On Fall Detection Using Smartphone Sensors

In today’s world there is rapid growth of technology in medical field. Body Sensor Networks are being used hugely for remote monitoring and support for people in need e.g. elderly, children, patients etc. Besides monitoring significant physiological parameters, posture and fall detection related to health monitoring has gained immense popularity. This work focuses on fall detection using accelerometer data as almost all people are nowadays carrying smartphones. A challenge lies in this field i.e. detecting sudden fall of an elderly or a patient because this needs immediate support. Delay can cause havoc to the person in need. This work basically aims to identify fall uniquely. An environment where the proposed algorithm can be deployed is proposed. Accuracy calculation of proposed technique is also given in support.