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Abstract Recently, interest has surged in glove-type assistive devices for relieving hand muscle stiffness caused by brain lesions. This study aims to develop an ergonomic method for drafting glove patterns intended for hand-assistive devices. To facilitate pattern development, we acquired three-dimensional (3D) scan data from the four hemiplegic patients while their hands were in a relaxed posture, which was subsequently transformed into two-dimensional (2D) data. Based on the 3D shape data, we analyzed the finger joint range of motion (ROM) and change ratio of skin surface length resulting from flexion and extension movements of the paralyzed hand. Incisions were strategically applied to regions displaying significant variations in these parameters. These flattened 2D patterns were then integrated into revised pattern blocks to enhance the shading data related to the 3D shape, resulting in the development of four glove patterns. We found that gloves prototyped using this innovative pattern-drafting method did not impede joint ROM when worn. Changes in clothing pressure inside the glove at the joints corresponded to the bending angles of the fingers, and the pressure did not exceed the discomfort threshold during hand flexion and extension movements. Importantly, participants provided positive subjective feedback concerning the comfort of the gloves. Our findings yield fundamental data for developing a foundational glove design for hand-assisted devices for patients with paralysis, achieved through the utilization of this novel ergonomic glove pattern-drafting method.

Abstract We developed the knitted shape-memory alloy (SMA) as a flexible actuator and applied it to a soft wearable exoglove for rehabilitation assistance. Based on user needs and anthropometric data, we custom-designed the exoglove for three hemiplegic patients using the knitted-SMA actuator and evaluated its bending performance, gripping force and wearability under the four simulation conditions (S1–S4). To address the specific needs, both SMA plain- and double-knit modules were applied to the exoglove based on the patients’ finger joint range of motion (ROMs). The joint ROMs of all fingers increased by 13.71% and the skin temperature increased by 2.21 °C after actuating the glove (p = 0.006). The gripping force increased as much as 55.01%, when compared to the baseline. All patients were able to don and doff the developed glove independently, and positively evaluated their subjective satisfaction and thermal perception. The findings suggested the potential of the knitted SMA for the future development of soft wearable robots.

Abstract Electronic monitoring systems have been globally adopted to track criminals to ensure public safety efficiently. In this study, we aimed to assess the wearability of an electronic bracelet using multiple evaluation methods, including the evaluation of range of motion (ROM), air gap (AG), and clothing pressure (CP) at the wearer’s wrist, as well as self-scoring of subjective comfort (SC). We recruited eight Korean male participants (N = 8) who were in their 30 s and did not have any musculoskeletal problems at data collection. We compared the test results collected on the first day with those obtained after wearing the electronic wrist bracelet for 5 consecutive days. We also examined the differences between the normal-weight and overweight groups. Overall, the data evinced a decrease in the wrist ROM, AG, and SC, but an increase in the CP after it was worn for 5 days. And, the results were more observable in the overweight group, as compared to the normal-weight group. Furthermore, this study proposed a novel and effective assessment tool that could be used to measure the wearability of devices or systems intended to be worn on the human body—not only the electronic wrist bracelet for criminal monitoring but also popular commercial electronic bracelets for sportswear or health-related monitoring system.