Quick on Your Feet: Modifying the Star Excursion Balance Test with a Cognitive Motor Response Time Task.

The Star Excursion Balance Test (SEBT) is a common assessment used across clinical and research settings to test dynamic standing balance. The primary measure of this test is maximal reaching distance performed by the non-stance limb. Response time (RT) is a critical cognitive component of dynamic balance control and the faster the RT, the better the postural control and recovery from a postural perturbation. However, the measure of RT has not been done in conjunction with SEBT, especially with musculoskeletal fatigue. The purpose of this study is to examine RT during a SEBT, creating a modified SEBT (mSEBT), with a secondary goal to examine the effects of muscular fatigue on RT during SEBT. Sixteen healthy young male and female adults [age: 20 ± 1 years; height: 169.48 ± 8.2 cm; weight: 67.93 ± 12.7 kg] performed the mSEBT in five directions for three trials, after which the same was repeated with a response time task using Blazepod™ with a random stimulus. Participants then performed a low-intensity musculoskeletal fatigue task and completed the above measures again. A 2 × 2 × 3 repeated measures ANOVA was performed to test for differences in mean response time across trials, fatigue states, and leg reach as within-subjects factors. All statistical analyses were conducted in JASP at an alpha level of 0.05. RT was significantly faster over the course of testing regardless of reach leg or fatigue state (p = 0.023). Trial 3 demonstrated significantly lower RT compared to Trial 1 (p = 0.021). No significant differences were found between fatigue states or leg reach. These results indicate that response times during the mSEBT with RT is a learned skill that can improve over time. Future research should include an extended familiarization period to remove learning effects and a greater fatigue state to test for differences in RT during the mSEBT.

Wearables for Biomechanical Performance Optimization and Risk Assessment in Industrial and Sports Applications.

Wearable technologies are emerging as a useful tool with many different applications. While these devices are worn on the human body and can capture numerous data types, this literature review focuses specifically on wearable use for performance enhancement and risk assessment in industrial- and sports-related biomechanical applications. Wearable devices such as exoskeletons, inertial measurement units (IMUs), force sensors, and surface electromyography (EMG) were identified as key technologies that can be used to aid health and safety professionals, ergonomists, and human factors practitioners improve user performance and monitor risk. IMU-based solutions were the most used wearable types in both sectors. Industry largely used biomechanical wearables to assess tasks and risks wholistically, which sports often considered the individual components of movement and performance. Availability, cost, and adoption remain common limitation issues across both sports and industrial applications.