MétaCan
Menu
Retour à la cohorte
Enregistrement W3081302210 · doi:10.22215/etd/2014-10142

Design, Control, and Implementation of a Robotic Gait Rehabilitation System for Overground Gait Training

2014· dissertation· en· W3081302210 sur OpenAlexaff
Aliasgar Morbi

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineEngineering
ThématiqueProsthetics and Rehabilitation Robotics
Établissements canadiensCarleton University
Organismes subventionnairesnon disponible
Mots-clésGaitController (irrigation)TrajectoryRobotStability (learning theory)Computer scienceGait trainingSimulationEngineeringControl engineeringControl theory (sociology)Artificial intelligenceControl (management)RehabilitationPhysical medicine and rehabilitationPhysical therapy

Résumé

récupéré en direct d'OpenAlex

Robotic devices for gait rehabilitation have the potential to improve patient and caregiver safety, reduce therapy costs, and allow a larger number of patients to get access to physical therapy.Additionally, data collected from the robot's sensors may be used to assess impairment severity and track patient progress.However these devices also suffer from many drawbacks such as high cost, complexity, limited training capabilities, and constrained joint motions and postural responses.With these limitations in mind, this thesis introduces GaitEnable, a simply designed robotic gait trainer that combines an intelligent reactive controller, an actuated omnidirectional mobile base and a passive body weight support system.In addition to describing the device and its control system, this thesis also presents results from a series of validation experiments performed to characterize the performance of the device.The results demonstrate that GaitEnable's control system ensures stable humanrobot interactions, and that GaitEnable can assist and perturb a user's gait in a systematic manner.The experiments also confirm that GaitEnable's actuated omni-directional mobile allows users to walk more naturally as it reduces the motion constraints that the device imposes.In addition to describing the GaitEnable system, this thesis also focuses on the more general problem of interaction stability in coupled human-robot systems.Two novel trajectory manipulations for ensuring stable, oscillation-free interactions in admittance-controlled haptic devices are proposed.A Lyapunov stability analysis is used to show that the proposed manipulations are stable in the sense of uniform ultimate boundedness.Also, an extensive set of experiments confirm that the impedance manipulations allow the display of large apparent inertia reductions, ensure stable interactions, and are robust to actuator saturation and model uncertainties.These features make them ideal for use with robotic systems that are attached to humans (e.g., the GaitEnable system).Use of these manipulations is also extended to typical position control problems, and additional experimental results confirm the manipulations help eliminate chatter and provide a better transient response and steady-state tracking error.I would like to thank my supervisor Dr. Mojtaba Ahmadi for his mentorship, guidance, and friendship over the many years I spent at Carleton.Whenever I was stuck, I always knew that I could knock on his door and immediately be invited in.More than that, I will be forever grateful to him for affording me the freedom to pursue what I was most passionate about.Opportunities like that are rare, and I'm thankful that he had enough faith in me to let me explore without boundaries.I also want to thank the staff in the MAE office and at the machine shop for their assistance with the multitude of requests I inevitably came to them with over the years.Finally, I also want to thank the numerous lab mates who I've had the pleasure of spending time with, and being friends with over the last five years.It was a long road to get here, and your suggestions, help and company made it possible.v improves patient safety and reduces therapist workload. MotivationImmobility can lead to accelerated bone and muscle loss, sensory deprivation, isolation, delerium and incontinence [5].Short bouts of immobility, e.g., even 5-10 days of bed rest during a hospitalization, can contribute to an increased risk of mortality and significant impairments in an individual's long-term ability for self-care and locomotion [6].Many of these hazards can be avoided by timely and sufficient gait rehabilitation therapy [6][7][8][9][10].Fundamentally, the key to faster recovery is to walk early, typically within 24-48 hours of a major surgery or acute illness.Many studies show that the simple act of walking 15-25 minutes a day within 48 hours of an acute illness or surgery can improve outcomes and reduce hospitalization stays by 2-5 days [6][7][8][9][10].Therefore, tools and practices that encourage users to walk earlier during their hospital stay are critical.The impact of early gait rehabilitation is substantial since over 5,000,000 orthopaedic, post-surgical and acute cardiovascular, respiratory, and neurological inpatients can benefit from this therapy [11].While the benefits are clear, two key barriers limit the widespread practice of early mobilization: i) patient and caregiver safety concerns; and ii), staffing limitations.Physical and cognitive impairments caused by an illness or medication/sedation can leave many patients at a heightened risk for falls.These falls are a serious problem since nearly 23% of falls result in serious injuries such as hip fractures [12].Additionally, serious falls can increase patient care costs by nearly $35,000 and result in millions in litigation costs [12].Accordingly, tools that facilitate early mobility must be designed to prevent falls and reduce a patient's risk of injury during their training.Caregiver injuries also pose an impediment to the delivery of gait rehabilitation therapy.Support staff such as nurses, nurses' aides, and attendants have the highest Chapter 5 -Experiments with GaitEnableThis chapter investigates whether GaitEnable's powered omnidirectional mobile base can reduce motion constraints and generate force cues for influencing a user's gait.Results from experiments performed by seven healthy subjects confirm that GaitEnable's powered mobile base is capable of masking the device's inertial properties, and that the control system is capable of transmitting force cues for assisting or perturbing a user's gait.Additional results also show the value of using a powered mobile base in comparison to using castors, and GaitEnable's ability to minimize motion constraints during free walking. Chapter 6 -Conclusions and RecommendationThis chapter summarizes the research and discusses possible improvements and directions for future work.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,009

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,011
Tête enseignante GPT0,255
Écart entre enseignants0,244 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations6
Publié2014
Routes d'admission1
Résumé présentoui

Explorer davantage

Même sujetProsthetics and Rehabilitation RoboticsTravaux en français237 207