2 research outputs found
Classification de mouvements fantômes du membre supérieur chez des amputés huméraux à l'aide de mesures électromyographiques et cinématiques
RÉSUMÉ
La perte d’un membre supérieur engendre de nombreux déficits fonctionnels pour l’amputé dans sa vie de tous les jours. En effet, la plupart des activités de la vie quotidienne, telles qu’attacher ses souliers ou ouvrir une bouteille, sont complexes et difficiles à réaliser avec un seul bras fonctionnel. Les impacts de ces déficits augmentent à mesure que le niveau d’amputation est plus haut au niveau du bras. Pour toutes ces personnes, les nombreuses avancées dans le domaine des
prothèses myoélectriques, c’est-à -dire commandées par l’activité musculaire des muscles restants après l’amputation, sont encourageantes parce qu’elles permettent d’entretenir l’espoir d’une prothèse à la commande intuitive.
Un phénomène particulier, présent chez la majorité des amputés, est celui des sensations au membre fantôme. Ces sensations peuvent se manifester sous plusieurs formes : thermiques, douleurs, mobilités. Les mobilités du membre fantôme sont particulièrement intéressantes pour le
développement des prothèses myoélectriques étant donné qu’il a été démontré que les mouvements fantômes produisent une activité électromyographique (EMG) au niveau du membre amputé. Cependant, les études s’intéressant à la détection des mouvements fantômes ont
enregistré l’activité EMG provenant de muscles difficilement intégrables dans l’emboiture d’une
prothèse myoélectriques, tels que ceux du dos, du torse et de l’épaule. La présente étude se concentre sur la classification des mouvements fantômes chez les amputés huméraux à l’aide de l’EMG dans l’optique de développer une prothèse myoélectrique commandée par reconnaissance
de formes.
Cinq adultes ayant subi une amputation unilatérale humérale suite à un trauma ont participé à cette étude. L’activité EMG des participants a été enregistrée exclusivement autour de leur moignon. Durant les enregistrements, il était demandé aux participants de réaliser l’un des principaux mouvements fantômes du membre supérieur : la flexion ou l’extension du coude, la
pronation ou la supination de l’avant-bras, la flexion ou l’extension du poignet, l’ouverture ou la fermeture de la main et le repos. Chaque mouvement fantôme devait être réalisé symétriquement à l’aide du bras sain et la cinématique de ce dernier a été enregistrée à l’aide d’un système d’analyse du mouvement. Dix caractéristiques (ou « features » en anglais) temporels ont été extraites des signaux EMG et utilisées pour entraîner un réseau de neurones permettant de classifier les mouvements fantômes du membre supérieur.----------ABSTRACT
Upper limb amputation creates substantial functional deficits for the amputee. Indeed, most activities of daily living, such as tying shoelaces or opening a bottle, are complex and hard to achieve with only one functional arm. These functional impairments increase as the level of amputation is higher up the arm. For these people, recent advances in the field of myoelectric
prostheses, i.e. controlled by the activity of the remaining muscles after amputation, are encouraging because they help maintain the hope of an intuitive prosthesis.
A particular phenomenon, occurring in the majority of amputees, is the presence of phantom limb sensations. Phantom limb sensations are of many types: thermal, pain, and mobility. Phantom limb mobilities are particularly interesting for the development of myoelectric prostheses since it has been shown that they produce an electromyographic (EMG) activity in the amputated limb.
However, the studies focusing on the detection of phantom movements recorded EMG from muscles that are hard to integrate into the socket element of a myoelectric prosthesis, such as the back, chest and shoulder muscles. This study focuses on the classification of phantom
movements in transhumeral amputees using EMG in the context of developing a myoelectric prosthesis controlled by pattern recognition.
Five adults who underwent unilateral humeral amputation following a trauma participated in this study. The EMG activity of the participants was recorded exclusively around their stump. During the recordings, participants were asked to perform one of the main upper limb phantom
movements: flexion or extension of the elbow, pronation or supination of the forearm, flexion or extension of the wrist, opening or closing the hand and rest. Each phantom movement was to be made symmetrical with the unaffected arm and the kinematics of the latter was recorded using a
motion analysis system. Ten time-domain features were extracted from the EMG signals and used to train a neural network to classify the phantom limb movements. The performance of the classifier was evaluated based on the number of movements studied and an optimal set of four
EMG features was determined. The impact of kinematic information on the classification performance was also evaluated.
The accuracy of the classification varies from one amputee to another, but some trends are common: performance decreases if the number of degrees of freedom considered in the classification increases and/or if the phantom movements become more distal. Moreover, the optimal set of four EMG features provided a performance equivalent to that obtained with all ten EMG features. The addition of the kinematic information improved classification accuracy for all amputees
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Understanding Affected Muscle Activity in Children with Unilateral Congenital Below-Elbow Deficiency for Intuitive Control of Dexterous Prostheses
There are many complex factors that will affect whether children with a unilateral congenital below-elbow deficiency (UCBED) will use a prosthetic limb to interact within their environment. Children face higher rates of prosthesis abandonment at 35-45%, compared to adults at 23-26%. Ultimately, for a child to wear and use their prosthesis, it must facilitate the effective performance of daily tasks and promote healthy social interactions. Although beginning to emerge, multiarticulate upper limb prostheses for children remain sparse despite the continued advancement of mechatronic technologies that have benefited adults with upper limb amputations. In contrast, pediatric devices typically provide a single open-close grasp (if a grasping function is available at all) and often offer non-anthropomorphic appearances, falling short of meeting the criteria essential to prosthesis adoption. Moreover, this population presents unique challenges, as they were born never having actuated a hand, and with forearm musculature that never fully developed–a stark departure from those with acquired limb absence. Due to the lack of investigation into how children with UCBED actuate their muscles coupled with the limited advancement in pediatric upper limb devices, the effective translation of dexterous prostheses remains a prominent issue. This dissertation builds the fundamental groundwork necessary for the effective translation of dexterous prosthetic hands for children with UCBED. It begins with an examination of how typically developing children use their hands to interact within their environment to inform dexterous device development (Chapter 3). Here we found that children, like adults, use a small subset of hand movements to perform object manipulation in home settings. Subsequently, a child-sized dexterous prosthetic hand was developed to serve as a dedicated research platform (Chapter 4). A thorough benchmark of this research platform was performed to validate its functional grasping ability and it was shown to be a robust device within a research environment. Prior to using this device, a cohort of children with UCBED were recruited, and an in-depth analysis of state-of-the-art prosthetic control, namely surface electromyography (sEMG) as a measure of affected muscle electrical activity, was conducted (Chapter 5). Upon investigation, participants exhibited a measurable degree of consistency and repeatability of their affected musculature as obtained through sEMG when they attempted missing hand and wrist movements. Furthermore, through tuning features, i.e., sEMG characteristics, and classification algorithms, we found a novel generalized feature set that provided increased classification to decode hand motor intent (Chapter 6). Moreover, we benchmarked the real-time performance of these children to execute hand movements, adding a translational dimension to our findings (Chapter 7). This forms a crucial foundation for understanding muscle actuation and use of advanced prostheses among children with UCBED.
Through this work, we have laid the foundation to understand the capacity of children with UCBED to control their affected musculature. This begins to address the translational aspect of child-size dexterous upper limb devices and has the potential to remove barriers to device acceptance