RESUMEN
Mixed reality (MR) technologies have a high potential to enhance obstacle negotiation training beyond the capabilities of existing physical systems. Despite such potential, the feasibility of using MR for obstacle negotiation on typical training treadmill systems and its effects on obstacle negotiation performance remains largely unknown. This research bridges this gap by developing an MR obstacle negotiation training system deployed on a treadmill, and implementing two MR systems with a video see-through (VST) and an optical see-through (OST) Head Mounted Displays (HMDs). We investigated the obstacle negotiation performance with virtual and real obstacles. The main outcomes show that the VST MR system significantly changed the parameters of the leading foot in cases of Box obstacle (approximately 22 cm to 30 cm for stepping over 7cm-box), which we believe was mainly attributed to the latency difference between the HMDs. In the condition of OST MR HMD, users tended to not lift their trailing foot for virtual obstacles (approximately 30 cm to 25 cm for stepping over 7cm-box). Our findings indicate that the low-latency visual contact with the world and the user's body is a critical factor for visuo-motor integration to elicit obstacle negotiation.
RESUMEN
BACKGROUND: Training physiotherapists require substantial experience and a lengthy period of time to achieve proficiency. However, establishing an objective method for quantifying the degree of force applied during treatment remains elusive, making training difficult. OBJECTIVES: This study aims to clarify the difference in the degree of force application between novice and expert physiotherapists using muscle deformation sensors and to assist in teaching. METHODS: A muscle deformation sensor array was utilized to capture the muscle bulging (muscle deformation), and the degree of force was visualized. The experiment involved two types of physiotherapy: upper and lower extremity exercises. Subsequently, the muscle deformation value and standard deviations of the muscle deformation data obtained were compared. RESULTS: Significant differences between novices and experts were observed in forearm muscle deformation values and standard deviations across both types of physiotherapies (p<0.05). Additionally, a distinction was observed in the left lower limb flexor muscles during upper extremity exercise (p<0.05). CONCLUSION: The results of this survey showed notable differences in the degree of force application between novices and experts, as demonstrated by our findings. Moreover, these implications extend beyond physiotherapy to sports, hobbies, and the teaching of traditional skills.
RESUMEN
Hand-gripping training is important for improving the fundamental functions of human physical activity. Bernstein's idea of "repetition without repetition" suggests that motor control function should be trained under changing states. The randomness level of load should be visualized for self-administered screening when repeating various training tasks under changing states. This study aims to develop a sensing methodology of random loads applied to both the agonist and antagonist skeletal muscles when performing physical tasks. We assumed that the time-variability and periodicity of the applied load appear in the time-series feature of muscle deformation data. In the experiment, 14 participants conducted the gripping tasks with a gripper, ball, balloon, Palm clenching, and paper. Crumpling pieces of paper (paper exercise) involves randomness because the resistance force of the paper changes depending on the shape and layers of the paper. Optical myography during gripping tasks was measured, and time-series features were analyzed. As a result, our system could detect the random movement of muscles during training.