Harnesses can be used in various applications, such as entertainment, rescue operations, and medical applications. Because users are supported on the harness for a long time, they should feel comfortable wearing the harnesses. However, existing commercial harnesses are uncomfortable to wear and cause continuous serious pain. Therefore, in this study, a new pant-type harness with a fabric air pocket to reduce the applied pressure on the body, especially in the groin, is proposed. Keeping this in mind, we have designed and developed the pant-type harness. In addition, we performed pressure and contact area measurement experiments using the harness developed, pressure sensor, and a human mannequin. Peak and mean pressures and contact areas near the groin and waist were measured in the experiments. From the results, when air is injected in the air pockets, the peak pressure and contact area near the waist increased, and the peak pressure near the groin decreased. This means that the pressure applied on the human mannequin near the groin reduces because of the increased contact area near the waist, which is achieved by multi-layered air pockets. In this study, we proposed the optimal design of a novel pant-type harness that can address the limitations of existing harnesses. The proposed harness can be used for a prolonged time in applications, such as virtual reality entertainment, rescue operations, and rehabilitation.

Stroke causes neurological pathologies, including gait pathologies, which are diagnosed by gait analysis. However, existing gait analysis devices are difficult to use in situ or are disrupted by external conditions. To overcome these drawbacks, a flexible capacitance sensor was developed in this study. To date, a performance comparison of flexible sensors with different dimensions has not been carried out. The aim of this study was to provide optimized sensor dimension information for gait analysis. To accomplish this, sensors with seven different dimensions were fabricated. The dimensions of the sensors were based on the average body size and movement range of 20- to 59-year-old adults. The sensors were characterized by 100 oscillations. The minimum hysteresis error was 8%. After that, four subjects were equipped with the sensor and walked on a treadmill at a speed of 3.6 km/h. All walking processes were filmed at 50 fps and analyzed in Kinovea. The RMS error was calculated using the same frame rate of the video and the sampling rate of the signal from the sensor. The smallest RMS error between the sensor data and the ankle angle was 3.13° using the 49 × 8 mm sensor. In this study, we confirm the dimensions of the sensor with the highest gait analysis accuracy; therefore, the results can be used to make decisions regarding sensor dimensions.

With the expansion of robots, researchers have focused on robot tasks with waterproof functions. Although numerous underwater‐robot studies have been published recently, there has been minimal research on the waterproofing of robotic hands. The aim of this study is to develop an underwater gripping control strategy for a robot hand using a waterproof glove. By using a silicone‐rubber‐based waterproof glove, the robot hand finished the underwater gripping task. However, an error occurred during the gripping task because of the resistance force of the glove. To reduce the error, torque control experiments were conducted in two ways. In the first, a grooved glove was fabricated to reduce the resistance force. In the second, a modified control model with torque compensation was employed. In the experiments, it was observed that the torque compensation control model was more feasible than improving the shape of the glove for underwater gripping.