitored simply using an IMU attached to the throttle lever. Validation experiments with a test MMS in the stationary state confirmed the consistency of the proposed coordinate transformation with the MMS’s geometrical structure. The driving test also demonstrated that the operating angles were estimated correctly on various terrains and that the effects of terrain inclination were compensated using an additional IMU attached to the scooter body. This method will be applicable to the quantitative monitoring of driving behavior and act as a complementary tool for the existing skills’ evaluation methods.

Sports prosthesis for lower-extremity amputees has a mechanical structure similar to flat springs, and its elastic energy is expected to improve sports performance. However, it is quite challenging to represent the mechanical phenomena during the takeoff action with sports prosthesis because the contact point to the ground moves based on the direction and deformation of the prosthesis. The purpose of this study is to propose a parametric model of sports prosthesis based on the flat spring design formulas to represent the deformation and rolling contact with the ground with a reasonable computational cost. The shape of the prosthesis is modeled as serial elements, and it can easily be changed by using design parameters, such as the curvature and length of each element. The curvature of each element of the prosthesis is modified by the deflection angle of the flat spring model, and the contact point to the ground is calculated by considering the deformation and rolling contact. The spring properties obtained from the proposed model well agreed with the result of a finite element analysis. Moreover, simulation results revealed that the deformed shape of the prosthesis and the takeoff action in the long jump qualitatively agreed with the actual phenomena. As future research, the proposed model, coupled with the human body model, will be applied to a computer simulation system to optimize the shape of the prosthesis in order to improve sports performance.

The frame stiffness in a racing bicycle might influence not only toughness as the frame structure but also performance of an athlete. The purpose of this study is to clarify biodynamic relations between the frame stiffness in a racing bicycle and the physical loads of an athlete by using a forward dynamics simulation model. The human body structure was represented by the 13-rigid-links and 23-degrees-of-freedom model. Based on the theory of multibody dynamics, the frame structure was expressed by combination of 12 rigid pipes, and the frame stiffness was modeled by rotational springs at the connecting joint between the rigid pipes. Spring coefficients were changed according to the thickness of the frame pipes. The pedaling load from the crank was computed by the angular velocity and angular acceleration of the crank. Moreover, the driving force in the bicycle was additionally defined to consider the influence of the frame weight on the human joint load. The human body model was driven by the joint toques to minimize the cost function consisting of the joint loads in the human body and the driving force in the bicycle, and also to keep desired angular velocity of the crank. Validity of the simulation was evaluated by comparing the joint angles and torques with the measured ones. As for the result, the larger stiffness of the frame resulted in smaller the joint loads in the human body, and optimal stiffness would be determined by the balance between the joint loads in the human body and the driving force in the bicycle.

Recently, in vehicle development, consideration of the human passenger/driver has become increasingly important. In the present study, numerical simulation of human-body dynamics for a human in a vehicle was conducted. Generally, humans are simulated using whole-body models during numerical simulation. However, the whole-body model has multiple degrees of freedom and multiple properties that must be considered. Moreover, the influence of parameters of the human body is uncertain, and it is difficult to accurately set these parameters. Therefore, we herein focus on motion control of the human head and trunk because these parts account for a large portion of the overall human body. A simplified human model that can identify the characteristics of motion control for actual human response was proposed. In the present paper, the parameters of this human motion control are identified based on results obtained experimentally and using a simulation model. The characteristics of motion of an individual human are then considered based on the obtained characteristics of the parameters.

This study aims to create a system that can be used to evaluate vehicle characteristics while simultaneously controlling human body behavior through numerical simulations. The proposed system consists of a vehicle model, a human body dynamics model, and a musculoskeletal model. In the present paper, a human body dynamics model using multibody dynamics is proposed. However, attempting to implement a whole-body model would necessitate dealing with multiple degrees of freedom and give rise to problematic phenomena. Furthermore, the influences of human motion are uncertain and difficult to parameterize. Accordingly, in the present research, the human model is limited to the head and trunk of a human body riding inside a vehicle. This human body dynamics model is composed of an internal model and an external model. The internal model incorporates a motion control model. The internal model, which is composed of an inverse model and a forward model, generates commands to control body motion, while the external model simulates the actual body motion. Then, in order to identify the parameters of the motion control model, the motion of maintaining posture is measured using a simple experimental device that can simulate horizontal acceleration applied to a subject. In order to demonstrate the effectiveness of the proposed human body dynamics model, a simple human dummy model (which simulates the experimental model used for experiments such as automobile collisions) that consists of only a spring and a damper was created. Comparing this dummy model with the human body dynamics model reveals that the human body dynamics model can simulate details of human motion that the simple dummy model cannot.

