Search results for: apnea and hypopnea index

Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

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Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

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Authors: Benghenia Hadj Abd El Kader

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Sleep apnea events as obstructive, central, mixed or hypopnea are characterized by frequent breathing cessations or reduction in upper airflow during sleep. An advanced method for analyzing the patterning of biomedical signals to recognize obstructive sleep apnea and hypopnea is presented. In the aim to extract characteristic parameters, which will be used for classifying the above stated (obstructive, central, mixed) sleep apnea and hypopnea, the proposed method is based first on the analysis of polysomnography signals such as electrocardiogram signal (ECG) and electromyogram (EMG), then classification of the (obstructive, central, mixed) sleep apnea and hypopnea. The analysis is carried out using the wavelet transform technique in order to extract characteristic parameters whereas classification is carried out by applying the SVM (support vector machine) technique. The obtained results show good recognition rates using characteristic parameters.

Keywords: obstructive, central, mixed, sleep apnea, hypopnea, ECG, EMG, wavelet transform, SVM classifier

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Authors: L. Korpinen, T. Kava, I. Salmi

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This study aimed to describe the operating model of obstructive sleep apnea. Due to the large number of patients, the role of nurses in the diagnosis and treatment of sleep apnea was important. Pulmonary physicians met only a minority of the patients. The sleep apnea study in 2018 included about 800 patients, of which about 28% were normal and 180 patients were classified as severe (apnea-hypopnea index [AHI] over 30). The operating model has proven to be workable and appropriate. The patients understand well that they may not be referred to a pulmonary doctor. However, specialized medical follow-up on professional drivers continues every year.

Keywords: sleep, apnea patient, operating model, hospital

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Authors: Cheng-Yu Tsai, Wen-Te Liu, Chen-Chen Lo, Yin-Tzu Lin, Kang Lo

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Background: Driving fatigue related to inadequate or disordered sleep accounts for a major percentage of traffic accidents. Obstructive sleep apnea syndrome (OSAS) is a common respiratory disorder during sleep. However, the effects of OSAS severity on driving drowsiness remain unclear. Objective: The aim of this study is to investigate the relationship between OSAS severity and driving fatigue. Methodologies: The physical condition while driving was obtained from the questionnaires to classify the state of driving fatigue. OSAS severity was quantified as the polysomnography, and the mean hourly number of greater than 3% dips in oxygen saturation during examination in a hospital in New Taipei City (Taiwan). The severity of OSAS was diagnosed by the apnea and hypopnea index (AHI) with the American Academy of Sleep Medicine (AASM) guideline. The logistic regression model was used to examine the associations after adjusted age, gender, neck circumstance, waist circumstance, and body mass index (BMI). Results: There were 880 subjects recruited in this study, who had been done polysomnography for evaluating severity for OSAS as well as completed the driver condition questionnaire. 752 subjects were diagnosed with OSA, and 484 subjects had fatigue driving behavior in the past week. Patients diagnosed with OSAS had a 9.42-fold higher odds ratio (p < 0.01, 95% CI = 5.41 – 16.42) of driving drowsiness for cohorts with a normal degree. Conclusion: We observe the considerable correlation between OSAS and driving fatigue. For the purpose of promoting traffic safety, OSAS should be monitored and treated.

Keywords: obstructive sleep apnea syndrome, driving fatigue, polysomnography, apnea and hypopnea index

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Authors: Cheng-Yu Tsai, Wen-Te Liu, Shin-Mei Hsu, Yin-Tzu Lin, Chi Wu

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Background: Obstructive Sleep apnea syndrome (OSAS) is a common respiratory disorder during sleep. In addition, Body parameters were identified high predictive importance for OSAS severity. However, the effects of body parameters on OSAS severity remain unclear. Objective: In this study, the objective is to establish a prediction model for OSAS by using body parameters and investigate the effects of body parameters in OSAS. Methodologies: Severity was quantified as the polysomnography and the mean hourly number of greater than 3% dips in oxygen saturation during examination in a hospital in New Taipei City (Taiwan). Four levels of OSAS severity were classified by the apnea and hypopnea index (AHI) with American Academy of Sleep Medicine (AASM) guideline. Body parameters, including neck circumference, waist size, and body mass index (BMI) were obtained from questionnaire. Next, dividing the collecting subjects into two groups: training and testing groups. The training group was used to establish the random forest (RF) to predicting, and test group was used to evaluated the accuracy of classification. Results: There were 3330 subjects recruited in this study, whom had been done polysomnography for evaluating severity for OSAS. A RF of 1000 trees achieved correctly classified 79.94 % of test cases. When further evaluated on the test cohort, RF showed the waist and BMI as the high import factors in OSAS. Conclusion It is possible to provide patient with prescreening by body parameters which can pre-evaluate the health risks.

