A Wearable Sensor -Based System for Real Time Posture Correction in Physiotherapy Sessions

This study introduces a wearable sensor-based system that can be used to provide real time posture correction during the physiotherapy. This system has machine learning algorithms that process posture data measured and recorded by wearable sensors to provide accurate tracking and adjustment of body posture. The tools used are the Inertial Measurement Units (IMUs), which are major devices which record real time information on body movement such as the acceleration and angular velocity of most important body parts such as the back, neck, and wrists. It is the use of sensor data as input to machine learning models that is trained to identify when a person is not in their ideal posture, which signals the system to provide the user with instant feedback in the form of visual or haptic indicators. The proposed approach gives physiotherapists and patients an active means of enhancing the effectiveness of posture correction, improvement of treatment progress, and the long-term posture awareness. The proposed system is proposed to provide a non-invasive, convenient, and a precise solution to real-time monitoring and adjustment of posture during the therapeutic interventions.

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