In this paper, we analyze the influence of dynamical characteristics of man-machine interfaces on both impedance perception levels and motor control characteristics of humans. In order to estimate dynamical characteristics of man-machine interfaces, humans make use of the coupling characteristics between sensory systems and motor systems in their bodies. In this study, we propose a new model-based estimation method of impedance perception level of related with motor control characteristics of the body. For the experiment, we used a 6 degree-of-freedom manipulator to simulate different impedances. A dual task was imposed on the subjects along with measuring dynamic characteristics of human who are operating the manipulator, where subjects were asked to perform simultaneously an upper limb tracking task and an impedance perception task. Based on the experimental results that show proportional relation between the differences of impedance perception levels and changes of the gain characteristics of the motor control transfer function model, the power spectrum density of the developed human model can be applied for on-line estimation of the impedance perception level of human in man-machine interface. The effectiveness of the proposed method is verified through comparison with subjective evaluation results.

We propose a method for the comprehensive identification of spastic and intrinsic properties of spastic knee joints using multiple pendulum tests. The stretch reflex system was modeled as a velocity feedback loop where the key component was the muscle spindle model generating the afferent signals with a constant threshold and gain of the lengthening velocity. For the comprehensive identification, multiple trajectories from one session of pendulum trials with different release angles were used as the reference trajectories that the model must reproduce. The identification was successful based on the results that the identified model represented the various features of pendulum trajectories and the simulated spastic torque closely matched the experimental EMG. The identified velocity threshold showed a remarkable correlation with the EMG duration and peak. The session-based method was effective in the identification of the spastic musculoskeletal system and the velocity threshold of the stretch reflex was suggested as a reliable and intuitive indicator of spastic severity.

Recently, in the human-centered design of the car seat, mutual interactive relationship based on structural dynamics of the human-machine system has been analyzed, and this technique is used to the methodology for the automobile design. However, these topics have been studied for only vibration measurement in a steady state and studies to analyze human body behavior in practical lateral-directional transient acceleration have not been performed yet. The purpose of this study is to simulate biomechanical body behavior of vehicle occupant in lateral-directional transient acceleration. The proposed experimental device has characteristics of low cost and simplicity of use. The used experimental device is composed of the carriage, the car seat, rubber band, cushion, motion capture system and mobile force plate. In this paper, the seated body behavior with lateral-directional acceleration is simulated. Moreover, each joint angle and each ground reaction moment through the experiments are calculated and quantitatively evaluated by using this experimental device and singular value decomposition. As results of the experiments, each movement pattern reflected by lateral-directional transient acceleration is obtained as the remarkable feature quantities because the influences of the characteristic lateral-directional behavior on the human body are shown. Finally, the effectiveness of the proposed measurement technique and method to analyze the biomechanical behavior of vehicle occupant during lateral-directional transient motion and its quantitative evaluation based on singular value decomposition are validated.

Walking is the human basic moving pattern and the elementary motion for human health promotion. In case of trying various measures as the moving pattern for human health promotion, the most traditional moving pattern called Nanba walking based on the biomechanics of the human body has been put into practical use. It has been thought that Nanba walking is actively focused because it is very useful for Japanese classic culture and there are many experimental discussions about Nanba walking. However, quantitative analysis of this walking pattern based on biomechanical data has not been inadequate. On the other hand, experimental study has been harder because of the difficult problem of facility. The purpose of this study are to generate Nanba walking by numerical simulation using three dimensional full human body simulation model as neuro-musculo-skeletal system including precise foot segment model developed in the past study and analyze the difference between Nanba walking and normal walking. As a result of simulation, Nanba walking was generated in order to change the feedback equation of neural oscillators. In simulation, walking characteristics such as locomotive speed and locomotive energy efficiency were optimized according to walking pattern respectively. As a conclusion of this study, it is validated as the effectiveness of Nanba walking that Nanba walking is suitable for faster locomotive speed because walking stability is also high in the single support phase by a little rotation of the upper body.

