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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)...
Obstructive Sleep Apnea (OSA) is the most common form of sleep disorder breathing. It is estimated that this insidious disease affects 15% of the US adult population. Current procedure of diagnosing OSA requires polysomnography (NPSG) conducted in accredited sleep laboratories and the data getting scored by certified sleep technicians, a costly process that is not readily available in all areas. Ultrasonic...
Polysomnography (PSG) studies are considered the “gold standard” for the diagnosis of Sleep Apnoea (SA). Identifying cessations of breathing from long-lasting PSG recordings manually is a labour-intensive and time-consuming task for sleep specialist, associated with inter-scorer variability. In this study a simplified, semi-automatic, three-channel method for detection of SA patients is proposed in...
Infants recovering from general anesthesia are at risk of postoperative apnea (POA), a potentially life threatening event. There is no accurate way to identify which infants will experience POA, and thus all infants with postmenstrual age < 60 weeks are monitored for apnea in hospital postoperatively. Using a comprehensive, automated analysis of the postoperative breathing patterns, we identified...
Obstructive sleep apnea (OSA) is a common respiratory disorder among adults. Recently we have shown that sedentary lifestyle causes an increase in diurnal leg fluid volume (LFV), which can shift into the neck at night when lying down to sleep and increase OSA severity. The purpose of this work was to investigate various metrics that represent baseline fluid retention in the legs and examine their...
Obstructive Sleep Apnea (OSA), defined by shallow breaths or complete cessation of breathing for more than 10s, is a significant contributing factor for the developments of hypertension, myocardial infarction, stroke and neuropsychological impairments. In this study, we have investigated the relation between apnea duration and apnea induced variations in cerebral blood flow velocity (CBFV) concomitant...
Lempel-Ziv Complexity (LZC) has been demonstrated to be a powerful complexity measure in several biomed-ical applications. During sleep, it is still not clear how many samples are required to ensure robustness of its estimate when computed on beat-to-beat interval series (RR). The aims of this study were: i) evaluation of the number of necessary samples in different sleep stages for a reliable estimation...
Evaluation of respiratory activity during sleep is essential in order to reliably diagnose sleep disorder breathing (SDB); a condition associated with serious cardio-vascular morbidity and mortality. In the current study, we developed and validated a robust automatic breathing-sounds (i.e. inspiratory and expiratory sounds) detection system of audio signals acquired during sleep. Random forest classifier...
Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) is a sleep related breathing disorder that has important consequences in the health and development of infants and young children. To enhance the early detection of OSAHS, we propose a methodology based on automated analysis of nocturnal blood oxygen saturation (SpO2) from respiratory polygraphy (RP) at home. A database composed of 50 SpO2 recordings...
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...
A non-contact vision-based system is presented for continuous respiratory rate monitoring. The system identifies feature points in a video feed and tracks them over time. Two methods are presented for comparison — a method which uses principal component analysis (PCA) and a simple averaging approach. These methods condense the feature point trajectories into a compact set of representative signals...
Capnometry is a method to measure carbon dioxide (CO2) in exhaled gas and its use during polysomnography (PSG) for diagnostic of sleep apnea-hypopnea syndrome is expanding. However, some problems exist for using capnometer in combination with other respiratory monitoring devices because capnometry requires additional sampling cannula or airway adapter attached to patients. To resolve these problems,...
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...
The measurement of regularity in the oxygen saturation (SpO2) signal has been suggested for use in identifying subjects with sleep disordered breathing (SDB). Previous work has shown that children with SDB have lower SpO2 regularity than subjects without SDB (NonSDB). Regularity was measured using non-linear methods like approximate entropy (ApEn), sample entropy (SamEn) and Lempel-Ziv (LZ) complexity...
ECG derived respiration (EDR) provides a comfortable measurement of respiration and is recently applied to sleep studies. Nevertheless, the mechanic disturbances due to postural changes or other physical activity during long-term recording is less investigated. In the present study, ECG, impedance-based respiration, and body accelerations were parallel recorded during a series of scheduled postures...
This work aims at studying the usefulness of the spectral information contained in airflow (AF) recordings in the context of Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) in children. To achieve this goal, we defined two spectral bands of interest related to the occurrence of apneas and hypopneas. We characterized these bands by extracting six common spectral features from each one. Two out of...
Obstructive Sleep Apnea is a chronic sleep disorder affecting a large number of the global population. Telemonitoring has been successfully evaluated as an alternative method to traditional care. This paper identifies drawbacks of the current telemonitoring approaches and presents a universal wireless system for continuous monitoring of basic respiration parameters. The proposed system monitors four...
Snoring is one of the representative phenomena of the sleep disorder and detection of snoring is quite important for improving quality of daily human life. The purpose of this research is to define the noises of the ordinary sleep situation and to find its characteristics as a preliminary research of snoring detection. Differently from previous snoring researches, we use a built-in sound recording...
This paper proposes a novel algorithm for automatic detection of snoring in sleep by combining non-contact bio-motion data with audio data. The audio data is captured using low end Android Smartphones in a non-clinical environment to mimic a possible user-friendly commercial product for sleep audio monitoring. However snore detection becomes a more challenging problem as the recorded signal has lower...
Several research groups have developed automated sleep-wakefulness classifiers for night wrist actigraphic (ACT) data. These classifiers tend to be unbalanced, with a tendency to overestimate the detection of sleep, at the expense of poorer detection of wakefulness. The reason for this is that the measure of success in previous works was the maximization of the overall accuracy, disregarding the balance...
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