Wearable Pressure Sensor Suit for Real-Time Detection of Incorrect Exercise Techniques

Abstract

In recent times, the popularity of gym culture has witnessed a remarkable surge. The pursuit of a healthier lifestyle, increased awareness of the benefits of regular exercise, and the desire for physical well-being have contributed to the widespread embrace of gym activities. Individuals across diverse age groups and backgrounds are increasingly recognizing the importance of incorporating fitness into their daily routines, leading to a higher interest in gym memberships and fitness classes. One crucial aspect of effective workouts is the importance of exercise form. Whether engaging in weightlifting, cardio exercises, flexibility routines, or even yoga, the proper execution of movements is crucial for maximizing benefits and preventing injuries. Maintaining correct posture, alignment, and technique not only enhances the efficiency of the workout but also safeguards against potential strains and stresses on the body. Recognizing the significance of exercise form, there is a growing demand for innovative solutions that can assist individuals in ensuring they perform exercises correctly. The need for a device that checks and monitors one’s form has become evident in the fitness landscape. This thesis presents a suit that provides real-time feedback, offering guidance on posture, movement range, and overall form during exercises. By integrating this technology into the fitness routine, individuals can optimize their workouts, reduce the risk of injuries, and enhance the overall effectiveness of their training sessions. This innovative suit employs pressure sensors to precisely calculate the flexion of individual muscle groups, thereby assessing the form of exercise. Utilizing piezo-resistive material, namely velostat, for our pressure sensors ensures dynamic responsiveness. The resistance varies proportionally based on the degree of muscle stretching, enabling the identification of over-stretching or under-stretching that may indicate suboptimal form. By comprehensively analyzing data from all sensors, we can accurately evaluate the proficiency of the exercise form. The focus of this thesis centers on a specialized suit designed to analyze the form of the back muscles during various exercises such as squats, deadlifts, and rows. The suit incorporates multiple sensors strategically placed on the back, seamlessly connected to the ESP32 microcontroller. This setup enables real-time feedback, with all necessary calculations performed on the microcontroller itself. Notably, the suit prioritizes user comfort by offering flexibility and durability without any rigid components that might impede the workout experience. Additionally, the suit features a detachable battery, ensuring its complete washability. Impressively, our suit demonstrates an accuracy range of 72% to 90% across the three specified exercises, highlighting its efficacy in precisely evaluating exercise form. This research not only contributes to the growing field of wearable technology in fitness but also underscores the potential for real-time, personalized feedback to enhance users’ workout experiences.