Article

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%.

Langue : ANGLAIS