Development of Automatic Controlled Walking Assistive Device Based on Fatigue and Emotion Detection

The world’s aging population is increasing. The number of elderly individuals having walking impairments is also increasing. Adequate exercise is becoming necessary for them. Therefore, several walking assistive devices have been developed or are under development. However, elderly individuals may have low motivation for exercising, or they may experience physical damage by excessive fatigue. This study proposed a method to enable elderly individuals to exercise with a positive emotion and prevent damage such as muscle fatigue. We proposed a 3D human condition model to control the walking assistive device. It includes the arousal, pleasure, and fatigue dimensions. With regard to the arousal and pleasure dimensions, we used heartbeat and electromyography (EEG) signals to train a deep neural network (DNN) model to identify human emotions. For fatigue detection, we proposed a method based on near-infrared spectroscopy (NIRS) to detect muscle fatigue. All the sensors are portable. This implies that it can be used for outdoor activities. Then, we proposed a walking strategy based on a 3D human condition model to control the walking assistive device. Finally, we tested the effectiveness of the automatic control system. The wearing of the walking assistive device and implementation of the walking strategy can delay the fatigue time by approximately 24% and increase the walking distance by approximately 16%. In addition, we succeeded in visualizing the distribution of emotion during each walking method variation. It was verified that the walking strategy can improve the mental condition of a user to a certain extent. These results showed the effectiveness of the proposed system. It could help elderlies maintain higher levels of motivation and prevent muscle damage by walking exercise, using the walking assistive device.

Analysis of Muscle Activity in the Sit-to-Stand Motion When Knee Movability is Disturbed

Sit-to-stand motion is an important daily activity, and disability of motion can significantly reduce quality of life. Therefore, it is important to understand the mechanism of sit-to-stand motion in order to prevent such scenarios. The sit-to-stand motion was found to be generated by four muscle groups, through muscle synergy. However, it is unclear how muscle synergy can be controlled. Human sit-to-stand motion may be planned based on body condition before motion. In this study, we aimed to clarify the relationship between body condition and muscle activity during the sit-to-stand motion. Accordingly, we measured the muscle activity when knee movability was disturbed as a condition of body change. We also measured the muscle activity during normal sit-to-stand motion and sit-to-stand motion with disturbed knee movability using surface electromyography. Subsequently, we extracted the muscle synergy from the measured muscle activity and compared the activity levels of muscle synergy. The results revealed that muscle activity contributing to forward bending increased and that contributing to the rise of the hip and stabilization decreased when knee movability was disturbed. These results suggest that humans compensate for disturbed knee movability with forward momentum and bending motion. Moreover, this implies that humans adjust their motion to various environments or body conditions by adjusting the level of forward bending activity.