Real-time musculoskeletal visualization of muscle tension and joint reaction forces

International audienceThis paper presents a novel software that visualizes the physical burden of human body during movements. Its main objective is to support factory workers by monitoring the risk of physical health problems like low back pains. To achieve the goal, the software utilizes wearable sensors like IMUs to realize the measurement at a work-site. Several physical information like joint angles, joint torques, muscle tensions, joint reaction forces can be obtained by real-time musculoskeletal computation. The musculoskeletal information can be plotted and recorded by the visualization interface which is integrated to an ergonomic assessment software DhaibaWorks

Musculoskeletal Estimation Using Inertial Measurement Units and Single Video Image

International audienceWe address the problem of estimating the physical burden of a human body. This translates to monitor and estimate muscle tension and joint reaction forces of a mus-culoskeletal model in real-time. The system should minimize the discomfort generating by any sensors that needs to be fixed on the user. Our system combines a 3D pose estimation from vision and IMU sensors. We aim to minimize the number of IMU fixed to the subject while compensating the remaining lack of information with vision

Identification of Flying Humanoids and Humans

Abstract-The mass properties are important to control robot dynamics or study human dynamics. In our previous works, we proposed a method to identify inertial parameters of legged mechanisms from base-link dynamics, using generalized coordinates and external forces information. In this paper, we propose an identification method based on floating-base dynamics, when the system has no external force. Inertial parameters can be identified without force measurement, only from motion data. The method has been tested on two examples; a simple chain consisted of two links and the human body dynamics

AN EVALUATION OF PERFORMANCE OF A DOUBLE-LEG CIRCLE ON A POMMEL HORSE, AND A DESIRABLE PERFOMANCE PROPOSAL

For the evaluation of the performance of a double-leg circle on a pommel horse, we focused on the relation between the horizontal rotation of a body about the vertical axis in the center of a pommel horse and the hip rotation about the longitudinal axis of a body. Several gymnasts having different levels of skill were examined by using a motion capture system. The analysis shows that the horizontal rotation and the hip rotation are in good synchronization for the performance of a well-trained gymnast

Modeling and Identification of a Realistic Spiking Neural Network and Musculoskeletal Model of the Human Arm, and an Application to the Stretch Reflex

This study develops a multi-level neuromuscular model consisting of topological pools of spiking motor, sensory and interneurons controlling a bi-muscular model of the human arm. The spiking output of motor neuron pools were used to drive muscle actions and skeletal movement via neuromuscular junctions. Feedback information from muscle spindles were relayed via monosynaptic excitatory and disynaptic inhibitory connections, to simulate spinal afferent pathways. Subject-specific model parameters were identified from human experiments by using inverse dynamics computations and optimization methods. The identified neuromuscular model was used to simulate the biceps stretch reflex and the results were compared to an independent dataset. The proposed model was able to track the recorded data and produce dynamically consistent neural spiking patterns, muscle forces and movement kinematics under varying conditions of external forces and co-contraction levels. This additional layer of detail in neuromuscular models has important relevance to the research communities of rehabilitation and clinical movement analysis by providing a mathematical approach to studying neuromuscular pathology

New evaluation framework for human-assistive devices based on humanoid robotics

This paper presents the new application of a humanoid robot as an evaluator of human-assistive devices. The reliable and objective evaluation framework for assistive devices is necessary for making industrial standards in order that those devices are used in various applications. In this framework, we utilize a recent humanoid robot with its high similarity to humans, human motion retargeting techniques to a humanoid robot, and identification techniques of robot's mechanical properties. We also show two approaches to estimate supporting torques from the sensor data, which can be used properly according to the situations. With the general formulation of the wire-driven multi-body system, the supporting torque of passive assistive devices is also formulated. We evaluate a passive assistive wear 'Smart Suit Lite (SSL)' as an example of device, and use HRP-4 as the humanoid platform

Muscle strength and Mass Distribution Identification toward subject-specific musculoskeletal modeling

International audienceIn 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

États-Unis" Muscle Strength and Mass Distribution Identification Toward Subject-Specific Musculoskeletal Modeling

Abstract — 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. A. Background I

Experimental Study for Controller-Friendly Contact Estimation for Humanoid Robot

International audienceIn this paper, we introduce a practical contact observer which allows detecting a contact on the body surface of a humanoid robot. Our method estimates the error force due to undesired contact. Then, contact detection (yes/no) is performed together with the estimation of the contact force and location. By comparing the real robot state according to sensory data with the desired state computed from the contact-free dynamics equation, we can estimate the external force applied to an unknown link. The link in contact is then detected by tracing the torque error along the robot's kinematic chain. Once the link in contact is determined, we can estimate the point where the contact force was applied by using the 3D geometric mesh model of a robot. The proposed method is validated through simulation and experiments using the humanoid robot HRP-4