Keywords: apnea and hypopnea index, Body parameters, obstructive sleep apnea syndrome, Random Forest

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Authors: Hsin-Yu Lin, Ching-Hsia Hung

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Obstructive sleep apnea (OSA) is characterized by a complete or partial obstruction of the upper airway during sleep. The vulnerable sites of upper airway collapses are consequences of sleep state-dependent reductions in tone in specific pharyngeal dilators. Clinical examinations reveal multilevel collapses of the upper airway among the patients with OSA. Therefore, an anatomically-based oropharyngeal rehabilitation should comprise a multilevel approach, including retropalatal, retroglossal, hypopharyngeal, temporomandibular, and facial levels, all of which involve different muscle groups and contribute to multifunctional interaction and coordination, such as swallowing, breathing, and phonation. The purpose of the study was to exam the effects of this rehabilitation program with a multilevel approach. In this study, fifteen subjects with newly diagnosed moderate or severe OSA (Apnea-Hypopnea-Index≥15) were randomized into an intervention group and control group. The intervention group (N=8) underwent a 12-week-intervention of a hospital-based rehabilitation program, while the control group (N=7) was kept on the waiting list. The 12-week-intervention comprised an anatomically based multilevel approach. The primary outcome was Polysomnography (PSG) data, and the secondary outcome was oropharyngeal and respiratory muscle function. In the intervention group, Apnea-Hypopnea-Index significantly improved (46.96±19.45 versus 32.78±10.78 events/h, p=0.017) compared with control group (35.77±17.49 versus 42.96±17.32 events/h, p=0.043). While the control group remained no change, the intervention group demonstrated other PSG outcomes significantly improvement, including arousal index (46.04±18.9 versus 32.98±8.35/h, p=0.035), mean SpO2 (92.88±2.1 versus 94.13±1.46%, p=0.039). Besides, the intervention group demonstrated significant improvement in oropharyngeal and respiratory muscle function compared to the control group. This anatomically-based oropharyngeal rehabilitation with a multilevel approach can be proven as a non-invasive therapy for patients with OSA.

Keywords: obstructive sleep apnea, upper airway, oropharyngeal rehabilitation, multilevel approach

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Authors: Ching-Yi Yiu, Hui-Chen Hsu

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Objectives: Obstructive sleep apnea syndrome (OSAS) is a popular problem in the modern society. It usually leads to sleep disorder, excessive daytime sleepiness and associated with cardiovascular diseases, cognitive dysfunction and even death. The nonsurgical therapies include continuous positive airway pressure (CPAP), diet and oral appliances. The surgical approaches have nasal surgery, tonsillectomy, adenoidectomy, uvulopalatopharyngoplasty (UPPP) and transoral robotic surgery (TORS).We compare the impact of surgical treatments on these kinds of patients. Methods: Between January 2018 to September 2022, We have enrolled 125 OSAS patients including 82 male and 43 female in Chi Mei Medical Center, Liouying, Taiwan. The age distribution from 6 to 71 years old (y/o) with mean age 36.1 y/o. The averaged body mass index (BMI) is 25 kg/m2 in male and 25.5 kg/m2 in female. In this cohort, we evaluated their upper airway obstruction sites with nasopharyngoscopy and scheduled a planned surgery. Some of cases received polysomnography (PSG) preoperatively, the averaged apnea-hypopnea index (AHI) is 37.7 events/hour. We have 68 patients received tonsillectomy, 9 received UPPP, 42 received UPPP and septomeatoplasty (SMP) and 6 received adenoidectomy and tonsillectomy (A and T). The subjective daytime sleepiness was evaluated with the Epworth sleepiness scale (ESS). Results: In the 68 tonsillectomy group, the averaged BMI is 24.9 kg/m2. In the UPPP group, the averaged BMI is 28.9 kg/m2. In UPPP and SMP group, the averaged BMI is 27.9 kg/m2. In the A and T group, the averaged BMI is 17.2 kg/m2. The reduction of AHI less than 20 is 58% postoperatively. The ESS reduced from 10.9 to 4.9 after surgery. Conclusion: Obstructive sleep apnea syndrome is a common upper airway disturbance in the general population. The prevalence rate is ranging high depending on different regions, age, sex and race. It leads to severe morbidity and mortality including car accident, stroke, nocturnal desaand sudden death and should be considered to be a major public health problem. The CPAP is effective to improve daytime sleepiness but the long-term compliance is low. The surgical treatment with different modalities can produce 50% decrease in AHI and ESS after surgery in the 6 to 12 months short-term period.

