Evaluation metrics of upper extremities for people with neurological disorders: An energy based approach

Autor: Ilia, T., Louca, Loucas S.
Přispěvatelé: Louca, Loucas S. [0000-0002-0850-2369]
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: ASME 2017 Dynamic Systems and Control Conference, DSCC 2017
Popis: Various neurological disorders, like Parkinson's disease, Multiple Sclerosis, Huntington's disease and Stroke, affect millions of people worldwide. Tremor that is a result of these disorders affects the performance of many Activities of Daily Living such as dressing, bathing, self-care, and writing, which reduces the functional independence and self-rated quality of life. Standardized rating scales have been developed, however, these scales display some degree of variability due to their subjective/qualitative approach. Therefore, the accurate and objective measure of a patient's condition is crucial. Due to the lack of objectivity and accuracy from conventional procedures, there is a need to develop an objective evaluation system. In this work, a horizontal movement test is implemented in a Virtual Environment with the use of a Haptic Interface. The proposed test consists of a simple reaching task (more tasks are under development) for defining quantitative metrics. Wrist motion is accurately measured using the haptic interface and analyzed to calculate evaluation metrics based on the joint energy and spatial deviation from the ideal path. To improve the sensitivity of the metrics, a harmonic disturbance force is applied by the haptic interface to the user. The disturbance frequency is varied from 1 to 7 Hz and the duration of the movement is constraint to be constant. Fourteen healthy adults performed the experiments with 10 to 21 repetitions for each movement conditions. The results show that all users spend higher energy to complete the test at frequencies around 2.5 Hz. The statistical analysis indicates that energy is a reliable evaluation metric, with low variance, that can be used to quantify upper extremities. Copyright © 2017 ASME. 1
Databáze: OpenAIRE