Determination of a Patient's Speed and Stride Length Minimizing Hardware Requirements

Within biomedical engineering, the use of wearable wireless accelerometers for gait analysis can provide useful information for multiple health-related applications. The minimization of hardware for an accurate and simple estimation of the patient's velocity and stride length represents a difficult task. In this paper we propose a new methodology to determine the velocity and stride length of the patient through the application of the wavelet transform to the waist acceleration signal minimizing the hardware requirements. We introduce 4 novel formulations to take into account the trade-off between accuracy and computational costs, showing that an adaptive optimum approach can deliver results with average errors below 5%.

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