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“Musica delenit bestiam feram” translates into “Music soothes the savage beast”. There is a hidden truth in this ancient quip passed down from generations. Besides soothing the heart, it also incites the heart to a healthier level of heart rate variability (HRV). In this paper, an approach to use and test music and biofeedback to increase the heart rate variability for people facing daily stress is...
Respiratory rate (RR) is an important measurement for ambulatory care and there is high interest in its detection using unobtrusive mobile devices. For this study, we investigated the estimation of RR from a photoplethysmography (PPG) signal that originated from a pulse oximeter sensor and had a sub-optimal sampling rate. We explored the possibility of estimating RR by extracting respiratory sinus...
This case study centered on the effects of Music Therapy (MT) on vegetative state (VS) patients for a continuous 41-day experiment with electrocardiogram (ECG) recorded. Mahler's Second Symphony was used for this MT. There are various elements in Mahler's second symphony, with string, wind, drum, and even voice; providing the subject a strong and dynamic stimulation. There are some significant changes...
This study investigates the interplay among heart rate variability (HRV), respiration, and the severity of motion sickness (MS) in a realistic passive driving task. Although HRV is a commonly used metrically in physiological research or even believed to be a direct measure of sympathovagal activities, the results of MS-effected HRV remain mixed across studies. The goal of this study is to find the...
Results of heart rate variability analysis depend on the quality of the initial RR time series that is measured only in one lead of the ECG. This work shows that RR time series can subtly change from lead to lead so the choice of the analyzed lead is another source of uncertainty. The standard deviation of the differences of two RR time series obtained from different leads can change from 0.5 ms to...
This paper discusses the effect of atrioventricular conduction time (AVCT) on the short-term Heart Rate Variability (HRV) by computing HRV parameters using intervals between the onsets of successive P waves (PP time series) for three groups: normal, arrhythmia and sudden cardiac death (SCD) patients. A very precise wavelet transform based ECG delineator was developed to detect PP, PR and RR time series...
Autonomic nervous system regulates the behavior of cardiac and respiratory systems. Its assessment during the ventilator weaning can provide information about physio-pathological imbalances. This work proposes a non linear analysis of the complexity of the heart rate variability (HRV) and breathing duration (TTot) applying recurrence plot (RP) and their interaction joint recurrence plot (JRP). A total...
Ectopic beats are early heart beats with remarkable large amplitude that provoke serious disturbances in the analysis of electrocardiograms (ECG). These beats are very common in atrial fibrillation (AF) and are the source of important residua when the QRST is intended to be removed. Given that QRST cancellation is a binding step in the appropriate analysis of atrial activity (AA) in AF, a method for...
The quality of automated real-time critical care monitoring is impacted by the degree of signal artifact present in clinical data. This is further complicated when different clinical rules applied for disease detection require source data at different frequencies and different signal quality. This paper proposes a novel multidimensional framework based on service oriented architecture to support real-time...
This paper investigates the viability of using the dynamic Bayesian Network framework as a tool to classify heart beats in long term ECG records. A Decision Support System composed by two layers is considered. The first layer performs the segmentation of each heartbeat available in the ECG record, whereas the second layer classifies the heartbeat as Premature Ventricular Contraction (PVC) or Other...
Atrial fibrillation (A-fib) is the most common cardiac arrhythmia. To effectively treat or prevent A-fib, automatic A-fib detection based on Electrocardiograph (ECG) monitoring is highly desirable. This paper reviews recently developed techniques for A-fib detection based on non-episodic surface ECG monitoring data. A-fib detection methods in the literature can be mainly classified into three categories:...
In this paper we associate features obtained from ECG signals with the expected levels of stress of real firefighters in action when facing specific events such as fires or car accidents. Five firefighters were monitored using wearable technology collecting ECG signals. Heart rate and heart rate variability features were analyzed in consecutive 5-min intervals during several types of events. A questionnaire...
Diabetic cardiac autonomic neuropathy (DCAN) is one of the most common complications of diabetes. One reason why the pathogenesis of DCAN is unclear is that non-invasive assessment of DCAN in humans and animals has been problematic. To overcome this limitation, we utilized a sensitive and non-invasive method to assess cardiac autonomic dysregulation from ECG records. The method, which could be easily...
The analysis of the surface Electrocardiogram (ECG) is the most extended noninvasive technique in cardi-ological diagnosis. In order to properly use the ECG, we need to cancel out ectopic beats. These beats may occur in both normal subjects and patients with heart disease, and their presence represents an important source of error which must be handled before any other analysis. This paper presents...
We present a novel, automatic point-process approach that is able to provide continuous, instantaneous estimates of heart rate variability (HRV) and respiratory sinus arrhythmia (RSA) in long duration data recordings such as those during an entire night of sleep. We analyze subjects with and without sleep apnea who underwent diagnostic polysomnography. The proposed algorithm is able to quantify multi-scale...
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