Research Assistant University of Washington Bangkok, Krung Thep, Thailand
Objectives: Ambulatory individuals with lower limb amputation perform a variety of activities including walking straight on level ground, turning right and left, ascending and descending stairs, and ascending and descending ramps, but their step count distribution is unknown. The purpose of this research is to develop and validate an instrument to measure these activities and report findings on a sample population.
Design: Leg motions were recorded by a portable instrument mounted on or inside a prosthetic pylon. Ambulatory activities were classified by a machine learning algorithm using data collected by the portable instrument. Individuals were recruited to first ambulate a defined course in a hospital environment while video recorded from behind. The course was designed to provide sufficient steps of each activity to train and validate the algorithm. Subjects were then free to pursue their usual activities while the portable instrument continued to collected data over the next 1-2 days. A linear mixed model was used to assess within-subject differences in step counts by locomotor activity.
Results: Ten individuals with unilateral transtibial amputation provided inform consent. All participants were male (mass: 86.2±3.6 kg, height: 1.80±0.03 m, age: 48.7±17.0 years, etiology: 8 trauma, 2 diabetes). The overall classification accuracy was 97.5 ± 1.5%. When free to walk as they pleased, 82.8% of all steps were straight ahead, 9.0% were turning steps, 3.6% were steps on ramps, and 4.8% were steps on stairs.
Conclusions: Approximately four out of every five steps were in a straight line on level ground, one in ten steps involved a turn, one in twenty steps were on a stairway, and one in nearly thirty steps were on a ramp. This information may be useful in the development of interventions and treatments intended to facilitate the diverse activities of these individuals in the home, work, and community environments.