Title | ||
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On the Design and Implementation of A Highly Accurate Pulse Predictor for Exercise Equipment |
Abstract | ||
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This study aims to develop highly accurate heart rate monitoring from the hand-held contact signal within a noisy environment during exercise. Methods: The periodic pattern and uncertainties of a physiological signal are modeled by a Laplacian random process. Based on this statistical model, a highly accurate pulse predictor (HAPPEE) is derived and implemented in real-time on a Cypress PSoC R 5LP development board. A real-time experiment is designed to compare HAPPEE with a commercial heart rate monitor from POLAR R . The percentage of credible estimates and the mean square error (MSE) of credible estimates are reported for experiments with seven healthy subjects. Results: The overall percentage of credible estimates is 99.2% for HAPPEE and 93.6% for POLAR. The overall MSE of credible estimates is 3.1 for HAPPEE and 7.7 for POLAR. These resuts show that HAPPEE is more accurate than POLAR. Conclusion: HAPPEE is able to accurately monitor heart rate within a noisy environment during exercise. Significance: Unlike existing heart rate estimation methods, HAPPEE does not require pulse detection or tuning parameters. It can be easily implemented in real-time on a low power and low cost development board for exercise equipment and outperforms a commercial heart rate monitor. |
Year | DOI | Venue |
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2015 | 10.1109/TBME.2015.2407155 | Biomedical Engineering, IEEE Transactions |
Keywords | Field | DocType |
exercise equipment,generalized likelihood ratio test,maximum likelihood estimator,band pass filters,real time systems | Simulation,Computer science,Mean squared error,Stochastic process,Pulse (signal processing),Electronic engineering,Exercise equipment,Statistical model,Heart rate,Statistics,PSoC,Heart rate monitor | Journal |
Volume | Issue | ISSN |
PP | 99 | 0018-9294 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
S. Kay | 1 | 309 | 40.73 |
Quan Ding | 2 | 59 | 7.72 |
Dongyang Li | 3 | 1 | 1.38 |