Gait monitoring and walk distance estimation with an accelerometer during 6-minute walk test

Abstract

BACKGROUND: The 6-min walk test (6MWT) encompasses potential and untapped information related to exercise capacity. However, this test does not yield any information about gait pattern. Recently, we used a ventilatory polygraph to reveal respiratory adaptation during the 6MWT with subjects having high or low body mass index (BMI). In this study, we aimed to determine gait parameters with the same device, which integrates an accelerometer. METHODS: Using a 30-m corridor, steps and U-turns were detected with a custom-made algorithm, compared to video recordings as a reference method, and analyzed offline. From the vertical acceleration signal, we were able to determine cadence and step length, and we could calculate the total distance covered in 6 min (6MWD). We then compared these variables between subjects with low BMI (n = 13 sub-jects) or high BMI (n = 29 subjects). RESULTS: Steps and U-turn detection correlated with video results (r = 0.99, P < .001 for both). The 6MWD calculation was also in line with classical measurements (r = 0.99, P < .001). High BMI subjects had a significantly lower 6MWD, cadence, and step length than controls (P < .001 for each). Walking speed was more closely correlated with step length (r = 0.92) than with cadence (r = 0.64) for both groups. CONCLUSION: Our results demonstrated that a ventilatory polygraph with an embedded accelerometer can be used to detect steps and U-turns, and to calculate 6MWD. This method is sufficiently sensitive to characterize significant BMI-dependent differences in gait pattern during a 6MWT and appears to be a prom-ising tool for routine clinical use.