IEEE journal of biomedical and health informatics
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IEEE J Biomed Health Inform · May 2017
A Wearable Thermometry for Core Body Temperature Measurement and Its Experimental Verification.
A wearable thermometry for core body temperature (CBT) measurement has both healthcare and clinical applications. On the basis of the mechanism of bioheat transfer, we earlier designed and improved a wearable thermometry using the dual-heat-flux method for CBT measurement. In this study, this thermometry is examined experimentally. ⋯ LTM shows no significant difference in parameters for the inference of circadian rhythm. The FCCM and LTM both simulated scenarios in which this thermometry could be used for intensive monitoring and daily healthcare, respectively. The results suggest that because of its convenient design, this thermometry may be an ideal choice for conventional CBT measurements.
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IEEE J Biomed Health Inform · May 2017
ECG Denoising Using Marginalized Particle Extended Kalman Filter With an Automatic Particle Weighting Strategy.
In this paper, a model-based Bayesian filtering framework called the "marginalized particle-extended Kalman filter (MP-EKF) algorithm" is proposed for electrocardiogram (ECG) denoising. This algorithm does not have the extended Kalman filter (EKF) shortcoming in handling non-Gaussian nonstationary situations because of its nonlinear framework. In addition, it has less computational complexity compared with particle filter. ⋯ In addition, the impact of the proposed filtering method on the distortion of diagnostic features of the ECG was investigated and compared with EKF/EKS methods using an ECG diagnostic distortion measure called the "Multi-Scale Entropy Based Weighted Distortion Measure" or MSEWPRD. The results revealed that our proposed algorithm had the lowest MSEPWRD for all noise types at low input SNRs. Therefore, the morphology and diagnostic information of ECG signals were much better conserved compared with EKF/EKS frameworks, especially in non-Gaussian nonstationary situations.