Balance training using an interactive game to enhance the use of the affected side after stroke

Shih-Hsiang Ciou, Yuh-Shyan Hwang, Chih-Chen Chen, Shih-Ching Chen, Shih-Wei Chou, Yu-Luen Chen, Shih-Hsiang Ciou, Yuh-Shyan Hwang, Chih-Chen Chen, Shih-Ching Chen, Shih-Wei Chou, Yu-Luen Chen

Abstract

[Purpose] Stroke and other cerebrovascular diseases are major causes of adult mobility problems. Because stroke immobilizes the affected body part, balance training uses the healthy body part to complete the target movement. The muscle utilization rate on the stroke affected side is often reduced which further hinders affected side functional recovery in rehabilitation. [Subjects and Methods] This study tested a newly-developed interactive device with two force plates to measuring right and left side centers of pressure, to establish its efficacy in the improvement of the static standing ability of patients with hemiplegia. An interactive virtual reality game with different side reaction ratios was used to improve patient balance. The feasibility of the proposed approach was experimentally demonstrated. [Results] Although the non-affected-side is usually used to support the body weight in the standing position, under certain circumstances the patients could switch to using the affected side. A dramatic improvement in static standing balance control was achieved in the eyes open condition. [Conclusion] The proposed dual force plate technique used in this study separately measured the affected and non-affected-side centers of pressure. Based on this approach, different side ratio integration was achieved using an interactive game that helped stroke patients improve balance on the affected side. Only the patient who had suffered stroke relatively recently benefited significantly. The proposed technique is of little benefit for patients whose mobility has stagnated to a certain level.

Keywords: Affected side; Standing balance; Stroke.

Figures

Fig. 1.
Fig. 1.
System schematic diagram
Fig. 2.
Fig. 2.
The relationship between the force and the moment arm
Fig. 3.
Fig. 3.
Schematic diagram of the capture device
Fig. 4.
Fig. 4.
Architecture of the game engine
Fig. 5.
Fig. 5.
The COP distribution of case A
Fig. 6.
Fig. 6.
The COP distribution of case B
Fig. 7.
Fig. 7.
COP distribution before and after training

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