Martin O. Mendez

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An alternative DSS which models the behaviour of the Heart Rate Variability (HRV) signal linked to stable (NREM) and instable (REM) cerebral waves during sleep and a probabilistic model of the sleep stages transitions for decision was developed. Time-Varying Autoregressive Models (TVAMs) were used as feature extractor while Hidden Markov Models (HMM) was(More)
In this paper, an analysis of heart rate variability (HRV) during decreases in the amplitude fluctuations of photopletysmography (PPG) [decreases in the amplitude fluctuations of photopletysmography (DAP)] events for obstructive sleep apnea syndrome (OSAS) screening is presented. Two hundred and sixty-eight selected signal segments around the DAP event were(More)
In this paper, we present a home device for the continuous monitoring of sleep and investigate its reliability regarding sleep evaluation. The system has been particularly designed for healthy people and for preventive purposes. It is not obtrusive and therefore can be used every night without impeding sleep in itself and without interfering with the normal(More)
In this paper, we discuss the possibility of performing a sleep evaluation from signals, which are not usually used for this purpose. In particular, we take into consideration the heart rate variability (HRV) and respiratory signals for automatic sleep staging, arousals detection, and apnea recognition. This is particularly useful for wearable or textile(More)
This paper presents a method for obstructive sleep apnea (OSA) screening based on the electrocardiogram (ECG) recording during sleep. OSA is a common sleep disorder produced by repetitive occlusions in the upper airways and this phenomenon can usually be observed also in other peripheral systems such as the cardiovascular system. Then the extraction of ECG(More)
This study proposes an alternative evaluation of Obstructive Sleep Apnea (OSA) based on ECG signal during sleep time. OSA is a common sleep disorder produced by repetitive occlusions in the upper airways. This respiratory disturbance produces a specific pattern on ECG. Extraction of ECG characteristics, as Heart Rate Variability (HRV) and peak R area,(More)
OBJECTIVE This study aims to identify, starting from a single EEG trace, quantitative distinctive features characterizing the A phases of the Cyclic Alternating Pattern (CAP). METHODS The C3-A2 or C4-A1 EEG leads of the night recording of eight healthy adult subjects were used for this analysis. CAP was scored by an expert and the portions relative to(More)
This study aims to develop an automatic detector of the A phases of the cyclic alternating pattern, periodic activity that generally occurs during non-REM (NREM) sleep. Eight polysomnographic recordings from healthy subjects were examined. From EEG recordings, five band descriptors, an activity descriptor and a variance descriptor were extracted and used to(More)
In the last years we have witnessed the growing interest in the heart rate variability (HRV) signal analysis during sleep. The study of the autonomic regulation during sleep allowed developing methods for automatic detection and classification of some sleep characteristics, both in physiological and pathological conditions. The main problems which require(More)
This study presents different methods for automatic sleep classification based on heart rate variability (HRV), respiration and movement signals recorded through bed sensors. Two methods for feature extraction have been implemented: time variant-autoregressive model (TVAM) and wavelet discrete transform (WDT); the obtained features are fed into two(More)