ABSTRACT
We report a case of sleep terrors complicated with sleepwalking. The patient was 9-year-old boy who suddenly woke up, walked, or screamed in his sleep. These symptoms were sometimes induced by such as fever elevation or school events. In order to prevent injury while sleeping, he was suggested taking medicine to suppress the nocturnal behavior. After taking shokenchuto based on his findings of qi deficiency, the episodes gradually disappeared and the frequency of fever elevation decreased. In this report, we present the improvements of sleep parameters provided by overnight polysomnography, performed before and after treatment. Shokenchuto is known as one of the curative medicines for sleep terrors, but this is the first report showing objective therapeutic effects using overnight polysomnography.
ABSTRACT
This letter presents an automated obstructive sleep apnoea (OSA) detection method with high accuracy, based on a deep learning framework employing convolutional neural network. The proposed work develops a system that takes single lead electrocardiography signals from patients for analysis and detects the OSA condition of the patient. The results show that the proposed method has some advantages in solving such problems and it outperforms the existing methods significantly. The present scheme eliminates the requirement of separate feature extraction and classification algorithms for the detection of OSA. The proposed network performs both feature learning and classifies the features in a supervised manner. The scheme is computation-intensive, but can achieve very high degree of accuracy—on an average a margin of more than 9% compared to other published literature till date. The method also has a good immunity to the contamination of the signals by noise. Even with pessimistic signal to noise ratio values considered here, the methods already reported are not able to outshine the present method. The software for the algorithm reported here can be a good contender to constitute a module that can be integrated with a portable medical diagnostic system.
Subject(s)
Humans , Classification , Electrocardiography , Learning , Methods , Noise , Signal-To-Noise RatioABSTRACT
Objective To extract breathing pattern parameters during sleep and get the varying law of NREM and REM sleep stages. Method A newly designed respiratory inductive plethysmography (RIP) and a polysomnography (PSG) are utilized to record whole-night-sleep data simultaneously. The breathing pattern parameters obtained by RIP are dealt with according to the results of sleep stages and sleep apnea by PSG. Then the rule found out and summarized from the experiment is applied to distinguish REM sleep. Conclusion RC/VT can be used as an effective parameter to differentiate NREM and REM sleep. Using this parameter, the results of RIP totally accord with the results of PSG.
ABSTRACT
AIM To investigate the role of serotonergic projection from dorsal raphe nuclei (DRN) to basolateral amygadaloid (BLA) in the regulation of sleep and waking state. METHODS stereotaxic microinjection and polysomnography were employed. RESULTS Microinjection of L Glu into the DRN caused an enhancement of wake (W) and a decrease of slow wave sleep (SWS) and paradoxical sleep (PS). However, microinjection of L Glu into the DRN plus bilateral microinjection of methysergide (MS) into the BLA reversed the effects of L Glu. Microinjection of PCPA into the DRN caused an enhancement of SWS and a decrease of W. Microinjection of PCPA into the DRN plus bilateral microinjection of 5 HTP into the BLA reversed the effects of PCPA. CONCLUSION These results suggest that the role of the DRN in the regulation of sleep and waking state is partly mediated by serotonergic projection from the DRN to the BLA.