Neuro-musculo-skeletal model has been developed that is capable of generating reasonable gait. However, the details of the ground reaction force waveform differ from real gait motion quantitatively. A whole-body walking model including the detailed foot model has not been proposed and a unified objective function has not been proposed. Therefore, the purposes of this study are to improve a forward dynamic walking simulation by developing a precise foot model and making a hybrid criterion for the generation of human gait motion by using the application and utilization of genetic algorithm for the optimized calculation. The dynamics of the human body has been represented by 22 three-dimensional rigid links with 78 muscles and 62 neural oscillators. Unknown neuronal parameters have been adjusted by a numerical search method using the evaluative criterion for locomotion that is defined by the locomotive energy efficiency, the toe clearance and the magnitude of the ground reaction force. As a result of adjustment of the neuronal parameters, walking 10 steps has been generated. The simulated walking pattern has closely agreed with actual human walking not only of joint movement but also of the mutual conversion of the mechanical energy and the magnitude of the ground reaction force.

The work of fitting ceiling boards is one of the hardest in carpentry, as it requires large muscular power. Hence there is a need to develop assisting apparatus for such work. In order to use this apparatus anywhere a wearable robot is the most suitable. As the robot must be autonomous and lightweight, a design requiring low power is proposed. A semi-active control method has been developed using springs, which requires low energy but satisfies the requirements of compliance and assistive force. In this paper several aspects of design, control and experiments of the developed prototype is explained. The experimental results prove that the robot reduces the muscular fatigue of carpentry worker by providing suitable assistive force.

Wire rope and pulley devices are used in various machines. To use these machines more safely, it is necessary to analyze the behavior of the contact between them. In this study, we represent a wire rope by a numerical model of a flexible body. This flexible body is expressed in the absolute nodal coordinate formulation (ANCF), and the model includes the normal contact force and the frictional force between the wire rope and the pulley. The normal contact force is expressed by spring-damper elements, and the frictional force is expressed by the Quinn method. The advantage of the Quinn method is that it reduces the numerical problems associated with the discontinuities in Coulomb friction at zero velocity. By using the numerical model, simulations are performed, and the validity of this model is shown by comparing its results with those of an experiment. Through numerical simulations, we confirm the proposed model for the contact between the wire rope and the pulley. We confirmed that the behavior of the wire rope changes when both the bending elastic modulus of the wire rope and the mass added to each end of the wire rope are changed.

The work of fitting ceiling boards is one of the hardest in carpentry, as it requires large muscular power. Hence there is a need to develop assisting apparatus for such work. In order to use this apparatus anywhere a wearable robot is the most suitable. As the robot must be autonomous and lightweight, a design requiring low power is proposed. A semi-active control method has been developed using springs, which requires low energy but satisfies the requirements of compliance and assistive force. In this paper several aspects of design, control and experiments of the developed prototype is explained. The experimental results prove that the robot reduces the muscular fatigue of carpentry worker by providing suitable assistive force.

In the era of expanding manned space missions, understanding the biomechanical impacts of zero gravity on human movement is pivotal. This study introduces a novel and cost-effective framework that demonstrates the application of Microsoft’s Azure Kinect body tracking technology as a motion input generator for subsequent OpenSim simulations in weightlessness. Testing rotations, locomotion, coordination, and martial arts movements, we validate the results’ realism under the constraints of angular and linear momentum conservation. While complex, full-body coordination tasks face limitations in a zero gravity environment, our findings suggest possible approaches to device-free exercise routines for astronauts and reveal insights into the feasibility of hand-to-hand combat in space. However, some challenges remain in distinguishing zero gravity effects in the simulations from discrepancies in the captured motion input or forward dynamics calculations, making a comprehensive validation difficult. The paper concludes by highlighting the framework’s practical potential for the future of space mission planning and related research endeavors, while also providing recommendations for further refinement. [ABSTRACT FROM AUTHOR]