Analysis on muscle activities of different movement patterns on an unstable platform using association rule mining

The objective of this study was to analyze the muscle activities of different movement patterns on a training system for posture control using an unstable platform through an improved association rule mining methodology. This training system for postural control that we developed could simultaneously provide the stimulation of visual, vestibular and somatosensory through the training programs using the visual feedback. To investigate the relationship of the different movement patterns and muscle activities, fifteen healthy young subjects took part in a series of postural control training using this system. The electromyography of the muscles in the lower limbs were recorded and analyzed under the different movement patterns. An improved association rule mining methodology was applied to analyze the relationship of the movement patterns and muscle activities. The results showed the significant differences in muscle activities for the different movement patterns as association rules. The experimental results suggest that, through the choice of different movement pattern, the training for lower extremity strength could be performed on specific muscles in different intensity. And, the ability of postural control could be improved by the training for lower extremity strength. Through the analysis results, we tried to find the best training method to improve the ability of postural control through improving the lower extremity muscular strength.