Feasibility study on iPhone accelerometer for gait detection

Falls amongst the elderly is becoming a major problem with over 50% of elderly hospitalizations due to injury from fall related accidents. Healthcare expenses are dramatically rising due to growing elderly population. Many current technologies for gait analysis are laboratory-based and can incur substantial costs for the healthcare sector for treatment of falls. However utilization of alternative commercially available technologies can potentially reduce costs. Accelerometers are one such option, being ambulatory motion sensors for the detection of orientation and movement. Smart mobile devices are considered as non-invasive and increasingly contain accelerometers for detecting device orientation. This study looks at the capabilities of the accelerometer within a smart mobile device, namely the iPhone, for identification of gait events from walking along a flat surface. The results prove that it is possible to extract features from the accelerometer of an iPhone such as step detection, stride time and cadence.