Modeling of Noisy Acceleration Signals from Quasi-periodic Movements for Drift-free Position Estimation.

OBJECTIVE: We present a novel approach to drift-free position estimation from noisy acceleration signals which often arise from quasi-periodic small-amplitude body movements. In contrast to the existing methods, this data-driven strategy is designed to properly describe time-variant harmonic structures in single-channel acceleration signals for low signal-to-noise ratios.

METHODS: It comprises three processing steps: (1) short-time modeling of acceleration dynamics (instantaneous harmonic amplitudes and phases) in the analysis frame, (2) analytical integration which yields short-time position, and (3) overlap-add recombination for full length position synthesis.

RESULTS: The comparative results, obtained from the medio-lateral X-acceleration components from 30s Chair Stand Test recordings, suggest that the proposed method outperforms two state-of-the-art reference methods in terms of Euclidean error, root mean square error, correlation coefficient and harmonic-to-noise ratio.

CONCLUSION: A major benefit of the method is that acceleration signal components unrelated to movement are suppressed in the whole analysis bandwidth, which allows for position estimation completely free of low-frequency artifacts.

SIGNIFICANCE: We believe that the method can be useful in frailty assessment in elderly population, as well as in clinical applications related to gait analysis in aging and rehabilitation.