Comparison of balance responses and motor patterns during sit-to-stand task with functional mobility in stroke patients
- PMID: 9354495
- DOI: 10.1097/00002060-199709000-00011
Comparison of balance responses and motor patterns during sit-to-stand task with functional mobility in stroke patients
Abstract
This study was undertaken to explore whether we could provide supportive laboratory evidence for the clinical observations that a stroke patient has lost functional mobility/locomotion capability based on dynamic balance responses (center of force sway patterns) and motor control activities (electromyography patterns) during the motor task of sit-to-stand. A computerized controlled dynamic postural control assessment system was developed and used in this study. Various dynamic balance indexes were introduced and derived from center of force sway patterns expressed in four domains (space, time, force, and frequency). Motor control was assessed by multichannel surface electromyography of each side of the lower limb during the same motor task. The functional mobility capability was evaluated using the traditional FIM method. Fourteen stroke patients with right hemiplegia and nine healthy elderly individuals were recruited as the experimental and control groups, respectively. Muscle activity was recorded for quadriceps, hamstrings, anterior tibialis, and triceps surae muscles and was used for analysis. Center of force sway patterns and ground reaction forces were registered. All signals were synchronized at "seat-off." Surface electromyographic patterns of activities recorded during sit-to-stand and dynamic balance indexes computed from center of force sway patterns were categorized and compared with the functional mobility scores. Results show that both the motor control patterns and dynamic balance indexes correlated well to the extent of mobility impairment evaluated using the traditional FIM method. An important conclusion for rehabilitation medicine is that the functional mobility capability of stroke patients may be expressed numerically using dynamic balance indexes and visualized graphically through electromyographic motor patterns.
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