Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Adaptive thresholding with inverted triangular area for real-time detection of the heart rate from photoplethysmogram traces on a smartphone.
Photoplethysmogram (PPG) signals acquired by smartphone cameras are weaker than those acquired by dedicated pulse oximeters. Furthermore, the signals have lower sampling rates, have notches in the waveform and are more severely affected by baseline drift, leading to specific morphological characteristics. This paper introduces a new feature, the inverted triangular area, to address these specific characteristics. ⋯ We collected data from 24 volunteers and compared our algorithm in peak detection with two competing algorithms designed for PPG signals, Incremental-Merge Segmentation (IMS) and Adaptive Thresholding (ADT). A sensitivity of 98.0% and a positive predictive value of 98.8% were obtained, which were 7.7% higher than the IMS algorithm in sensitivity, and 8.3% higher than the ADT algorithm in positive predictive value. The experimental results confirmed the applicability of the proposed method.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Respiratory rate estimation from the oscillometric waveform obtained from a non-invasive cuff-based blood pressure device.
The presence of respiratory activity in the electrocardiogram (ECG), the pulse oximeter's photoplethysmo-graphic and continuous arterial blood pressure signals is a well-documented phenomenon. In this paper, we demonstrate that such information is also present in the oscillometric signal acquired from automatic non-invasive blood pressure monitors, and may be used to estimate the vital sign respiratory rate (RR). ⋯ Results demonstrated a good RR estimation accuracy of our method when compared to the reference values extracted from the reference respiration waveforms (mean absolute error of 2.69 breaths/min), which is comparable to existing methods in the literature that extract RR from other physiological signals. The proposed method has been implemented in Java on the Android device for use in an mHealth platform.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
The mixing rate of the arterial blood pressure waveform Markov chain is correlated with shock index during hemorrhage in anesthetized swine.
Identifying the need for interventions during hemorrhage is complicated due to physiological compensation mechanisms that can stabilize vital signs until a significant amount of blood loss. Physiological systems providing compensation during hemorrhage affect the arterial blood pressure waveform through changes in dynamics and waveform morphology. We investigated the use of Markov chain analysis of the arterial blood pressure waveform to monitor physiological systems changes during hemorrhage. ⋯ A change in the mixing rate from baseline estimates was identified during hemorrhage for each animal (median time of 13 min, ~10% estimated blood volume, with minimum and maximum times of 2 and 33 min, respectively). The mixing rate was found to have an inverse correlation with shock index for all 7 animals (median correlation coefficient of -0.95 with minimum and maximum of -0.98 and -0.58, respectively). The Markov chain mixing rate of arterial blood pressure recordings is a novel potential biomarker for monitoring and understanding physiological systems during hemorrhage.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Investigation of photoplethysmography and near infrared spectroscopy for the assessment of tissue blood perfusion.
Pulse Oximetry (PO) and Near Infrared Spectroscopy (NIRS) are among the most widely adopted optical techniques for the assessment of tissue perfusion. PO estimates arterial oxygen saturation (SpO2) by exploiting light attenuations due to pulsatile arterial blood (AC) and constant absorbers (DC) at two different wavelengths. NIRS processes the attenuations of at least two wavelengths to calculate concentrations of Deoxygenated ([HHb]), Oxygenated ([HbO2]), Total Haemoglobin ([tHb]) and Tissue Oxygenation Index (TOI). ⋯ The system adopts both Pulse Oximetry and NIRS principles to calculate SpO2, [HHb], and [HbO2] and [tHb]. The system has been evaluated on the forearm of 10 healthy volunteers during cuff-induced vascular occlusions. The presented system was able to estimate SpO2, [HHb], [HbO2] and [tHb], showing good agreement with state-of-the-art NIRS and conventional PO.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
An adaptive brain-machine interface algorithm for control of burst suppression in medical coma.
Burst suppression is an electroencephalogram (EEG) indicator of profound brain inactivation in which bursts of electrical activity alternate with periods of isoelectricity termed suppression. Specified time-varying levels of burst suppression are targeted in medical coma, a drug-induced brain state used for example to treat uncontrollable seizures. A brain-machine interface (BMI) that observes the EEG could automate the control of drug infusion rate to track a desired target burst suppression trajectory. ⋯ We design an adaptive recursive Bayesian estimator to jointly estimate drug concentrations and system parameters in real time. We construct a controller using the linear-quadratic-regulator strategy that explicitly penalizes large infusion rate variations at steady state and uses the estimates as feedback to generate robust control. Using simulations, we show that the adaptive algorithm achieves precise control of time-varying target levels of burst suppression even when model parameters are initialized randomly, and reduces the infusion rate variation at steady state.