Keywords: apnea-hypopnea index, obstructive sleep apnea syndrome, polysomnography, uvulopalatopharyngoplasty

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Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

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Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

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Authors: Yasmeen Jamal Alabdallat, Almutazballlah Bassam Qablan, Hamza Al-Salhi, Salameh Alarood, Ibraheem Alkhawaldeh, Obada Abunar, Adam Abdallah

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Obstructive sleep apnea (OSA) is a disorder caused by the repeated collapse of the upper airway during sleep. It is the most common cause of sleep-related breathing disorder, as OSA can cause loud snoring, daytime fatigue, or more severe problems such as high blood pressure, cardiovascular disease, coronary artery disease, insulin-resistant diabetes, and depression. The hypoglossal nerve stimulator (HNS) is an implantable medical device that reduces the occurrence of obstructive sleep apnea by electrically stimulating the hypoglossal nerve in rhythm with the patient's breathing, causing the tongue to move. This stimulation helps keep the patient's airways clear while they sleep. This systematic review and meta-analysis aimed to assess the clinical outcome of hypoglossal nerve stimulation as a treatment of obstructive sleep apnea. A computer literature search of PubMed, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials was conducted from inception until August 2022. Studies assessing the following clinical outcomes (Apnea-Hypopnea Index (AHI), Epworth Sleepiness Scale (ESS), Functional Outcomes of Sleep Questionnaire (FOSQ), Oxygen Desaturation Indices (ODI), (Oxygen Saturation (SaO2)) were pooled in the meta-analysis using Review Manager Software. We assessed the quality of studies according to the Cochrane risk-of-bias tool for randomized trials (RoB2), Risk of Bias In Non-randomized Studies - of Interventions (ROBINS-I), and a modified version of NOS for the non-comparative cohort studies.13 Studies (Six Clinical Trials and Seven prospective cohort studies) with a total of 817 patients were included in the meta-analysis. The results of AHI were reported in 11 studies examining OSA 696 patients. We found that there was a significant improvement in the AHI after 12 months of HNS (MD = 18.2 with 95% CI, (16.7 to 19.7; I2 = 0%); P < 0.00001). Further, 12 studies reported the results of ESS after 12 months of intervention with a significant improvement in the range of sleepiness among the examined 757 OSA patients (MD = 5.3 with 95% CI, (4.75 to 5.86; I2 = 65%); P < 0.0001). Moreover, nine studies involving 699 participants reported the results of FOSQ after 12 months of HNS with a significant reported improvement (MD = -3.09 with 95% CI, (-3.41 to 2.77; I2 = 0%); P < 0.00001). In addition, ten studies reported the results of ODI with a significant improvement after 12 months of HNS among the 817 examined patients (MD = 14.8 with 95% CI, (13.25 to 16.32; I2 = 0%); P < 000001). The Hypoglossal Nerve Stimulation showed a significant positive impact on obstructive sleep apnea patients after 12 months of therapy in terms of apnea-hypopnea index, oxygen desaturation indices, manifestations of the behavioral morbidity associated with obstructive sleep apnea, and functional status resulting from sleepiness.

