IoT-based Gait Monitoring System for Static and Dynamic Classification of Data

The motor capability of a human is an essential factor to perform various tasks. In most cases, a person with health problems such as diabetes is observed to have a declining motor functions. When this declining motor function is not monitored, this may result to severe health problems that may lead to death. There have been many studies that allow the observation and analysis of the gait movement of a person whether he is in static or dynamic state. However, to accurately observe the person's condition, health monitoring is needed. But most monitoring techniques introduced are limited to a certain space and time making it inconvenient for patients and medical practitioners. Thus, this paper will focus on implementing an IoT-based smart system capable of managing, interpreting and storing data from the patient's gait pattern through Inertial Measurement Unit (IMU) sensors. The main contribution of this study is the ability to differentiate whether the person is in static or dynamic motion for that certain period of time and creates a storage of these classifications.