Dissertation/ Thesis
A Kinematic Framework for Upper Extremity Rehabilitation Assessment : Expectation- Maximization as a Motor Learning Model ; Un modèle cinématique pour l'évaluation de la rééducation des membres supérieurs : l'espérance-maximisation comme modèle d'apprentissage moteur
| العنوان: | A Kinematic Framework for Upper Extremity Rehabilitation Assessment : Expectation- Maximization as a Motor Learning Model ; Un modèle cinématique pour l'évaluation de la rééducation des membres supérieurs : l'espérance-maximisation comme modèle d'apprentissage moteur |
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| المؤلفون: | Meziani, Yeser |
| المساهمون: | Laboratoire de Conception, Optimisation et Modélisation des Systèmes (LCOMS), Université de Lorraine (UL), Laboratoire d'Automatique de Tlemcen (LAT), Université Aboubekr Belkaid - University of Belkaïd Abou Bekr Tlemcen, Bourse - Campus France, Université de Lorraine, Université Abou Bekr Belkaid (Tlemcen, Algérie), Guy Bourhis, Mohammed Amine Hadj Abdelkader, Yann Morère |
| المصدر: | https://hal.univ-lorraine.fr/tel-03876007 ; Automatic. Université de Lorraine; Université Abou Bekr Belkaid (Tlemcen, Algérie), 2022. English. ⟨NNT : 2022LORR0096⟩. |
| بيانات النشر: | HAL CCSD |
| سنة النشر: | 2022 |
| المجموعة: | Université de Lorraine: HAL |
| مصطلحات موضوعية: | Post CVA, Physical systems modelisation, Motor abilities rehabilitation, Post AVC, Modélisation des systèmes physiques, Performance de rééducation, [SPI.AUTO]Engineering Sciences [physics]/Automatic |
| الوصف: | Motor learning as a recovery mechanism is assumed to be a framework that drived and guided physical therapy and now since the advent of robotics doing the same to the rehabilitation devices. The rehabilitation process presents the intersection of many different interconnected facets that co-interact to produce recovered movements. The use of the technology introduces many benefits while contributing to the complexity of the phenomena at hand. We interest our research to the passive exosquelette training of the upper limb. We propose an adaptive intra patient assessment scale that is capable of detecting intra-patient performance changes during robotic training. Motor learning, the process of our brain's acquiring newer motor skills or relearning those he lost due to neurological or traumatic incident is our portal to investigating this phenomenon. The interaction of the system that is composed of the device, the incentive in form of exercise games and the patients with all its level of existence, physiological, psycho-logical, and cognitive is the system of study. The components present heterogeneous qualities and dynamically driven changes. The system output in the form of the trajectories executed is our gauging instrument to investigate the interactions within the system. We formulate the trajectory model as a Markov Chain and use the Kalman Filter to estimate the smoothed states. While dynamics are variant in time we model the assumptions about the movement into a dynamical formulation and estimate its parameters from data. To account for the time variability we introduce parallel noise source to the dynamics and estimate it using an Expectation-Maximization algorithm. The temporal nature being only a single facet of the kinematic phenomena, we assume a variable temporal alignment and estimate it using Expectation-Maximization iteration to increase the likelyhood of the estimated model compared to the observed trajectories. Once learned the model dependent and extracted parameters are used to compare between ... |
| نوع الوثيقة: | doctoral or postdoctoral thesis |
| اللغة: | English |
| Relation: | NNT: 2022LORR0096; tel-03876007; https://hal.univ-lorraine.fr/tel-03876007; https://hal.univ-lorraine.fr/tel-03876007/document; https://hal.univ-lorraine.fr/tel-03876007/file/DDOC_T_2022_0096_MEZIANI.pdf |
| الاتاحة: | https://hal.univ-lorraine.fr/tel-03876007 https://hal.univ-lorraine.fr/tel-03876007/document https://hal.univ-lorraine.fr/tel-03876007/file/DDOC_T_2022_0096_MEZIANI.pdf |
| Rights: | info:eu-repo/semantics/OpenAccess |
| رقم الانضمام: | edsbas.3B8A676 |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |