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This preliminary study investigated the use of cardiac information or more specifically, heart rate variability (HRV), for automatic deep sleep detection throughout the night. The HRV data can be derived from cardiac signals, which were obtained from polysomnography (PSG) recordings. In total 42 features were extracted from the HRV data of 15 single-night PSG recordings (from 15 healthy subjects)...
The characterisation of functional interdependencies of the autonomic nervous system (ANS) stands an evergrowing interest to unveil electroencephalographic (EEG) and Heart Rate Variability (HRV) interactions. This paper presents a biosignal processing approach as a supportive computational resource in the estimation of sleep dynamics. The application of linear, non-linear methods and statistical tests...
Underwater electrocardiogram (ECG) monitoring currently uses Ag/AgCl electrodes and requires sealing of the electrodes to avoid water intrusion, but this procedure is time consuming and often results in severe irritations or even tearing of the skin. To alleviate these problems, our research team developed hydrophobic electrodes comprised of a mixture of carbon black powder (CB) and polydimethylsiloxane...
Polysomnography (PSG) is the gold standard that manually quantifies the apnea-hypopnea index (AHI) to assess the severity of sleep apnea syndrome (SAS). This study presents an algorithm that automatically estimates the AHI value using a disposable HealthPatchTM sensor. Volunteers (n=53, AHI: 0.1–85.8) participated in an overnight PSG study with patch sensors attached to their chest at three specified...
Insomnia is a condition that affects the nervous and muscular system. Thirty percent of the population between 18 and 60 years suffers from insomnia. The effects of this disorder involve problems such as poor school or job performance and traffic accidents. In addition, patients with insomnia present changes in the cardiac function during sleep. Furthermore, the structure of electroencephalographic...
In this study, we have investigated how the asymmetry of beat-to-beat foetal heart rate variability (fHRV) changes during development after 35 weeks and before 32 weeks of gestation. Noninvasive foetal electrocardiogram (fECG) signals from 78 pregnant women at the gestational age from16 to 41 weeks with normal single pregnancies were analysed. Heart rate asymmetry (HRA) index that measures time asymmetry...
In this work, we introduce a number of models for human circadian phase estimation in ambulatory conditions using various sensor modalities. Machine learning techniques have been applied to ambulatory recordings of wrist actigraphy, light exposure, electrocardiograms (ECG), and distal and proximal skin temperature to develop ARMAX models capturing the main signal dependencies on circadian phase and...
A priori discrimination of high mortality risk amongst congestive heart failure patients constitutes an important clinical stake in cardiology and involves challenging analyses of the temporal dynamics of heart rate variability (HRV). The present contribution investigates the potential of a new multifractal formalism, constructed on wavelet p-leader coefficients, to help discrimination between survivor...
Spectral analysis of fetal heart rate variability could provide information on fetal wellbeing. Unfortunately, fetal heart rate recordings are often contaminated by artifacts. Correction of these artifacts affects the outcome of spectral analysis, but it is currently unclear what level of artifact correction facilitates reliable spectral analysis. In this study, a method is presented that estimates...
Bipolar disorder is a chronic psychiatric condition during which patients experience mood swings among depression, hypomania or mania, mixed state (depression-hypomania) and euthymia, i.e., good affective balance. Nowadays, an objective characterization of the temporal trends of the disease as a response to the pharmacological treatment through physiological signatures, especially during severe episodes,...
Remote detection of cognitive load has many powerful applications, such as measuring stress in the workplace. Cognitive tasks have an impact on breathing and heart rate variability (HRV). We show that changes in physiological parameters during cognitive stress can be captured remotely (at a distance of 3m) using a digital camera. A study (n=10) was conducted with participants at rest and under cognitive...
Physiological sensor based workload estimation technology provides a real-time means for assessing cognitive workload and has a broad range of applications in cognitive ergonomics, mental health monitoring, etc. In this paper we report a study on detecting changes in workload using multi-modality physiological sensors and a novel feature extraction and classification algorithm. We conducted a cognitive...
Heart rate variability (HRV) has been studied as a non-invasive technique to characterize the autonomic nervous system (ANS) regulation of the heart. Non-linear methods based on chaos theory have been used during the last decades as markers for risk stratification. However, interpretation of these nonlinear methods in terms of sympathetic and parasympathetic activity is not fully established. In this...
The reduced Heart Rate Variability (HRV) is believed to be associated with several diseases such as congestive heart failure, diabetes and chronic kidney diseases (CKD). In these cases, HRV biofeedback may be a potential intervention method to increase HRV which in turn is beneficial to these patients. In this work, a real-time Android biofeedback application based on a Bluetooth enabled ECG and thoracic...
Chronic stress detection is an important factor in predicting and reducing the risk of cardiovascular disease. This work is a pilot study with a focus on developing a method for detecting short-term psychophysiological changes through heart rate variability (HRV) features. The purpose of this pilot study is to establish and to gain insight on a set of features that could be used to detect psychophysiological...
The heart rate variability (HRV) is a commonly used method to quantify the sympathetic and the parasympa-thetic modulation of the heart rate. HRV is mainly conducted on electrocardiograms (ECG). However, the use of photo-plethysmography (PPG) as a marker of the autonomic tone is emerging. In this study we investigated the feasibility of deriving pulse rate variability (PRV) using PPG signals recorded...
We sought to better understand the physiology underlying the metrics of heart rate variability (HRV) in trauma patients without serious injury, compared to healthy laboratory controls. In trauma patients without serious injury (110 subjects, 470 2-min data segments), we studied the correlation between sinus arrhythmia (SA) rate, heart rate (HR), and respiratory rate (RR). Most segments with 2.4 <...
Heart Rate variability (HRV) is the inter-beat variability in heart rate and is moderated by the balance of sympathetic and parasympathetic divisions of the autonomic nervous system. Electrocardiography (ECG) can be utilized to obtain Low frequency (LF) to high frequency (HF) ratios that represent sympathetic to parasympathetic response, respectively and these ratios may be increased in people with...
Following natural disasters, accidents, and shocking incidents, some children experience post-traumatic stress disorder (PTSD). The respiration control method, which relaxes the body and mind, may efficiently prevent PTSD. Therefore, we developed a stuffed toy that leads children's respiration using the up-and-down movement of the abdomen to help them relax. We investigated the most appropriate respiration...
Wearable monitoring of heart rate (HR) during physical activity and exercising allows real time control of exercise intensity and training effect. Recently, technologies based on pulse plethysmography (PPG) have become available for personal health management for consumers. However, the accuracy of these monitors is poorly known which limits their application. In this study, we evaluated accuracy...
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