Keywords: apnea, meta-analysis, hypoglossal, stimulation

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Authors: Stelios A. Mitilineos, Nicolas-Alexander Tatlas, Georgia Korompili, Lampros Kokkalas, Stelios M. Potirakis

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Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a widespread chronic disease that mostly remains undetected, mainly due to the fact that it is diagnosed via polysomnography which is a time and resource-intensive procedure. Screening the disease’s symptoms at home could be used as an alternative approach in order to alert individuals that potentially suffer from OSAHS without compromising their everyday routine. Since snoring is usually linked to OSAHS, developing a snore detector is appealing as an enabling technology for screening OSAHS at home using ubiquitous equipment like commodity microphones (included in, e.g., smartphones). In this context, this study developed a snore detection tool and herein present the approach and selection of specific sound features that discriminate snoring vs. environmental sounds, as well as the performance of the proposed tool. Furthermore, a Real-Time Snore Detector (RTSD) is built upon the snore detection tool and employed in whole-night sleep sound recordings resulting to a large dataset of snoring sound excerpts that are made freely available to the public. The RTSD may be used either as a stand-alone tool that offers insight to an individual’s sleep quality or as an independent component of OSAHS screening applications in future developments.

Keywords: obstructive sleep apnea hypopnea syndrome, apnea screening, snoring detection, machine learning, neural networks

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Authors: R. Pääkkönen, L. Korpinen, T. Kava, I. Salmi

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This study evaluates obstructive sleep apnea treatment through a case study involving a 67-year-old male driver who had a successful continuous positive airway pressure (CPAP) treatment at home but experienced difficulties with traveling and dental care. There are many cheap sleep apnea and snoring devices available, but there is little professional advice on what kind of devices can help. Professional drivers receive yearly specialized medical care follow-up.

Keywords: sleep, apnea patient, CPAP, professional driver

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Authors: Suleman Maliha, Suleman Sidra

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Obstructive sleep apnea (OSA) is a sleep disorder that can result in behavioral and psychomotor impairments in children. The classical treatment modalities for OSA have been continuous positive airway pressure and adenotonsillectomy. However, orthodontic intervention through rapid maxillary expansion (RME) has also been commonly used to manage skeletal transverse maxillary discrepancies. Aim and objectives: The aim of this study is to determine the efficacy of rapid maxillary expansion in paediatric patients with obstructive sleep apnea by assessing pre and post-treatment mean apnea-hypopnea index (AHI) and oxygen saturations. Methodology: Literature was identified through a rigorous search of the Embase, Pubmed, and CINAHL databases. Articles published from 2012 onwards were selected. The inclusion criteria consisted of patients aged 18 years and under with no systemic disease, adenotonsillar surgery, or hypertrophy who are undergoing RME with AHI measurements before and after treatment. In total, six suitable papers were identified. Results: Three studies assessed patients pre and post-RME at 12 months. The first study consisted of 15 patients with an average age of 7.5 years. Following treatment, they found that RME resulted in both higher oxygen saturations (+ 5.3%) and improved AHI (- 4.2 events). The second study assessed 11 patients aged 5–8 years and also noted improvements, with mean AHI reduction from 6.1 to 2.4 and oxygen saturations increasing from 93.1% to 96.8%. The third study reviewed 14 patients aged 6–9 years and similarly found an AHI reduction from 5.7 to 4.4 and an oxygen saturation increase from 89.8% to 95.5%. All modifications noted in these studies were statistically significant. A long-term study reviewed 23 patients aged 6–12 years post-RME treatment on an annual basis for 12 years. They found that the mean AHI reduced from 12.2 to 0.4, with improved oxygen saturations from 78.9% to 95.1%. Another study assessed 19 patients aged 9-12 years at two months into RME and four months post-treatment. Improvements were also noted at both stages, with an overall reduction of the mean AHI from 16.3 to 0.8 and an overall increase in oxygen saturations from 77.9% to 95.4%. The final study assessed 26 children aged 7-11 years on completion of individual treatment and found an AHI reduction from 6.9 to 5.3. However, the oxygen saturation remained stagnant at 96.0%, but this was not clinically significant. Conclusion: Overall, the current evidence suggests that RME is a promising treatment option for paediatric patients with OSA. It can provide efficient and conservative treatment; however, early diagnosis is crucial. As there are various factors that could be contributing to OSA, it is important that each case is treated on its individual merits. Going forward, there is a need for more randomized control trials with larger cohorts being studied. Research into the long-term effects of RME and potential relapse amongst cases would also be useful.

