(1) Background: The development of a lightweight, easy-to-use system that measures the foot’s plantar pressure is becoming an increasingly important area of research in physiotherapy. For further development of the smart sock system, a formative usability study was conducted, where the smart textile sock sensor system was used for self-correction during functional tasks; (2) Methods: Five athletes from the football school participated in the formative usability study. Athletes performed pre-defined functional tasks for self-correction when interacting with the smart textile sock system. Formative usability evaluation methods: effectiveness (task success rate, error rate), efficiency (time-based), satisfaction evaluated by System Usability Scale (SUS); (3) Results: Formative usability indicators: task completeness effectiveness ranged from 40% to 100% in the first- and second-stage tasks. Completed task efficiency time: Stage 1, from 4.2 s (SD 1.3) to 88.8 s (SD 19.8); Stage 2, from 7.2 s (SD 1.9) to 9.6 s (SD 2.1). Satisfaction was assessed by the SUS system user group with 76 points (SD 7.42), which indicates “good” satisfaction; (4) Conclusions: formative usability indicators showed the need for technical improvements to the smart textile sock pressure sensor system. The SUS results indicate “good” satisfaction with the smart textile sock pressure sensor system and its application.

Correctly performed Cardiopulmonary Resuscitation (CPR) is a critical element in preventing deaths caused by cardiac arrest (CA). To improve the outcomes and quality of CPR, stand-alone devices that monitor the performance and provide feedback have been developed. However, these devices have multiple limitations due to their rigidity and stiffness. Furthermore, most of the devices do not account for complete chest recoil as a metric of quality CPR, reducing the quality of compressions. To overcome these limitations, this study proposes smart gloves equipped with e-textiles-based pressure sensors and inertial measurement units (IMUs) to monitor the quality adult CPR in real-time. The prototype development combined data-driven design and Research Through Design (RtD) methods, taking into account not only the accuracy but also the usability of the smart gloves. A preliminary study with nine participants performing CPR on a doll was conducted to evaluate the accuracy and wearability of the smart gloves. Study results show that the smart gloves accurately detect chest compression parameters, including compression depth, compression rate, chest recoil and interruption between compressions based on the intelligent fusion of pressure sensors and IMUs. In addition, the newly developed smart gloves are lightweight, hand adaptable, and easily replicable as an alternative for hard case devices. The design methods used in this study can be applied to design other accessible and comfortable wearable devices in healthcare settings.

Background: The prevalence of upper limb impairment ranges from 40% to 50% in the chronic phase of stroke, presenting a significant public health challenge. Although traditional therapy effectively improves hand motor function, it often faces accessibility challenges. Telerehabilitation, particularly smart device–based therapy, provides a scalable and engaging alternative, although its effectiveness still requires further investigation. Objective: This study aimed to identify smart device–based therapy interventions for improving hand motor function in stroke survivors during rehabilitation and to assess their effectiveness in hand motor function improvement in comparison with traditional therapy methods. Methods: A scoping review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines to identify and evaluate smart device–based therapy interventions aimed at improving hand motor function in stroke survivors. A comprehensive literature search was performed across multiple databases, including Web of Science, PubMed (MEDLINE), EBSCO Complete, Google Scholar, Science Direct, ClinicalKey, and Scopus. Studies were screened based on predefined inclusion criteria, focusing on clinical trials that investigated the effectiveness of smart device–based rehabilitation approaches. Data extraction was carried out systematically, capturing key study characteristics, intervention types, and outcome measures. The effectiveness of these interventions was assessed and synthesized to provide a comprehensive overview of their impact on hand motor function recovery in stroke rehabilitation. Results: A total of 958 studies were identified, of which 17 met the inclusion criteria. The studies encompassed various research designs, including randomized controlled trials (n=9), pilot feasibility studies (n=3), and a comparative nonrandomized trial (n=1). The interventions used diverse digital strategies, including gamified rehabilitation programs (n=14), virtual or mixed reality systems (n=7), Kinect camera or sensor-based approaches (n=6), Jintronix software platforms (n=4), robot-assisted devices (n=3), and tablet- or app-based rehabilitation systems (n=7). Overall, smart device–based therapies were associated with improvements in hand motor function, frequently reaching clinically meaningful thresholds, while also enhancing patient engagement and adherence. Conclusions: The findings of this scoping study highlight the significant potential of smart device therapies for enhancing hand motor functions among stroke survivors. The development of smart devices is an evolving process, highlighting the need for future studies to assess their long-term effectiveness, optimize intervention designs, and explore their broader application in stroke rehabilitation.

Football players, particularly in youth leagues, face a high risk of lower limb injuries due to improper movement patterns. While programs like FIFA 11+ help reduce injuries, they lack real-time, personalized feedback for biomechanical correction. This concept protocol outlines the development of a DAid^® smart socks-based biofeedback system that integrates biomechanical monitoring with mixed reality (MR) feedback to enhance injury prevention. The DAid^® smart socks, equipped with pressure sensors and inertial measurement units (IMUs), track plantar pressure distribution and the center of pressure (COP). Real-time feedback is delivered via a Meta Quest 3 MR headset, enabling athletes to adjust movement patterns instantly. This protocol establishes a framework for evaluating the system’s feasibility and effectiveness in optimizing biomechanics and reducing injury risks. By combining wearable technology with MR-based feedback, this study advances injury prevention strategies, with potential applications in rehabilitation and performance training.