Measurement of Gait Kinematics in Multiple Sclerosis using a portable sensor
Notice bibliographique
Résumé
Multiple sclerosis (MS) is a common cause of disability in young adults. Currently, around 93,000 Canadians are living with the disease and the prevalence is increasing in Canada and worldwide. MS course and clinical features vary from one individual to another and are based on type. Mobility limitations are reported in early MS and progress over the years with walking difficulties perceived as the most challenging sequela. The importance of walking limitations in defining progression of MS has raised a suggestion of using gait changes for earlier detection of disease progression. Although the Expanded Disability Status Scale (EDSS) - a measure of disease progression - relies heavily on walking ability, multiple studies have reported changes in gait that are not translated into changes in the EDSS score. However, long-term changes in the EDSS were predicted by earlier gait limitations such as slow walking speed. Measures of gait kinematics, that better characterize gait quality could be early indicators of MS disability and MS progression. The development of wearable sensors made the assessment of gait kinematics more accessible and holds promise for self-monitoring and self-management. The objective of this thesis is to contribute evidence as to the relevance of measures of gait kinematics to quantify disability in MS. The work on this thesis was made possible because of access to data from people with MS whose gait quality was assessed using a new wearable Heel2ToeTM sensor (PhysioBiometrics Inc.). The thesis comprises one manuscript with two objectives. The primary objective is to estimate the extent to which personal factors and functional indicators are associated with gait quality parameters (gait kinematics) – measured using the Heel2Toe sensor - among ambulatory people with MS and the association of gait quality parameters with measures of physical capacity. The secondary objective is to estimate the extent to which gait quality parameters - changed over 3 months period among people with MS participating in an exercise intervention that did not include gait-targeted treatment.Correlational analysis was used to link MS impairments of leg weakness, leg heaviness, leg power, impaired coordination, fatigue, bladder dysfunction and mood with parameters related to gait kinematics. The strongest relationships (r ≥ 0.4) were observed between measures of leg power (vertical jump) and mood with both the power and balance cycles of the gait cycle. Of physical capacity measures, gait quality parameters were most strongly associated (r ≥ 0.5) with the Six-Minute Walk Test. Over 3 months period, without any specific gait training, parameters of gait kinematics deteriorated in multiple participants, improved in others, and remained the same in few participants, but these proportions did not differ from uniform distribution. However, some of the gait parameters changed concordantly
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».