Keywords: orthodontics, sleep apnea, maxillary expansion, review

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Authors: Filip Franciszek Karuga, Szymon Turkiewicz, Marta Ditmer, Marcin Sochal, Piotr Białasiewicz, Agata Gabryelska

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Circadian rhythm, an internal coordinator of physiological processes is composed of a set of semi-autonomous clocks. Clocks are regulated through the expression of circadian clock genes which form feedback loops, creating an oscillator. The primary loop consists of activators: CLOCK, BMAL1 and repressors: CRY, PER. CLOCK can be substituted by the Neuronal PAS Domain Protein 2 (NPAS2). Orphan nuclear receptor (REV-ERB-α) is a component of the secondary major loop, modulating the expression of BMAL1. Circadian clocks might be disrupted by the obstructive sleep apnea (OSA), which has also been associated with type II diabetes mellitus (DM2). Interestingly, studies suggest that dysregulation of NPAS2 and REV-ERB-α might contribute to the pathophysiology of DM2 as well. The goal of our study was to examine the role of NPAS2 and REV-ERB-α in DM2 in OSA patients. After examination of the clinical data, all participants underwent polysomnography (PSG) to assess their apnea-hypopnea index (AHI). Based on the acquired data participants were assigned to one of 3 groups: OSA (AHI>30, no DM2; n=17 for NPAS2 and 34 for REV-ERB-α), DM2 (AHI>30 + DM2; n=7 for NPAS2 and 15 for REV-ERB-α) and control group (AHI<5, no DM2; n=16 for NPAS2 and 31 for REV-ERB-α). ELISA immunoassay was performed to assess the serum protein level of REV-ERB-α and NPAS2. The only statistically significant difference between groups was observed in NPAS2 protein level (p=0.037). Post-hoc analysis showed significant differences between the OSA and the control group (p=0.017). AHI and NPAS2 level was significantly correlated (r=-0.478, p=0.002) in all groups. A significant correlation was observed between the REV-ERB-α level and sleep efficiency (r=0.617, p=0.005) as well as sleep maintenance efficiency (r=0.645, p=0.003) in the OSA group. We conclude, that NPAS2 is associated with OSA severity and might contribute to metabolic sequelae of this disease. REV-ERB-α on the other hand can influence sleep continuity and efficiency.

Keywords: OSA, diabetes mellitus, endocrinology, chronobiology

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Authors: Oyuntsetseg Sandag, Lkhagvadorj Khosbayar, Naidansuren Tsendeekhuu, Densenbal Dansran, Bandi Solongo

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Introduction: Obstructive sleep apnea (OSA) is a common disorder affecting at least 2% to 4% of the adult population. It is estimated that nearly 80% of men and 93% of women with moderate to severe sleep apnea are undiagnosed. A number of screening questionnaires and clinical screening models have been developed to help identify patients with OSA, also it’s indeed to clinical practice. Purpose of study: Determine dependence of obstructive sleep apnea between for severe risk and risk factor. Material and Methods: A cross-sectional study included 114 patients presenting from theCentral state 3th hospital and Central state 1th hospital. Patients who had obstructive sleep apnea (OSA)selected in this study. Standard StopBang questionnaire was obtained from all patients.According to the patients’ response to the StopBang questionnaire was divided into low risk, intermediate risk, and high risk.Descriptive statistics were presented mean ± standard deviation (SD). Each questionnaire was compared on the likelihood ratio for a positive result, the likelihood ratio for a negative test result of regression. Statistical analyses were performed utilizing SPSS 16. Results: 114 patients were obtained (mean age 48 ± 16, male 57)that divided to low risk 54 (47.4%), intermediate risk 33 (28.9%), high risk 27 (23.7%). Result of risk factor showed significantly increasing that mean age (38 ± 13vs. 54 ± 14 vs. 59 ± 10, p<0.05), blood pressure (115 ± 18vs. 133 ± 19vs. 142 ± 21, p<0.05), BMI(24 IQR 22; 26 vs. 24 IQR 22; 29 vs. 28 IQR 25; 34, p<0.001), neck circumference (35 ± 3.4 vs. 38 ± 4.7 vs. 41 ± 4.4, p<0.05)were increased. Results from multiple logistic regressions showed that age is significantly independently factor for OSA (odds ratio 1.07, 95% CI 1.02-1.23, p<0.01). Predictive value of age was significantly higher factor for OSA (AUC=0.833, 95% CI 0.758-0.909, p<0.001). Our study showing that risk of OSA is beginning 47 years old (sensitivity 78.3%, specifity74.1%). Conclusions: According to most of all patients’ response had intermediate risk and high risk. Also, age, blood pressure, neck circumference and BMI were increased such as risk factor was increased for OSA. Especially age is independently factor and highest significance for OSA. Patients’ age one year is increased likelihood risk factor 1.1 times is increased.

