A Synthesis of Bipedal Locomotion in Human and Robots

This report is the result of a joint reflection carried out by researchers from automatic control and neuroscience fields, both trying to answer a same question: what are the functional basis of bipedal locomotion and how to control them? The originality of this work is to put in parallel two synthesis of how the problem of biped displacements is solved in robotics in one hand and in nature in the other hand. We believe that the key e lements explaining the performances in adaptability and reactivity of human could help roboticians to find some issues for the design of automatic control schemes. Similarly, the theoretical framework of biped robotics could help neuroscientists to formulate concepts and models

A Synthesis of Bipedal Locomotion in Human and Robots

This report is the result of a joint reflection carried out by researchers from automatic control and neuroscience fields, both trying to answer a same question: what are the functional basis of bipedal locomotion and how to control them? The originality of this work is to put in parallel two synthesis of how the problem of biped displacements is solved in robotics in one hand and in nature in the other hand. We believe that the key e lements explaining the performances in adaptability and reactivity of human could help roboticians to find some issues for the design of automatic control schemes. Similarly, the theoretical framework of biped robotics could help neuroscientists to formulate concepts and models

Robust foot clearance estimation based on the integration of foot-mounted IMU acceleration data

This paper introduces a method for the robust estimation of foot clearance during walking, using a single inertial measurement unit (IMU) placed on the subject's foot. The proposed solution is based on double integration and drift cancellation of foot acceleration signals. The method is insensitive to misalignment of IMU axes with respect to foot axes. Details are provided regarding calibration and signal processing procedures. Experimental validation was performed on 10 healthy subjects under three walking conditions: normal, fast and with obstacles. Foot clearance estimation results were compared to measurements from an optical motion capture system. The mean error between them is significantly less than 15 % under the various walking conditions

Vision-based interface for grasping intention detection and grip selection : towards intuitive upper-limb assistive devices

Assistive devices for indivuals with upper-limb movement often lack controllability and intuitiveness, in particular for grasping function. In this work, we introduce a novel user interface for grasping movement control in which the user delegates the grasping task decisions to the device, only moving their (potentially prosthetic) hand toward the targeted object

Spike Sorting of Muscle Spindle Afferent Nerve Activity Recorded with Thin-Film Intrafascicular Electrodes

Afferent muscle spindle activity in response to passive muscle stretch was recorded in vivo using thin-film longitudinal intrafascicular electrodes. A neural spike detection and classification scheme was developed for the purpose of separating activity of primary and secondary muscle spindle afferents. The algorithm is based on the multiscale continuous wavelet transform using complex wavelets. The detection scheme outperforms the commonly used threshold detection, especially with recordings having low signal-to-noise ratio. Results of classification of units indicate that the developed classifier is able to isolate activity having linear relationship with muscle length, which is a step towards online model-based estimation of muscle length that can be used in a closed-loop functional electrical stimulation system with natural sensory feedback

Le contrôleur du robot BIP2000

L'INRIA Rhône-Alpes et le Laboratoire de Mécanique des Solides de l'Université de Poitiers ont développé dans le cadre d'un projet commun, un robot anthropom- orphe à quinze degrés de liberté capable de marcher dynamiquement ainsi que de gravir des escaliers. Deux prototypes ont été conçus et réalisés par le LMS. L'INRIA avait la responsabilité de la réalisation de l'armoire de commande et des câblages, ainsi que du développement d'un contrôleur pour le robot. Ce rapport présente la partie logicielle du contrôleur qui a été programmé et mis en oeuvre sur la base de l'environnement temps-réel Orccad. Ce contrôleur a été utilisé dans le cadre d'expérimentations de marche statiquement stable dans le plan et de mouvements posturaux 3D statiquement stables. Ces résultats ont été présentés lors de l'Exposition Universelle de Hanovre 2000 et ont fait l'objet de plusieurs publications. Ce document fait suite au Rapport Technique 0243 qui présente les détails liés à l'armoire de commande et au câblage du robot

Posture and Movement Estimation Based on Reduced Information. Application to the Context of FES-based Control of Lower-Limbs

International audienc

Synthesis of optimal electrical stimulation patterns for functional motion restoration: applied to spinal cord-injured patients

We investigated the synthesis of electrical stimulation patterns for functional movement restoration in human paralyzed limbs. We considered the knee joint system, co-activated by the stimulated quadriceps and hamstring muscles. This synthesis is based on optimized functional electrical stimulation (FES) patterns to minimize muscular energy consumption and movement efficiency criteria. This two-part work includes a multi-scale physiological muscle model, based on Huxley’s formulation. In the simulation, three synthesis strategies were investigated and compared in terms of muscular energy consumption and co-contraction levels. In the experimental validation, the synthesized FES patterns were carried out on the quadriceps-knee joint system of four complete spinal cord injured subjects. Surface stimulation was applied to all subjects, except for one FES-implanted subject who received neural stimulation. In each experimental validation, the model was adapted to the subject through a parameter identification procedure. Simulation results were successful and showed high co-contraction levels when reference trajectories were tracked. Experimental validation results were encouraging, as the desired and measured trajectories showed good agreement, with an 8.4 % rms error in a subject without substantial time-varying behavior. We updated the maximal isometric force in the model to account for time-varying behavior, which improved the average rms errors from 31.4 to 13.9 % for all subjects

Point-process analysis of neural spiking activity of muscle spindles recorded from thin-film longitudinal intrafascicular electrodes

Recordings from thin-film Longitudinal Intra-Fascicular Electrodes (tfLIFE) together with a wavelet-based de-noising and a correlation-based spike sorting algorithm, give access to firing patterns of muscle spindle afferents. In this study we use a point process probability structure to assess mechanical stimulus-response characteristics of muscle spindle spike trains. We assume that the stimulus intensity is primarily a linear combination of the spontaneous firing rate, the muscle extension, and the stretch velocity. By using the ability of the point process framework to provide an objective goodness of fit analysis, we were able to distinguish two classes of spike clusters with different statistical structure. We found that spike clusters with higher SNR have a temporal structure that can be fitted by an inverse Gaussian distribution while lower SNR clusters follow a Poisson-like distribution. The point process algorithm is further able to provide the instantaneous intensity function associated with the stimulus-response model with the best goodness of fit. This important result is a first step towards a point process decoding algorithm to estimate the muscle length and possibly provide closed loop Functional Electrical Stimulation (FES) systems with natural sensory feedback information.National Institutes of Health (U.S.) (Grant R01-HL084502)National Institutes of Health (U.S.) (Grant DP1-OD003646

Implementation and validation of a stride length estimation algorithm, using a single basic inertial sensor on healthy subjects and patients suffering from Parkinson’s disease

As low cost and highly portable sensors, inertial measurements units (IMU) have become increasingly used in gait analysis, embodying an efficient alternative to motion capture systems. Meanwhile, being able to compute reliably accurate spatial gait parameters using few sensors remains a relatively complex problematic. Providing a clinical oriented solution, our study presents a gyrometer and accelerometer based algorithm for stride length estimation. Compared to most of the numerous existing works where only an averaged stride length is computed from several IMU, or where the use of the magnetometer is incompatible with everyday use, our challenge here has been to extract each individual stride length in an easy-to-use algorithm requiring only one inertial sensor attached to the subject shank. Our results were validated on healthy subjects and patients suffering from Parkinson’s disease (PD). Estimated stride lengths were compared to GAITRite© walkway system data: the mean error over all the strides was less than 6% for healthy group and 10.3% for PD group. This method provides a reliable portable solution for monitoring the instantaneous stride length and opens the way to promising applications