scholarly journals Signal Processing Techniques for Removal of Various Artifacts from Obstructive Sleep Apnea Signals

2019 ◽  
Vol 8 (12) ◽  
pp. 430-435
Keyword(s):  
Signal Processing ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Body Position ◽  
Well Being ◽  
Motion Artifacts ◽  
Obstructive Sleep ◽  
Wide Range ◽  
Processing Techniques ◽  
Signal Processing Techniques

Sleep is judgmental to health and well-being. Deficient quality sleep is similar with a wide range of negative outcomes varies from schizophrenia to cardiovascular disorders. Obstructive sleep apnea is one of the sleep disorders. In order to identify the various syndromes the signals are need to record by using the sensors. Sleep signals are recorded by using the polysomnography (PSG) labs which is the old traditional and gold standard for recording the sleep signals. PhysioNet is a large online medical database that consists of a large collection of recordings of various physiological signals. PhysioNet database consist of sleep apnea database available. Physionet website is a universal service, physionet resource supported by the national institute of health’s National Institute of Biomedical Imaging and Bioengineering (NIBIB) and National Institute of General Medical Sciences (NIGMS). This survey paper aims to bring the different Signal Processing Techniques for Removal of Various Artifacts from Obstructive Sleep Apnea Signals to identify sleep apnea syndrome, because pre-processing is most effective and efficient to reduce unwanted signals from the original sleep signals. While recording the sleep apnea signals various artifacts records along with raw signals either directly or indirectly due to the internal and external sources like Power line interference, Muscle contractions, Electrode contact noise, Motion Artifacts, Baseline wandering, Noise generated by electronic circuits, while breathing and coughing, body position movements etc, and they need to be eliminated in order to acquire genuine health information. So in order to remove there artificats from the sleep signals the signal processing techniques (filtering techniques) are predominantly used for pre-processing of the sleep signals and have been executed in a wide variety of systems for analysis. Filtering of the sleep signal is contingent and should be implemented only when the required statistics remains cryptic

Nocturnal body position in sleeping children with and without obstructive sleep apnea

2007 ◽  
Vol 42 (4) ◽  
pp. 374-379 ◽  
Author(s):  
Ehab Dayyat ◽  
Muna M.A. Maarafeya ◽  
Oscar Sans Capdevila ◽  
Leila Kheirandish-Gozal ◽  
Hawley E. Montgomery-Downs ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Body Position ◽  
Obstructive Sleep

scholarly journals Body Position and Obstructive Sleep Apnea in Children

SLEEP ◽  
2002 ◽  
Vol 25 (1) ◽  
pp. 66-71 ◽  
Author(s):  
Lucila B. Fernandes do Prado ◽  
Xianbin Li ◽  
Richard Thompson ◽  
Carole L. Marcus
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Body Position ◽  
Obstructive Sleep

scholarly journals Adherence to the Mediterranean lifestyle is inversely associated with insomnia presence and severity: cross-sectional analysis in obstructive sleep apnea patients

2020 ◽  
Vol 79 (OCE2) ◽  
Author(s):  
Ioanna Kechribari ◽  
Meropi Kontogianni ◽  
Michael Georgoulis ◽  
Kallirroi Lamprou ◽  
Antonia Kalogera ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Healthy Lifestyle ◽  
Well Being ◽  
Sleep Habits ◽  
Upper Airways ◽  
Lifestyle Habits ◽  
Obstructive Sleep ◽  
The Mediterranean ◽  
Insomnia Symptoms

AbstractInsomnia is the most prevalent sleep disorder and frequently co-occurs with obstructive sleep apnea (OSA), a chronic disease characterized by repetitive pauses of breathing during sleep due to obstructions of the upper airways. The link between lifestyle and sleep quantity and quality is an area of intensive research, however data exploring associations between lifestyle habits and insomnia symptoms are still scarce. The aim of the present study was to investigate the potential association between the level of adherence to the Mediterranean lifestyle (ML), a healthy lifestyle pattern incorporating the prudent Mediterranean diet, adequate physical activity and healthy sleep habits, and insomnia presence and severity. The study sample consisted of 243 adult patients with polysomnography-diagnosed OSA. Participants’ insomnia-related disorders were evaluated through the Athens Insomnia Scale (AIS), an 8-item index ranging from 0 (absence of any sleep-related problem) to 24 (severe degree of insomnia); AIS values of > 6 were used to establish the diagnosis of insomnia. All patients were evaluated with regard to anthropometric indices and lifestyle habits, and adherence to the ML was estimated through the MEDLIFE index, a 28-item index ranging from 0 to 28, with higher values indicating greater proximity to the healthy lifestyle of the Mediterranean region. An inverse correlation was observed between the MEDLIFE index and total AIS (rho = -0.22, p = 0.001), as well as most individual components of AIS, including difficulty in sleep induction (rho = -0.14, p = 0.03), awakenings during the night (rho = -0.2, p = 0.008), short sleep duration (rho = -0.16, p = 0.01), low quality of sleep (rho = -0.13, p = 0.05), low well-being during the day (rho = -0.16, p = 0.02), and low functioning capacity during the day (rho = -0.15, p = 0.02). Patients with insomnia (AIS > 6), compared to those without (AIS ≤ 6), exhibited lower MEDLIFE index values [13 (11–15) vs. 14 (12–15), P = 0.002], had more severe OSA as assessed by the apnea-hypopnea index (AHI) [55 (24–87) vs. 35 (17–57) events/hour, P < 0.001] and tended to have higher body mass index (BMI) [35.0 (30.6–39.7) vs. 32.4 (29.5–38.6) kg/m2, P = 0.06]. According to logistic regression analysis, MEDLIFE index was inversely associated with the presence of insomnia (OR: 0.89, 95%CI: 0.80–0.99, P = 0.04) after adjustment for age, sex, smoking, BMI, daily energy intake and AHI. In conclusion, a higher adherence to the ML is inversely associated with insomnia presence and severity in patients with obstructive sleep apnea. Future research should assess whether this association applies in other samples, as well as whether the ML could be an efficient therapeutic tool alleviating or treating insomnia symptoms.