Keywords: obstructive sleep apnea, Stop-Bang, BMI (Body Mass Index), blood pressure

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Authors: Mary S. Ruppert-Stroescu, Minh Pham, Bruce Benjamin

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Sleep apnea is a condition where a person stops breathing and can lead to cardiovascular disease, hypertension, and stroke. In the United States, approximately forty percent of overnight sleep apnea detection tests are cancelled. The purpose of this study was to develop a textile-based sensing system that acquires biometric signals relevant to cardiovascular health, to transmit them wirelessly to a computer, and to quantitatively assess the signals for sleep apnea detection. Patient interviews, literature review and market analysis defined a need for a device that ubiquitously integrated into the patient’s lifestyle. A multi-disciplinary research team of biomedical scientists, apparel designers, and computer engineers collaborated to design a textile-based sensing system that gathers EKG, Sp02, and respiration, then wirelessly transmits the signals to a computer in real time. The electronic components were assembled from existing hardware, the Health Kit which came pre-set with EKG and Sp02 sensors. The respiration belt was purchased separately and its electronics were built and integrated into the Health Kit mother board. Analog ECG signals were amplified and transmitted to the Arduino™ board where the signal was converted from analog into digital. By using textile electrodes, ECG lead-II was collected, and it reflected the electrical activity of the heart. Signals were collected when the subject was in sitting position and at sampling rate of 250 Hz. Because sleep apnea most often occurs in people with obese body types, prototypes were developed for a man’s size medium, XL, and XXL. To test user acceptance and comfort, wear tests were performed on 12 subjects. Results of the wear tests indicate that the knit fabric and t-shirt-like design were acceptable from both lifestyle and comfort perspectives. The airflow signal and respiration signal sensors return good signals regardless of movement intensity. Future study includes reconfiguring the hardware to a smaller size, developing the same type of garment for the female body, and further enhancing the signal quality.

Keywords: sleep apnea, sensors, electronic textiles, wearables

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Authors: Santanu Chattopadhyay, Gautam Sarkar, Arabinda Das

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This paper presents wavelet based classification of various heart diseases. Electrocardiogram signals of different heart patients have been studied. Statistical natures of electrocardiogram signals for different heart diseases have been compared with the statistical nature of electrocardiograms for normal persons. Under this study four different heart diseases have been considered as follows: Myocardial Ischemia (MI), Congestive Heart Failure (CHF), Arrhythmia and Sleep Apnea. Statistical nature of electrocardiograms for each case has been considered in terms of kurtosis values of two types of wavelet coefficients: approximate and detail. Nine wavelet decomposition levels have been considered in each case. Kurtosis corresponding to both approximate and detail coefficients has been considered for decomposition level one to decomposition level nine. Based on significant difference, few decomposition levels have been chosen and then used for classification.

Keywords: arrhythmia, congestive heart failure, discrete wavelet transform, electrocardiogram, myocardial ischemia, sleep apnea

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Authors: Rabab A. El Wahsh, Hatem M. Marey, Maha Yousif, Asmaa M. Ibrahim

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Background: OSA and COPD are associated with microvascular changes. Retinal microvasculature can be directly and non-invasively examined. Aim: to evaluate retinal vascular tortuosity in patients with COPD, OSA, and overlap syndrome. Subjects and method: Sixty subjects were included; 15 OSA patients, 15 COPD patients, 15 COPD-OSA overlap patients, and 15 matched controls. They underwent digital retinal photography, polysomnography, arterial blood gases, spirometry, ESS, and stop-bang questionnaires. Results: Tortuosity of most retinal vessels was higher in all patient groups compared to the control group; tortuosity was more marked in overlap syndrome. There was a negative correlation between tortuosity of retinal vessels and PO2, O2 saturation, and minimum O2 desaturation, and a positive correlation with PCO2, AHI, O2 desaturation index, BMI and smoking index. Conclusion: Retinal vascular tortuosity occurs in OSA, COPD and overlap syndrome. Retinal vascular tortuosity is correlated with arterial blood gases parameters, polysomnographic findings, smoking index and BMI.

