This paper proposes a novel method for using accelerometer data to estimate walking step. The modulus maximum of wavelet transform is used to detect the step for the first time. Recently, the most traditional step estimated methods are based on thresholds which depend on subject and
walking condition. However, our proposed method can not only overcome these drawbacks but also avoid noise effectively. To validate the performance of the proposed methods, we test accelerometer data collected from 35 subjects walking under free-living conditions. The experiments shows that
the average accuracy of step estimate is 97.25% which better than threshold-based method. Based on the results of these experiments, is concluded that a tri-accelerometer is a promising tool for the accurate assessment of walking step.
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