RESUMO
Functional mobility tests, such as the L test of functional mobility, are recommended to provide clinicians with information regarding the mobility progress of lower-limb amputees. Smartphone inertial sensors have been used to perform subtask segmentation on functional mobility tests, providing further clinically useful measures such as fall risk. However, L test subtask segmentation rule-based algorithms developed for able-bodied individuals have not produced sufficiently acceptable results when tested with lower-limb amputee data. In this paper, a random forest machine learning model was trained to segment subtasks of the L test for application to lower-limb amputees. The model was trained with 105 trials completed by able-bodied participants and 25 trials completed by lower-limb amputee participants and tested using a leave-one-out method with lower-limb amputees. This algorithm successfully classified subtasks within a one-foot strike for most lower-limb amputee participants. The algorithm produced acceptable results to enhance clinician understanding of a person's mobility status (>85% accuracy, >75% sensitivity, >95% specificity).
Assuntos
Amputados , Extremidade Inferior , Aprendizado de Máquina , Adulto , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Amputados/reabilitação , Extremidade Inferior/cirurgia , Extremidade Inferior/fisiopatologia , Extremidade Inferior/fisiologia , Algoritmo Florestas AleatóriasRESUMO
INTRODUCTION: The evidence on the utility and effectiveness of rehabilitation interventions delivered via telerehabilitation is growing rapidly. Telerehabilitation is expected to have a key role in rehabilitation in the future. AIM: The aim of this evidence-based position paper (EBPP) is to improve PRM physicians' professional practice in telerehabilitation to be delivered to improve functioning and to reduce activity limitations and/or participation restrictions in individuals with a variety of disabling health conditions. METHODS: To produce recommendations for PRM physicians on telerehabilitation, a systematic review of the literature and a consensus procedure by means of a Delphi process have been performed involving the delegates of all European countries represented in the UEMS PRM Section. RESULTS: The systematic literature review is reported together with the 32 recommendations resulting from the Delphi procedure. CONCLUSIONS: It is recommended that PRM physicians deliver rehabilitation services remotely, via digital means or using communication technologies to eligible individuals, whenever required and feasible in a variety of health conditions in favor of the patient and his/her family, based on evidence of effectiveness and in compliance with relevant regulations. This EBPP represents the official position of the European Union through the UEMS PRM Section and designates the professional role of PRM physicians in telerehabilitation.