Keywords: OSA, COPD, overlap syndrome, retinal vascular tortuosity

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Authors: Ke Qiu, Minzi Mao, Jianjun Ren, Yu Zhao

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Although much has been done to investigate the influence of obstructive sleep apnea (OSA) on cognitive function, little attention has been paid to the role which gender differences play in this association. In the present study, we aim to explore the gender-specific association between OSA and cognitive impairment. Participants from UK biobank who have completed at least one of the five baseline cognitive tests (visuospatial memory, prospective memory, fluid intelligence, short numeric memory and reaction time) were included and were further categorized into three groups: (1) OSA, (2) self-reported snoring but without OSA, and (3) healthy controls (without OSA or snoring). Multivariable regression analysis was performed to examine the associations among snoring, OSA and performance of each of the five cognitive domains. A total of 267,889 participants (47% male, mean age: 57 years old) were included in our study. In the multivariable regression analysis, female participants in the OSA group had a higher risk of having poor prospective memory (OR: 1.24, 95% CI: 1.02～1.50, p = 0.03). Meanwhile, among female participants, OSA were inversely associated with the performances of fluid intelligence (β: -0.29, 95% CI: -0.46～-0.13, p < 0.001) and short-numeric memory (β: -0.14, 95% CI: -0.35～0.08, p = 0.02). In contrast, among male participants, no significant association was observed between OSA and impairment of the five cognitive domains. Overall, OSA was significantly associated with cognitive impairment in female participants rather than in male participants, indicating that more special attention and timely interventions should be given to female OSA patients to prevent further cognitive impairment.

Keywords: obstructive sleep apnea (OSA), cognitive impairment, gender-specific association, UK biobank

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Authors: Isil Cakir, Mustafa Uluhan

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Elevated serum Cardiotrophin-1 (CT-1) and leptin levels are important risk factors for cardiovascular diseases (CVDs). Obstructive sleep apnea syndrome (OSAS) has been reported to increase the risk of CVDs, too. The aim of this study was to evaluate the concentrations of serum CT-1 and leptin in these patients and whether their possible association with the disease severity. Fifty newly diagnosed patients with OSAS and thirty nonapneic snoring subjects were participated in this study. The mean ages of patients and control groups were 47.40±13.30 and 43.23±10.50 years, respectively (P=0.128). Fasting serum triglyseride, total cholesterol, LDL and HDL cholesterol, also CT-1 and leptin levels were evaluated. A significant difference was found in the serum CT-1 and leptin levels between the patients and the controls:serum median CT-1 levels in patients and control groups, respectively, were 19.47 and 8.23 pg/mL (P < 0.001) and leptin levels were 2.07 and 1.29 ng/mL (P < 0.001). In severe patients group (n=39), serum median CT-1 level was found statistically significantly higher than the median level in mild/moderate patients (n=11) group. Patients CT-1 concentrations were not associated with lipoprotein levels and there was no correlation between patients’ leptin and lipid profile parameters. Two risk factors for CVDs, CT-1 and leptin, have significantly elevated and they were associated with OSAS. Furthermore, CT-1 was associated with the severity of disease. We recommend the use of increased serum CT-1 and leptin concentrations as markers of the presence and severity of OSAS.They can be used as early markers in male OSAS patients without known CVDs.

Keywords: obstructive sleep apnea syndrome, cardiotrophin-1, leptin, cardiovascular disease

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Authors: Cheng-Yu Tsai, Wen-Te Liu, Yin-Tzu Lin, Chen-Chen Lo, Kang Lo

