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Evaluating the Impact of Sleep Disruptions in Women through Automated Analysis
Published in Erick C. Jones, Supply Chain Engineering and Logistics Handbook, 2020
Shalini Gupta, Felicia Jefferson, Erick C. Jones
OSA is a common sleep disorder that is caused by complete or partial functional impairment of the upper airway dilator muscle, which leads to apnea/hypopnea-induced oxygen desaturation, repetitive micro-arousals, and disturbed sleep [3]. Thus, OSA patients suffer from sleep fragmentation and chronic sleep deprivation, with common symptoms of daytime sleepiness, tiredness, snoring, etc. [6]. When adequate apnea and hypopnea episodes are present together with these symptoms, OSA is labeled as obstructive sleep apnea syndrome (OSAS) [16]. Various factors have been identified as predictors of OSA including oropharyngeal narrowing, neck circumference, and BMI. In general, factors that predispose individuals to increased collapsibility of the upper airway are major risk factors for OSA [20]. Among all of them, obesity is the greatest risk factor for OSA due to its high prevalence [21]. Clinical diagnosis of OSA requires baseline polysomnography (PSG) of patients and a Continuous Positive Airway Pressure (CPAP) titration study, while home studies are increasingly being used as screening tests [34].
A study of poultry realtime monitoring and automation techniques
Published in Arun Kumar Sinha, John Pradeep Darsy, Computer-Aided Developments: Electronics and Communication, 2019
A. Arun Gnana Raj, S. Margaret Amala, J. Gnana Jayanthi
Sungho Kaneshiro and Yasue Mitsukura [10] has proposed respiratory sound analysis for Continuous Positive Airway Pressure Machines. Continuous positive airway pressure (CPAP) is a medical treatment for obstructive sleep apnoea syndrome. For CPAP, it is necessary to monitor the respiratory sounds such as, inspiration, expiration, and snoring to supply proper pressure depending on the respiratory conditions of patients. As the first step, short-time Fourier transform is applied to each channel of observed microphone signals for selectively acquiring directional signals and then for extracting time-frequency (T-F) features. Different features can be extracted in the time-frequency magnitude spectrogram. Now compare the sound features of inspiration and expiration produced by the microphones, 50 Hz notch filter has been applied and the data will be divided into epoch. For separate respiratory sounds and CPAP machine noise the degenerate un-mixing estimation technique (DUET) has been used. The experiments clearly shows that the amplitude and frequency bands are different between the inspiration and expiration states. So that the inspiration and expiration can be easily identified.
Sleep Disorders
Published in John A. Caldwell, J. Lynn Caldwell, Fatigue in Aviation, 2016
John A. Caldwell, J. Lynn Caldwell
A sleep apnea is defined as the cessation of breathing during sleep for at least ten seconds. The sleep of a normal person contains as many as five sleep apneas per hour (the number per hour is called the apnea index) without any residual effects on health or daytime alertness. However, when the apnea index increases to as much as 20 or more, then both health and daytime alertness suffer. Apnea events result from airway constrictions that are so tight that they do not allow enough oxygen for normal breathing to come through. These obstructions lead to snoring and gasping, but also to sleep disruption because the oxygen-deprived sleeper usually reacts to the lack of oxygen with a jerk that produces a shift into a lighter sleep stage (or a complete awakening). As these events occur throughout the night, sleep becomes fragmented and non-restorative. The severity of the symptoms is linked to the severity of the apnea. A person with severe sleep apnea can stop breathing over 100 times an hour, with episodes lasting as long as 60 seconds. A person with minor sleep apnea may stop breathing only ten times an hour with each episode lasting only ten seconds.
Multi-dimensional readiness assessment of medical devices
Published in Theoretical Issues in Ergonomics Science, 2023
Rosemary Ruiz Seva, Angela Li Sin Tan, Lourdes Marie Sequerra Tejero, Maria Lourdes Dorothy S. Salvacion
The lack of a usability study can result in technical glitches and patient mortality as in the Therac-25 accidents with patients suffering severe radiation burns (Leveson 1995; Leveson and Turner 1993). Some MDs are designed to be used alone by the patient at home or with the aid of a caregiver. A case in point is the Continuous Positive Airway Pressure (CPAP) machine used for sleep apnea, a potentially serious disorder. The correct setup of the device and proper fitting of the mask on the face is important to ensure that the MD will deliver the continuous positive pressure to the airways for the entire duration of sleep. A usability study conducted on this MD showed that patients find it difficult to get it ready for use, and caregivers find it hard to maintain (Fung et al. 2015).
Validation of a numerical model for the mechanical behavior of a continuous positive airway pressure mask
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2022
Francesco Genna, Nicola Francesco Lopomo, Fabio Savoldi
Continuous Positive Airway Pressure (CPAP) masks are adopted to treat several medical conditions including respiratory failure associated with COVID-19 infection (Nightingale et al. 2020) and obstructive sleep apnea (McEvoy et al. 2016). The standard use implies their placement over the face of the subject, tensioning and fastening a headgear around the head, and keeping the device on under air pumping through an intake tube (Kushida et al. 2006). The tension in the headgear bands, necessary both to keep the mask in position and to guarantee a good sealing so as to limit air leakage, can however be the source of possibly severe problems deriving from the long duration and the relatively high intensity of the involved forces, including device-related pressure ulcers (Gefen and Ousey 2020) and dentofacial deformities (Tsuda et al. 2010).
Respiratory Effort Signal Based Sleep Apnea Detection System Using Improved Random Forest Classifier
Published in IETE Journal of Research, 2021
Anju Prabha, Jyoti Yadav, Asha Rani, Vijander Singh
Sleep apnea (SA) is a major sleep disorder; an SA event is marked when there is a drop in the peak amplitude of the airflow signal for more than 10 s [1]. Obstructive sleep apnea (OSA) is caused by a complete or partial blockage of the upper airway due to the throat muscles collapse, enlarged tonsils or infections in respiratory tract, etc. [2]. Central sleep apnea (CSA) is characterized by the lack of drive from the central nervous system to the respiratory muscles [3]. Sleep-wake cycles are regulated by the interplay of the circadian rhythm and homeostatic drive to sleep [4]. Hence, lack of sleep can impair cardiovascular and homeostatic regulatory systems in the long term and lead to heart failure, stroke and hypertension, etc. Around 1 billion adults suffer from OSA in the world and India ranks 4th for most cases [5,6].