Symmetry analysis of amputee gait based on body center of mass trajectory and discrete fourier transform

The calculation of symmetry in amputee gait is a valuable tool to assess the functional aspects of lower limb prostheses and how it impacts the overall gait mechanics. This paper analyzes the vertical trajectory of the body center of mass (CoM) of a group formed by transfemoral amputees and non-amputees to quantitatively compare the symmetry level of this parameter for both cases. A decomposition of the vertical CoM into discrete Fourier series (DFS) components is performed for each subject’s CoM trajectory to identify the main components of each pattern. A DFS-based index is then calculated to quantify the CoM symmetry level. The obtained results show that the CoM displays different patterns along a gait cycle for each amputee, which differ from the sine-wave shape obtained in the non-amputee case. The CoM magnitude spectrum also reveals more coefficients for the amputee waveforms. The different CoM trajectories found in the studied subjects can be thought as the manifestation of developed compensatory mechanisms, which lead to gait asymmetries. The presence of odd components in the magnitude spectrum is related to the asymmetric behavior of the CoM trajectory, given the fact that this signal is an even function for a non-amputee gait. The DFS-based index reflects this fact due to the high value obtained for the non-amputee reference, in comparison to the low values for each amputee

Investigating upper limb movement classification on users with tetraplegia as a possible neuroprosthesis interface

Spinal cord injury (SCI), stroke and other nervous system conditions can result in partial or total paralysis of individual’s limbs. Numerous technologies have been proposed to assist neurorehabilitation or movement restoration, e.g. robotics or neuroprosthesis. However, individuals with tetraplegia often find difficult to pilot these devices. We developed a system based on a single inertial measurement unit located on the upper limb that is able to classify performed movements using principal component analysis. We analyzed three calibration algorithms: unsupervised learning, supervised learning and adaptive learning. Eight participants with tetraplegia (C4-C7) piloted three different postures in a robotic hand. We achieved 89% accuracy using the supervised learning algorithm. Through offline simulation, we found accuracies of 76% on the unsupervised learning, and 88% on the adaptive one

Active Pathological Tremor Compensation on the Upper Limbs using Functional Electrical Stimulation

Le tremblement, défini comme un mouvement rythmique involontaire, est un des mouvements anormaux les plus fréquents. Le tremblement n'est pas une pathologie mortelle, mais elle diminue souvent considérablement la qualité de vie de la personne. Les traitements efficaces ne sont pas encore disponibles, puisque les solutions pharmacologiques et chirurgicales souffrent encore de limitations en termes d'efficacité, de risques et de coûts. Une alternative consiste à utiliser des technologies d'assistance, tels que les exosquelettes ou la Stimulation Électrique Fonctionnelle (SEF).Néanmoins, la conception de systèmes actifs de compensation des tremblements présente plusieurs défis. Un tel système doit être capable, par exemple, d'atténuer les tremblements tout en minimisant la fatigue, la douleur et l'inconfort induit. Il doit aussi distinguer entre le tremblement et le mouvement volontaire, afin de réduire les interférences sur les mouvements intentionnels.Cette thèse se concentre donc sur l'évaluation de l'usage de la SEF pour atténuer le tremblement. Une première contribution concerne le développement des modèles neuromusculosquelettiques pour étudier l'influence des boucles réflexes sur la dynamique du tremblement, ainsi que la modulation de l'impédance de l'articulation via la co-contraction induite par la SEF. Un algorithme pour estimer en ligne le tremblement et ses caractéristiques tout en filtrant le mouvement volontaire a été proposé et validé sur patients. Enfin, un système SEF pour atténuer le tremblement basé sur le contrôle d'impédance a été conçu et évalué sur patients, alors qu'une deuxième stratégie en boucle fermée a été testée sur des sujets sains.Tremor, defined as an involuntary, approximately rhythmic and roughly sinusoidal movement, is one of the most common movement disorders. It is not a life-threatening pathology, but it often decreases significantly the person's quality of life. Today, effective treatments for pathological tremor are not yet available, since current pharmacological and surgical alternatives still present limitations with respect to effectiveness, risks, and costs. A different approach is the use of assistive technologies, such as upper limb exoskeletons or Functional Electrical Stimulation (FES).Nevertheless, the design of active tremor compensation systems based on these technologies presents several challenges. Such a system must be able, for instance, to attenuate tremor while minimizing the induced fatigue, pain, and discomfort. Also, it must be able to distinguish between pathological tremor and voluntary motion, in order to reduce interference on intentional movements.This thesis is focused then in evaluating the use of FES to attenuate the effects of tremor. A first contribution concerns the use of neuromusculoskeletal models to study the effects reflex pathways may produce on tremor dynamics, as well as how FES-induced co-contraction may modulate joint impedance. Also, an online algorithm to estimate tremor and its features while simultaneously filtering voluntary motion has been proposed and validated with tremor patients. Finally, a FES system to attenuate tremor based on impedance control has been designed and evaluated on tremor patients, while a second strategy using closed-loop FES control has been tested on healthy subjects

