Effect of the Observation of an Audio-Visual Modeling on the Rehabilitation of Upper Limb Function in Stroke Patients

시청각적 모델링의 관찰이 뇌졸중 환자의 상지기능 재활에 미치는 영향

  • Received : 2006.12.26
  • Accepted : 2007.03.11
  • Published : 2007.05.21

Abstract

The purpose of this experiment was to investigate the applicability of audio-visual modeling for improving the efficiency of rehabilitative programs by analyzing the effects of observing these various models on the capacity of stroke patients to perform upper limb activities. Twenty-one stroke patients participated in the experiment and were randomly assigned to either task modeling, sport modeling, or control group. During 2 weeks of intervention, subjects in all groups participated in the physical practice of experimental tasks. These tasks comprised of a Nine Hole Peg Test, the Jebsen-Taylor Hand Function tests, and locomotion. These tasks were performed 5 days a week, 30 min per day. In addition to the physical practice, the task modeling group observed a model performing experimental tasks and locomotive activities for 20 min, while the sport modeling group observed a model performing various sport activities for 20 min. Subjects' ability to perform the experimental tasks was measured 3 times, before, immediately after, and 1 week after the intervention. Analyses of the capacity to perform upper extremity activities displayed significant improvement from the pre-test to immediate and delayed post-tests in all groups. However, the amount of improvement was the highest in the task modeling group. The task modeling group was superior to the control group in the post-test of all experimental tasks, whereas the sport modeling group did not display significant differences from the control group. These results suggest that audio-visual modeling can be used as an effective cognitive intervention for facilitating the rehabilitation of stroke patients, and its rehabilitative effect can be maximized when the program is comprised of performance scenes directly related to the target task.

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