A protocol for balance and mobility training via sensorized movement analysis

Movement analysis is crucial for assessing physical and functional capacity in both well-being and sports. Clinical tests like the 30-Second Chair Stand Test (30CST) and the Timed Up and Go (TUG) test are commonly used for lower limb assessment. However, these tests don’t fully capture proprioception, coordination, strength, endurance, and flexibility—factors strongly linked to independence, longevity, and quality of life. The protocol for balance and mobility training created within the framework of the Tuscany Health Ecosystem utilizes sensor technologies and signal processing to analyze data from fitness-related movements. We developed the Squat Test (SQT) and Single Leg Deadlift Test (SLDLT), functional movements mimicking daily activities. This study investigates the impact of visual feedback on physical abilities. One group performs the tests while observing their balance on a monitor displaying foot pressure data from a sensorized mat as visual feedback. Another group performs the tests without this visual feedback. We hypothesize that while visual feedback may initially improve movement scores, it might create a dependency, hindering the development of true proprioceptive awareness and balance improvement; conversely, it can ease the learning of the necessary neuromuscular capabilities to improve the execution of the tests. The final comparison of the results will explain if visual feedback is relevant for motor learning improvement.