Development of a step counting algorithm using the ambulatory tibia load analysis system for tibia fracture patients

Introduction: Ambulation can be used to monitor the healing of lower extremity fractures. However, the ambulatory behavior of tibia fracture patients remains unknown due to an inability to continuously quantify ambulation outside of the clinic. The goal of this study was to design and validate an algorithm to assess ambulation in tibia fracture patients using the ambulatory tibial load analysis system during recovery, outside of the clinic. METHODS: Data were collected from a cyclic tester, 14 healthy volunteers performing a 2-min walk test on the treadmill, and 10 tibia fracture patients who wore the ambulatory tibial load analysis system during recovery. RESULTS: The algorithm accurately detected 2000/2000 steps from simulated ambulatory data. During the 2-min walk test, step counts derived from the algorithm and treadmill showed a strong correlation (r(2)>0.98) to the visual (“actual”) step count. Applying the algorithm to continuous data from tibia fracture patients revealed qualitative differences in gait between the initial and later stages of recovery. Additionally, a relatively large standard deviation (≤3000 steps) in the daily average step count indicated a variety of patient ambulatory behaviors. CONCLUSION: The algorithm reported in this study can assess the ambulatory activity of tibia fracture patients during the recovery period.