Implementation of an iPod Application as a Wearable and Wireless Accelerometer System for Identifying Quantified Disparity of Hemiplegic Gait

Wearable and wireless accelerometer applications may alleviate rampant strain on medical resources. In particular wireless accelerometer systems that are also wearable hold the utility to enable gait analysis beyond the confines of gait laboratories in more autonomous and patient representative environments. Preliminary research has demonstrated the capacity for wireless accelerometer devices to quantify and identify meaningful disparities regarding hemiplegic gait. The iPod is equipped with an accelerometer sensor and software permitting robust applications. The research presents an iPod application capable of recording the acceleration waveform of gait and subsequently transmitting the acceleration waveform through wireless Internet connectivity by email. Two tandem operated iPods are mounted to a subject with chronic hemiplegic gait for preliminary engineering proof of concept to demonstrate the capacity of the iPod as a wireless accelerometer platform for identifying quantified disparity of hemiplegic gait. Post-processing and feature extraction of the acceleration waveform yielded three gait parameters, which have been previously demonstrated for identifying quantified disparity of hemiplegic gait. The three parameters: temporal disparity of stance to stance, time averaged acceleration of stance to stance, and the affected leg/unaffected leg ratio for stance to stance time averaged acceleration less the offset demonstrated a considerable degree of accuracy, consistency, and reliability. In comparison between the affected leg and unaffected leg temporal disparity of stance to stance and time averaged acceleration of stance to stance established statistical significance. The iPod application for gait analysis constitutes a wireless accelerometer platform capable of identifying quantified disparity of hemiplegic gait based on post-processing of the acceleration waveform in a statistically significant manner.