IEEE journal of biomedical and health informatics
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IEEE J Biomed Health Inform · May 2015
Signal-quality indices for the electrocardiogram and photoplethysmogram: derivation and applications to wireless monitoring.
The identification of invalid data in recordings obtained using wearable sensors is of particular importance since data obtained from mobile patients is, in general, noisier than data obtained from nonmobile patients. In this paper, we present a signal quality index (SQI), which is intended to assess whether reliable heart rates (HRs) can be obtained from electrocardiogram (ECG) and photoplethysmogram (PPG) signals collected using wearable sensors. The algorithms were validated on manually labeled data. ⋯ First, we demonstrate that, by using the SQI as a trigger for a power-saving strategy, it is possible to reduce the recording time by up to 94% for the ECG and 93% for the PPG with only minimal loss of valid vital-sign data. Second, we demonstrate how an SQI can be used to reduce the error in the estimation of respiratory rate (RR) from the PPG. The performance of the two applications was assessed on data collected from a clinical study on hospital patients who were able to walk unassisted.
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IEEE J Biomed Health Inform · Jan 2015
Clinical TrialBeta-band frequency peaks inside the subthalamic nucleus as a biomarker for motor improvement after deep brain stimulation in Parkinson's disease.
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) remains an empirical, yet highly effective, surgical treatment for advanced Parkinson's disease (PD). DBS outcome depends on accurate stimulation of the STN sensorimotor area which is a trial-and-error procedure taking place during and after surgery. Pathologically enhanced beta-band (13-35 Hz) oscillatory activity across the cortico-basal ganglia pathways is a prominent neurophysiological phenomenon associated with PD. ⋯ Good (poor) DBS responders had, in average, 1 mm (3.5 mm) vertical distance between the maximum beta-peak weighted across the parallel microelectrodes and the center of the stimulation area. The distances were statistically different in the two groups ( p = 0.0025 ). Our biomarker could provide personalized intra- and postoperative support in stimulating the STN sensorimotor area associated with optimal long-term clinical benefits.
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IEEE J Biomed Health Inform · Jan 2015
Clinical TrialImproving compliance in remote healthcare systems through smartphone battery optimization.
Remote health monitoring (RHM) has emerged as a solution to help reduce the cost burden of unhealthy lifestyles and aging populations. Enhancing compliance to prescribed medical regimens is an essential challenge to many systems, even those using smartphone technology. In this paper, we provide a technique to improve smartphone battery consumption and examine the effects of smartphone battery lifetime on compliance, in an attempt to enhance users' adherence to remote monitoring systems. ⋯ We tested the battery optimization technique in an in-lab pilot study and validated its effects on compliance in the Women's Heart Health Study. The battery optimization technique enhanced the battery lifetime by 192% on average, resulting in a 53% increase in compliance in the study. A system like WANDA-CVD can help increase smartphone battery lifetime for RHM systems monitoring physical activity.
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IEEE J Biomed Health Inform · Jan 2015
Quantification of wave reflection using peripheral blood pressure waveforms.
This paper presents a novel minimally invasive method for quantifying blood pressure (BP) wave reflection in the arterial tree. In this method, two peripheral BP waveforms are analyzed to obtain an estimate of central aortic BP waveform, which is used together with a peripheral BP waveform to compute forward and backward pressure waves. These forward and backward waves are then used to quantify the strength of wave reflection in the arterial tree. ⋯ The feasibility of the proposed method was examined in an experimental swine subject under a wide range of physiologic states and in 13 cardiac surgery patients. In the swine subject, the method was comparable to the reference method based on central aortic BP and flow. In cardiac surgery patients, the method was able to estimate forward and backward pressure waves in the absence of any central aortic waveforms: on the average, the root-mean-squared error between actual versus computed forward and backward pressure waves was less than 5 mmHg, and the error between actual versus computed reflection index was less than 0.03.
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IEEE J Biomed Health Inform · Sep 2014
Autoregressive hidden Markov models for the early detection of neonatal sepsis.
Late onset neonatal sepsis is one of the major clinical concerns when premature babies receive intensive care. Current practice relies on slow laboratory testing of blood cultures for diagnosis. A valuable research question is whether sepsis can be reliably detected before the blood sample is taken. ⋯ Both learning and inference carefully use domain knowledge to extract the baby's true physiology from the monitoring data. Our model can produce real-time predictions about the onset of the infection and also handles missing data. We evaluate the effectiveness of the AR-HMM for sepsis detection on a dataset collected from the Neonatal Intensive Care Unit at the Royal Infirmary of Edinburgh.