THE REAL TIME GAIT PHASE DETECTION FOR LOWER LIMBS USING IOT TECHNOLOGY

Abstract

Stroke has been recognized as a major public health concern, being the third most common cause of mortality and topping the nation's disability rate. Stroke patients have difficulty walking and moving to the point of endangering areas of the brain that control movement coordination when brain impulses become chaotic, and muscles may find it difficult to communicate effectively. The gait sensor function can measure various characteristics of the human gait with the movement signal recorded and used to perform the gait analysis. The goal of this product is to obtain real-time run phase performance using wearable sensors and IoT technology by tracking the number of steps generated by the patient. The movement signals recorded by these sensors are used to perform gait analysis and can be used as analytical data such as number of steps, cadence, and length of steps to obtain information about the level of progress achieved by stroke patients. Combining with a motorized walker will aid stroke patients' movement during treatment and can encourage them to walk at an appropriate speed. Based on the effectiveness of the tools that have been measured throughout, the patient can produce and display progress in graph form. From this study, several improvements can be made to improve the usability of the device in the future