Tremor attenuation using FES-based joint stiffness control

In this paper, a strategy to attenuate tremor based on co-contraction of antagonist muscles using Functional Electrical Stimulation (FES) is fully presented. Both methods to track tremor features in real-time, while filtering voluntary motion, and to identify a suitable joint model are described. Using this information, the stimulation controller modulates joint stiffness based on tremor intensity, while preventing the generation of undesirable joint torque. An experimental evaluation of the system, which confirmed the effectiveness of the approach, is also presented

Methodology for automatic movement cycle extraction using Switching Linear Dynamic System

Human motion assessment is key for motor-control rehabilitation. Using standardized definitions and spatiotemporal features - usually presented as a movement cycle diagram- specialists can associate kinematic measures to progress in rehabilitation therapy or motor impairment due to trauma or disease. Although devices for capturing human motion today are cheap and widespread, the automatic interpretation of kinematic data for rehabilitation is still poor in terms of quantitative performance evaluation. In this paper we present an automatic approach to extract spatiotemporal features from kinematic data and present it as a cycle diagram. This is done by translating standard definitions from human movement analysis into mathematical elements of a Switching Linear Dynamic System model. The result is a straight-forward procedure to learn a tracking model from a sample execution. This model is robust when used to automatically extract the movement cycle diagram of the same motion (the Sit-Stand-Sit, as an example) executed in different subject-specific manner such as his own motion speed

Towards a cooperative framework for interactive manipulation involving a human and a humanoid

International audienceIn this paper we propose a novel approach for interactive manipulation involving a human and a humanoid. The interaction is represented by means of the relative configuration between the human's and the robot's hands. Based on this principle and a set of mathematical tools also proposed in the paper, a large set of tasks can be represented intuitively. We also introduce the concept of simultaneous handling using mirrored movements, where the human controls the robot and simultaneously interacts with it by means of a common manipulated object. Illustrative experiments are performed to validate the proposed techniques

FES-controlled co-contraction strategies for pathological tremor compensation

In this paper, a strategy for pathological tremor compensation based on co-contraction of antagonist muscles induced by Functional Electrical Stimulation (FES) is presented. Although one of the simplest alternatives to apply FES for reducing the effects of tremor, the contribution of different co-contraction levels for joint motion and impedance must be accurately estimated, specially since tremor itself is highly time-varying. In this work, a detailed musculoskeletal model of the human wrist actuated by flexor and extensor muscles is used for this purpose. The model takes into account different properties that affect muscle dynamics, such as proprioceptive feedback and combined natural and artificial activation. The model, analysis of stiffness modulation clue to FES-controlled co-contraction and simulation results are presented in the paper

A Kinematic Information Acquisition Model That Uses Digital Signals from an Inertial and Magnetic Motion Capture System

This paper presents a model that enables the transformation of digital signals generated by an inertial and magnetic motion capture system into kinematic information. First, the operation and data generated by the used inertial and magnetic system are described. Subsequently, the five stages of the proposed model are described, concluding with its implementation in a virtual environment to display the kinematic information. Finally, the applied tests are presented to evaluate the performance of the model through the execution of four exercises on the upper limb: flexion and extension of the elbow, and pronation and supination of the forearm. The results show a mean squared error of 3.82° in elbow flexion-extension movements and 3.46° in forearm pronation-supination movements. The results were obtained by comparing the inertial and magnetic system versus an optical motion capture system, allowing for the identification of the usability and functionality of the proposed model

A comparative study on control strategies for FES cycling using a detailed musculoskeletal model

Although advances in technology promoted new physiotherapy approaches for rehabilitation, there is still an urge for equipment and techniques to improve quality of life for patients with motor disabilities. Functional Electrical Stimulation Cycling (FES Cycling) is an example of this type of technology, in which we control stimulation parameters to enable a spinal cord injured person to ride a bicycle. The presented research proposes a new detailed musculoskeletal platform using OpenSim to test and develop control strategies. With this platform, we were able to compare performance of four control techniques in transient and steady states