Direct Mobile Coaching as a Paradigm for the Creation of Mobile Feedback Systems

In sports feedback systems, digital systems perform tasks such as capturing, analysing and representing data. These systems not only aim to provide athletes and coaches with insights into performances but also help athletes learn new tasks and control movements, for example, to prevent injuries. However, designing mobile feedback systems requires a high level of expertise from researchers and practitioners in many areas. As a solution to this problem, we present Direct Mobile Coaching (DMC) as a design paradigm and model for mobile feedback systems. Besides components for feedback provisioning, the model consists of components for data recording, storage and management. For the evaluation of the model, its features are compared against state-of-the-art frameworks. Furthermore, the capabilities are benchmarked using a review of the literature. We conclude that DMC is capable of modelling all 39 identified systems while other identified frameworks (MobileCoach, Garmin Connect IQ SDK, RADAR) could (at best) only model parts of them. The presented design paradigm/model is applicable for a wide range of mobile feedback systems and equips researchers and practitioners with a valuable tool.

Review of Real-Time Biomechanical Feedback Systems in Sport and Rehabilitation

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.

DAid pressure socks system: Performance evaluation

BACKGROUND

Plantar pressure measurement has been proven to produce crucial information for gait analysis. Socks with integrated textile pressure sensors are a promising tool for non-obtrusive plantar pressure acquisition and monitoring.

RESEARCH QUESTION

Can the DAid Pressure Socks System be employed for the measurement of plantar pressure and temporal parameters during walking?

METHOD

Plantar pressure measurement was acquired simultaneously by the DAid Pressure Socks System (DPSS) and Pedar® insole measurement system for a normal walking gait of 17 volunteers. The measurement from both systems was processed and gait temporal parameters were calculated. The calculated temporal parameters included stride time, step time, stance time, swing time, single support time, double support time, and cadence. The Intraclass Correlation Coefficient (ICC) was calculated to evaluate the agreement between the plantar pressure measurement and temporal parameters obtained from both systems.

RESULTS

For plantar pressure measurement, excellent agreement (ICC > 0.90) was achieved in approximately 23 % cases, while in roughly 37 %, 27 %, and 13 % cases the agreement was good (ICC > 0.75), moderate (ICC > 0.50), and poor (ICC < 0.50), respectively. The mean relative differences (as a percentage) between the temporal parameter values calculated from the measurement of both systems were 0.80 % (stride time), 3.06 % (step time), 3.15 % (stance time), 5.08 % (swing time / opposite single support time), 14.47 % (double support time), and 0.78 % (cadence).

SIGNIFICANCE

The ICC result calculated for the plantar pressure measurement indicated a reasonable agreement between both systems. Additionally, the relatively low mean difference was observed for 5 out of 6 calculated temporal gait parameters. Consequently, the presented DPSS could be considered as a substitute for the commercial gait analysis tools for applications that do not require great accuracy of the absolute plantar pressure measurement.