SEMG-based gesture recognition is useful for human–computer interactions, especially for technology supporting rehabilitation training and the control of electric prostheses. However, high variability in the sEMG signals of untrained users degrades the performance of gesture recognition algorithms. In this study, the hand posture recognition algorithm and radar plot-based visual feedback training were developed using multichannel sEMG sensors. Ten healthy adults and one bilateral forearm amputee participated by repeating twelve hand postures ten times. The visual feedback training was performed for two days and five days in healthy adults and a forearm amputee, respectively. Artificial neural network classifiers were trained with two types of feature vectors: a single feature vector and a combination of feature vectors. The classification accuracy of the forearm amputee increased significantly after three days of hand posture training. These results indicate that the visual feedback training efficiently improved the performance of sEMG-based hand posture recognition by reducing variability in the sEMG signal. Furthermore, a bilateral forearm amputee was able to participate in the rehabilitation training by using a radar plot, and the radar plot-based visual feedback training would help the amputees to control various electric prostheses.

This study investigated the efficacy of Augmented Reality (AR) in the rehabilitation of lower limb amputees by comparing movement accuracy and subjective satisfaction with and without AR. Ten individuals with unilateral lower limb amputations participated. Joint range of motion during exercises was measured using a 3D motion capture system. Subjective satisfaction was assessed via a 5-point Likert scale. Movement accuracy was evaluated by analyzing changes and variability (standard deviation) in joint angles across eight selected movements. Results showed that AR feedback significantly increased average joint angles in specific movements: standing arm raise to the side, standing trunk lateral flexion, and standing knee flexion to maximum height. Furthermore, AR feedback led to a significant reduction in the standard deviation of joint angles for most exercises, indicating improved movement consistency. Subjective satisfaction scores for interest, motivation, exercise effectiveness, movement accuracy, and overall satisfaction were significantly higher with AR.

The most common aftereffect of severe burns in patients is hypertrophic scarring. Hypertrophic scars typically form following severe burns; it refers to excessive collagen production in the dermal layer during the healing process, resulting in an abnormal raised scar. Currently, practical treatments for suppressing hypertrophic scars include laser therapy, pressure therapy, and the application of silicone sheets for moisture retention. The most extensively used treatment involves compression therapy using specially designed garments for the affected areas. However, this method has limitations when applied to curved surfaces like the face. To address this issue, three-dimensional (3D) scanning and 3D printing techniques have been actively developed for face masks and have shown promising clinical results. Unfortunately, current facial masks under development lack a sensor system to measure pressure, making it difficult to ensure consistent and appropriate pressures during clinical trials. In this study, we have developed a burn pressure mask capable of real-time pressure monitoring. The facial mask developed in this study utilizes an FSR-type sensor to measure the pressure applied to the skin. We have also embedded electrical wires within the mask to enhance its comfort and wearability. For this study, two patients wore the facial mask with real-time pressure measurement capabilities for 4 weeks in 12 h per day on average. We evaluated whether the mask maintained the appropriate pressure range (15–25 mmHg) throughout the clinical trial and whether it effectively inhibited scar formation. Through the analysis of recorded pressure signal data, we confirmed that the patients consistently maintained the appropriate pressure while wearing the mask during the clinical trial. Additionally, we observed significant differences in skin moisture levels, transepidermal water loss, and scar thickness before and after the experiment. These findings suggest that the facial mask, featuring real-time monitoring capabilities, effectively prevents the formation of hypertrophic scars.

Microprocessor-controlled knee prostheses (MPKs) face limited accessibility in resource-constrained environments due to high implementation costs and excessive power consumption associated with complex actuators. This study examines the technical feasibility of a low-cost electronically controlled pneumatic knee (ECPK) that combines structural mechanics with minimal electronic control. A functional decoupling strategy was implemented: stance-phase stability is provided by passive kinematic locking of a four-bar linkage over the near-extended stance range, while a lightweight feedforward controller driven by a single joint-axis Hall sensor segments the gait cycle continuously, updates its speed estimate once per step, and adjusts the valve only for swing-phase damping. From the stance duration of the preceding steps, this controller presets the pneumatic valve orifice to compensate for mechanical response delays, so that link rotation speed is regulated semi-actively without powered actuation. System integration and control viability were evaluated in a single-case feasibility study (N = 1), in which the ECPK was compared within subject with a commercial mechanical prosthesis after a 4-week adaptation period. Despite a 400 g distal mass penalty, the semi-active control algorithm was associated with a smaller increase in step-length asymmetry at the highest speed tested. Furthermore, net oxygen cost was lower with the ECPK during high-speed walking. Because the conditions were compared at unmatched self-selected speeds and the ECPK condition reached a respiratory exchange ratio (RER) of 1.13, this observation is hypothesis-generating. Coupling passive four-bar stance stability with minimal electronic swing regulation is therefore a viable engineering basis for accessible prostheses, and the present study establishes its technical feasibility rather than its clinical effectiveness.