Real-time biomechanical feedback (BMF) is a relatively new area of research. The potential of using advanced technology to improve motion skills in sport and accelerate physical rehabilitation has been demonstrated in a number of studies. This paper provides a literature review of BMF systems in sports and rehabilitation. Our motivation was to examine the history of the field to capture its evolution over time, particularly how technologies are used and implemented in BMF systems, and to identify the most recent studies showing novel solutions and remarkable implementations. We searched for papers in three research databases: Scopus, Web of Science, and PubMed. The initial search yielded 1167 unique papers. After a rigorous and challenging exclusion process, 144 papers were eventually included in this report. We focused on papers describing applications and systems that implement a complete real-time feedback loop, which must include the use of sensors, real-time processing, and concurrent feedback. A number of research questions were raised, and the papers were studied and evaluated accordingly. We identified different types of physical activities, sensors, modalities, actuators, communications, settings and end users. A subset of the included papers, showing the most perspectives, was reviewed in depth to highlight and present their innovative research approaches and techniques. Real-time BMF has great potential in many areas. In recent years, sensors have been the main focus of these studies, but new types of processing devices, methods, and algorithms, actuators, and communication technologies and protocols will be explored in more depth in the future. This paper presents a broad insight into the field of BMF.

This study explores the application of wireless wearable devices within the emerging domain of biomechanical feedback systems for sports and rehabilitation. A critical aspect of these systems is the need for real-time operation, where wearable devices must execute multiple processes concurrently while ensuring specific tasks are performed within precise time constraints. To address this challenge, we developed a specialized, lightweight periodic scheduler for microcontrollers. Extensive testing under various conditions demonstrated that sensor sampling frequencies of 650 Hz and 1750 Hz are achievable when utilizing one and 26 sensor samples per packet, respectively. Receiver delays were observed to be a few milliseconds or more, depending on the application scenario. These findings offer practical guidelines for developers and practitioners working with real-time biomechanical feedback systems. By optimizing sensor sampling frequencies and packet configurations, our approach enables more responsive and accurate feedback for athletes and patients, improving the reliability of motion analysis, rehabilitation monitoring, and training assessments. Additionally, we outline the limitations of such systems in terms of transmission delays and jitter, providing insights into their feasibility for different real-world applications.

This study explores the application of wireless wearable devices within the emerging domain of biomechanical feedback systems for sports and rehabilitation. A critical aspect of these systems is the need for real-time operation, where wearable devices must execute multiple processes concurrently while ensuring specific tasks are performed within precise time constraints. To address this challenge, we developed a specialized, lightweight periodic scheduler for microcontrollers. Extensive testing under various conditions demonstrated that sensor sampling frequencies of 650 Hz and 1750 Hz are achievable when utilizing 1 and 26 sensor samples per packet, respectively. Receiver delays were observed to be a few milliseconds or more, depending on the application scenario. These findings offer practical guidelines for developers and practitioners working with real-time biomechanical feedback systems. By optimizing sensor sampling frequencies and packet configurations, our approach enables more responsive and accurate feedback for athletes and patients, improving the reliability of motion analysis, rehabilitation monitoring, and training assessments. Additionally, we outline the limitations of such systems in terms of transmission delays and jitter, providing insights into their feasibility for different real-world applications.

Aquatic environments impose strong constraints on conventional feedback channels and challenge the deployment of wearable human–machine interfaces. This paper presents the design, characterization, and field validation of a head-worn vibrotactile interface intended for symbolic cue delivery during swimming. The proposed platform consists of a waterproof wearable node, six individually controlled actuators, a custom driver, and a host-side control application that uses a lightweight protocol and autonomous execution to tolerate intermittent wireless connectivity after submersion. Actuator operation was characterized under deployment conditions. Symbolic cues were encoded using spatial and sequential activation patterns and validated in a field protocol with 51 competitive swimmers. To enable practical scoring without additional underwater motion instrumentation, each cue was mapped to an externally observable response. After familiarization with a six-symbol cue–response vocabulary, participants produced the predefined observable responses with 96.96% overall task-level accuracy, with 99.35% in the initial out-of-water trial and 94.55% in the subsequent in-water trial following symbol familiarizing and training. Because trial order was fixed, the between-trial difference cannot be attributed exclusively to the aquatic medium. Symbol-level analysis showed that front-actuator and crawl cues were the most robust. Secondary user evaluation results indicated that the prototype was understandable and tolerable during short sessions. These results support the feasibility of trained symbolic vibrotactile cue delivery for a compact six-cue vocabulary in one head-mounted configuration in aquatic environments and provide an engineering foundation for future closed-loop aquatic feedback systems.