Injuries caused by falls are common among athletes. The field of sports mechanics and training are moving towards implementing green technology to evaluate the performance and training of the athletes. There is a need to understand the gait pattern of an individual for better understanding and planning. Gait analyses performed within a laboratory imposes restriction over an individual’s performance, which can influence the gait pattern intended to study. A shoe-integrated sensor system provides the freedom to move the subject freely, while at the same time provides information related to the gait pattern and fall events occur. MEMS sensors integrated shoes are developed to study the gait pattern for wellness monitoring among elders. The fall is detected by comparing the amount of the pressure distribution in the respective sensors with the accelerometer placed around the ankle. In this work, the presence of the abnormality in the gait pattern and the abnormal point are analysed. A shoe system with sensor design and interface with LabVIEW are developed. In case 1, the heel pressure is 35mV, the toe pressure is 9.2mV, acceleration value is 1.3mV and fall is no fall.