In taekwondo, poomsae (i.e., form) competitions have no quantitative scoring standards, unlike gyeorugi (i.e., full-contact sparring) in the Olympics. Consequently, there are diverse fairness issues regarding poomsae evaluation, and the demand for quantitative evaluation tools is increasing. Action recognition is a promising approach, but the extreme and rapid actions of taekwondo complicate its application. This study established the Taekwondo Unit technique Human Action Dataset (TUHAD), which consists of multimodal image sequences of poomsae actions. TUHAD contains 1936 action samples of eight unit techniques performed by 10 experts and captured by two camera views. A key frame-based convolutional neural network architecture was developed for taekwondo action recognition, and its accuracy was validated for various input configurations. A correlation analysis of the input configuration and accuracy demonstrated that the proposed model achieved a recognition accuracy of up to 95.833% (lowest accuracy of 74.49%). This study contributes to the research and development of taekwondo action recognition.

A flexible surgical robot that can adjust its stiffness guarantees safe operation by satisfying both the high flexibility required when the robot approaches a surgical target and the more stiffness necessary for the end effector to perform surgical procedures. Therefore, this paper proposes a flexible surgical robot that consists of a central backbone, eight super-elastic wires as peripheral backbones, SMA springs, rubber tubes, and several disks. The inner diameter of the SMA springs that can be changed via their temperature creates a tightening force change to apply onto the eight backbone wires of the robot to adjust the overall stiffness of the robot. The simple structure is favorable for robot miniaturization. Frictional force and stiffness modulation experiments of the robot are performed. The results confirmed that the robot's stiffness was increased approximately 1.4 times between the martensite state and the austenite state of the SMA spring. The relationship model between the flexural rigidity of the robot and the frictional force between the SMA spring with the peripheral backbones is established. We compared the flexural rigidity values obtained from our model with those of the experimental result and confirmed that the model was valid.

Objective: To evaluate a novel multi-channel functional electrical stimulation (FES) rehabilitation method based on the evaluation of patient-specific walking dysfunction. Methods: This study investigated a novel multi-channel FES-based rehabilitation method that analysed the patient’s muscle synergy and walking posture. A patient-specific FES profile was produced in the pre-evaluation stage by comparing the muscle synergy and walking posture of the patient with those of healthy control subjects. During the rehabilitation phase, this profile was used to determine an appropriate FES pulse width and amplitude for stimulating the patient’s muscles as they walked across a flat surface. Results: Two stroke patients with hemiplegic symptoms participated in a clinical evaluation of the proposed method involving a 4-week course of rehabilitation. An evaluation of the rehabilitation results based on a comparison of the pre- and post-rehabilitation muscle synergy and walking posture revealed that the rehabilitation enhanced the muscle synergy similarity between the patients and healthy control subjects and their quantitative walking performance, as measured by a 10-m walk test and walking speed, by up to 23.38% and 30.00%, respectively. Conclusion: These results indicated that the proposed rehabilitation method improved walking ability by improving muscle coordination and adequately supporting weakened muscles in stroke patients.