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 2011
Cardiac sounds from a wearable device for sternal seismocardiography.
Seismocardiography is the body-surface recording of vibrations produced by the beating heart. A high frequency (HF) accelerometric component of the seismocardiogram (SCG) is related to the heart sounds generated by the closure of atrio-ventricular and semilunar valves. This paper evaluates the feasibility of recording the SCG component associated to cardiac sounds by means of a wearable device originally designed for monitoring ECG, respiratory movements, body accelerations and posture in freely moving subjects. ⋯ They also show significant differences in the HF component of SCG between supine and standing postures. Analyzing the HF SCG in a volunteer sleeping at high altitude (4554 m asl) substantial differences were also found among three body positions (lying supine or on the left or right side). These differences are likely to reflect changes in cardiac mechanics induced by different postures of the body.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2011
Wavelet-based features for characterizing ventricular arrhythmias in optimizing treatment options.
Ventricular arrhythmias arise from abnormal electrical activity of the lower chambers (ventricles) of the heart. Ventricular tachycardia (VT) and ventricular fibrillation (VF) are the two major subclasses of ventricular arrhythmias. While VT has treatment options that can be performed in catheterization labs, VF is a lethal cardiac arrhythmia, often when detected the patient receives an implantable defibrillator which restores the normal heart rhythm by the application of electric shocks whenever VF is detected. ⋯ This might eventually lead to an objective way of analyzing arrhythmias in the overlap zone and computing their degree of affinity towards VT or VF. A database of 24 human ventricular arrhythmia tracings obtained from the MIT-BIH arrhythmia database was analyzed and wavelet-based features that demonstrated discrimination between the VT, VF, and VT-VF groups were extracted. An overall accuracy of 75% in classifying the ventricular arrhythmias into 3 groups was achieved.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2011
Wavelet transform cardiorespiratory coherence detects patient movement during general anesthesia.
Heart rate variability (HRV) may provide anesthesiologists with a noninvasive tool for monitoring nociception during general anesthesia. A novel wavelet transform cardiorespiratory coherence (WTCRC) algorithm has been developed to calculate estimates of the linear coupling between heart rate and respiration. WTCRC values range from 1 (high coherence, no nociception) to 0 (low coherence, strong nociception). ⋯ Values below this threshold were treated as successful detection. The algorithm was found to detect movement with sensitivity ranging from 95% (minimum WTCRC) to 65% (average WTCRC). The WTCRC algorithm thus shows promise for noninvasively monitoring nociception during general anesthesia, using only heart rate and respiration.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2011
The frequency of saccades correlates to peak velocity in symmetrical disparity vergence.
A pure vergence stimulus requires the two eyes to turn equally inward or outward theoretically resulting in a pure symmetrical vergence response. However, saccades, a rapid conjugate eye movement, are frequently observed in vergence responses. This investigation sought to systematically quantify whether the occurrence of saccades within symmetrical vergence responses is correlated to vergence peak velocity. ⋯ The occurrence of saccades is negatively correlated to vergence peak velocity. When the velocity is slower, the number of saccades increases. This study suggests that the brain may initiate a saccade to facilitate a slow vergence movement, potentially to allow object recognition before binocular fusion.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2011
EMG contributes to improve Cerebral State Index modeling in dogs anesthesia.
Cerebral State Index (CSI) is a measure of depth of anesthesia (DoA) developed for humans, which is traditionally modeled with the Hill equation and the propofol effect-site concentration (Ce). The CSI has been studied in dogs and showed several limitations related to the interpretation of EEG data. Nevertheless, the CSI has a lot of potential for DoA monitoring in dogs, it just needs to be adjusted for this species. ⋯ In fact, the EMG introduction in CSI model significantly decreased the modeling error: 11.8 [8.6; 15.2] (fuzzy logic) versus 20.9 [16.4; 29.0] (Hill). This work shows that CSI modeling in dogs can be improved using the current human anesthesia set-up, once the EMG signal is acquired simultaneously with the CSI index. However, it does not invalidate the search of new DoA indices more adjusted to use in dog's anesthesia.