scholarly journals The Effect of Body Position on Physiological Factors that Contribute to Obstructive Sleep Apnea

SLEEP ◽  
2015 ◽  
Vol 38 (9) ◽  
pp. 1469-1478 ◽  
Author(s):  
Simon A. Joosten ◽  
Bradley A. Edwards ◽  
Andrew Wellman ◽  
Anthony Turton ◽  
Elizabeth M. Skuza ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Body Position ◽  
Physiological Factors ◽  
Obstructive Sleep

scholarly journals Improvement in Obstructive Sleep Apnea With Weight Loss is Dependent on Body Position During Sleep

SLEEP ◽  
2017 ◽  
Vol 40 (5) ◽  
Author(s):  
Simon A. Joosten ◽  
Jun K. Khoo ◽  
Bradley A. Edwards ◽  
Shane A. Landry ◽  
Matthew T. Naughton ◽  
...  
Keyword(s):  
Weight Loss ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Body Position ◽  
Obstructive Sleep

scholarly journals Positional Obstructive Sleep Apnea Syndrome in Elderly Patients

2020 ◽  
Vol 17 (3) ◽  
pp. 1120 ◽  
Author(s):  
Giannicola Iannella ◽  
Giuseppe Magliulo ◽  
Cristina Lo Iacono ◽  
Giulia Bianchi ◽  
Antonella Polimeni ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Elderly Patients ◽  
Classification System ◽  
Body Position ◽  
Sleep Apnea Syndrome ◽  
Positional Therapy ◽  
New Amsterdam ◽  
Obstructive Sleep ◽  
Old Adult

Background The purpose of this study was to evaluate the prevalence of position-dependent obstructive sleep apnea (POSA) in elderly patients (≥65 years old). Adult (range 19-65 years old) and elderly patients were also compared in order to show differences in the incidence of POSA between these two groups of patients. Methods A prospective bi-center study was performed between January 2018 and May 2019. A total of 434 participants underwent polysomnography (PSG) study at home (Embletta MPR). Body position during the PSG recordings was determined. Patients were subdivided in two groups: those aged between 19 and 65 years old (adult patients) and ≥65 years old (elderly patients). POSA patients were defined using Cartwright’s system, Bignold classification, and the new Amsterdam Positional OSA Classification (APOC). Results The prevalence of POSA in elderly patients differed according to the classification system used: 49.3% using Cartwright’s classification system, 20.5% with the Bignold classification, and 22.6%, 38.9%, and 5.4% of APOC 1, APOC 2, and APOC3 sub-classes were respectively identified for the APOC classification system. No difference between adult and elderly patients regarding the prevalence of POSA was observed. No statistical differences emerged between the two groups of patients in terms of supine (p = 0.9) and non-supine AHI (p = 0.4). Conclusions A significant number of elderly patients could be considered treatable with positional therapy according to the APOC classification. However, the efficacy and applicability of positional therapy in elderly patients must be confirmed by further research.

Association of Body Position With Severity of Apneic Events in Patients With Severe Nonpositional Obstructive Sleep Apnea

CHEST Journal ◽  
2000 ◽  
Vol 118 (4) ◽  
pp. 1018-1024 ◽  
Author(s):  
Arie Oksenberg ◽  
Iyad Khamaysi ◽  
Donald S. Silverberg ◽  
Ariel Tarasiuk
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Body Position ◽  
Obstructive Sleep

EVALUATION OF SIGNAL PROCESSING TECHNIQUES IN DISCRIMINATING ECG SIGNALS OF MEN AND WOMEN DURING REST CONDITION AND EMOTIONAL STATES

2018 ◽  
Vol 30 (04) ◽  
pp. 1850028 ◽  
Author(s):  
Ateke Goshvarpour ◽  
Atefeh Goshvarpour ◽  
Ataollah Abbasi
Keyword(s):  
Gender Differences ◽  
Signal Processing ◽  
Emotional States ◽  
Men And Women ◽  
Wide Range ◽  
Significant Difference ◽  
Rest Condition ◽  
Processing Techniques ◽  
The Impact ◽  
Signal Processing Techniques

Great range of electrocardiogram (ECG) signal processing methods can be found in the literature. In addition, the importance of gender differences in physiological activities was also identified in various conditions. This article aims to provide a comprehensive evaluation of linear and nonlinear ECG parameters to indicate suitable signal processing approaches which can show significant differences between men and women. These differences were investigated in two conditions: (i) during rest condition, and (ii) during the affective image inducements. A wide range of parameters from time-, frequency-, wavelet-, and nonlinear-techniques were examined. Applying the Wilcoxon rank sum test, significant differences between two genders were inspected. The analysis was performed on 47 college students at rest condition and while subjects watching four types of affective pictures, including sadness, happiness, fear, and peacefulness. The impact of these emotions on the results was also investigated. The results indicated that 72.95% and 72.61% of all features were significantly different between male and female in rest condition and affective inducements, respectively. In addition, the highest percentage of the significant difference between ECG parameters of men and women was achieved using nonlinear characteristics. Considering all features together, the highest significant difference between two genders was achieved for negative emotions, including sadness and fear. In conclusion, the results of this study emphasized the importance of gender role in cardiac responses during rest condition and different emotional states. Since these gender differences are well manifested by nonlinear signal processing techniques, dynamical gender-specific ECG system may improve the automatic emotion recognition accuracies.

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