Classifying prosthetic use via accelerometry in persons with transtibial amputations

Knowledge of how persons with amputation use their prostheses and how this use changes over time may facilitate effective rehabilitation practices and enhance understanding of prosthesis functionality. Perpetual monitoring and classification of prosthesis use may also increase the health and quality of life for prosthetic users. Existing monitoring and classification systems are often limited in that they require the subject to manipulate the sensor (e.g., attach, remove, or reset a sensor), record data over relatively short time periods, and/or classify a limited number of activities and body postures of interest. In this study, a commercially available three-axis accelerometer (ActiLife ActiGraph GT3X+) was used to characterize the activities and body postures of individuals with transtibial amputation. Accelerometers were mounted on prosthetic pylons of 10 persons with transtibial amputation as they performed a preset routine of actions. Accelerometer data was postprocessed using a binary decision tree to identify when the prosthesis was being worn and to classify periods of use as movement (i.e., leg motion such as walking or stair climbing), standing (i.e., standing upright with limited leg motion), or sitting (i.e., seated with limited leg motion). Classifications were compared to visual observation by study researchers. The classifier achieved a mean +/- standard deviation accuracy of 96.6% +/- 3.0%.