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Background: Driving drowsiness related to inadequate or disordered sleep accounts for a major percentage of traffic accidents. Sleep-disordered breathing (SDB) syndrome is a common respiratory disorder during sleep. However, the effects of SDB syndrome on driving fatigue remain unclear. Objective: This study aims to investigate the relationship between SDB pattern and driving drowsiness. Methodologies: The physical condition while driving was obtained from the questionnaires to classify the state of driving fatigue. SDB syndrome was quantified as the polysomnography, and the air flow pattern was collected by the thermistor and nasal pressure cannula. To evaluate the desaturation, the mean hourly number of greater than 3% dips in oxygen saturation was sentenced by reregistered technologist during examination in a hospital in New Taipei City (Taiwan). The independent T-test was used to investigate the correlations between sleep disorders related index and driving drowsiness. Results: There were 880 subjects recruited in this study, who had been done polysomnography for evaluating severity for obstructive sleep apnea syndrome (OSAS) as well as completed the driver condition questionnaire. Four-hundred-eighty-four subjects (55%) were classified as fatigue group, and 396 subjects (45%) were served as the control group. Significantly higher values of snoring index (242.14 ± 205.51 /hours) were observed in the fatigue group (p < 0.01). The value of respiratory disturbance index (RDI) (31.82 ± 19.34 /hours) in fatigue group were significantly higher than the control group (p < 0.01). Conclusion: We observe the considerable association between SDB syndrome and driving drowsiness. To promote traffic safety, SDB syndrome should be controlled and alleviated.

Keywords: driving drowsiness, sleep-disordered breathing syndrome, snoring index, respiratory disturbance index.

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Authors: Christina Hagen, Pragathi Kamale Gurmurthy, Thorsten M. Buzug

Abstract:

CFD simulations are performed in the upper airway of a patient suffering from obstructive sleep apnea (OSA) that is a sleep related breathing disorder characterized by repetitive partial or complete closures of the upper airways. The simulations are aimed at getting a better understanding of the pathophysiological flow patterns in an OSA patient. The simulation is compared to medical data of a sleep endoscopic examination under sedation. A digital model consisting of surface triangles of the upper airway is extracted from the MR images by a region growing segmentation process and is followed by a careful manual refinement. The computational domain includes the nasal cavity with the nostrils as the inlet areas and the pharyngeal volume with an outlet underneath the larynx. At the nostrils a flat inflow velocity profile is prescribed by choosing the velocity such that a volume flow rate of 150 ml/s is reached. Behind the larynx at the outlet a pressure of -10 Pa is prescribed. The stationary incompressible Navier-Stokes equations are numerically solved using finite elements. A grid convergence study has been performed. The results show an amplification of the maximal velocity of about 2.5 times the inlet velocity at a constriction of the pharyngeal volume in the area of the tongue. It is the same region that also shows the highest pressure drop from about 5 Pa. This is in agreement with the sleep endoscopic examinations of the same patient under sedation showing complete contractions in the area of the tongue. CFD simulations can become a useful tool in the diagnosis and therapy of obstructive sleep apnea by giving insight into the patient’s individual fluid dynamical situation in the upper airways giving a better understanding of the disease where experimental measurements are not feasible. Within this study, it could been shown on one hand that constriction areas within the upper airway lead to a significant pressure drop and on the other hand a good agreement of the area of pressure drop and the area of contraction could be shown.

Keywords: biomedical engineering, obstructive sleep apnea, pharynx, upper airways

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Authors: U. Mary

Abstract:

Let be a graph with a finite, nonempty set of objects called vertices together with a set of unordered pairs of distinct vertices of called edges. The vertex set is denoted by and the edge set by. Given two graphs and the wiener index of, wiener index for the splitting graph of a graph, the first Zagreb index of and its splitting graph, the 3-steiner wiener index of, the 3-steiner wiener index of a special graph are explored in this paper.

Keywords: complementary prism graph, first Zagreb index, neighborhood corona graph, steiner distance, splitting graph, steiner wiener index, wiener index

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Authors: Sadie Khorramnia, Asha Bonney, Kate Galloway, Andrew Kyoong

Abstract:

Sleep plays a pivotal role in the registration and consolidation of memory. Multiple observational studies have demonstrated that self-reported sleep duration and sleep quality are associated with cognitive performance. Montreal Cognitive Assessment questionnaire is a screening tool to assess mild cognitive (MCI) impairment with a 90% diagnostic sensitivity. In our current study, we used MOCA to identify MCI in patients who underwent sleep study in our sleep department. We then looked at the clinical risk factors and sleep-related parameters in subjects found to have mild cognitive impairment but without a diagnosis of sleep-disordered breathing. Clinical risk factors, including physician, diagnosed hypertension, diabetes, and depression and sleep-related parameters, measured during sleep study, including percentage time of each sleep stage, total sleep time, awakenings, sleep efficiency, apnoea hypopnoea index, and oxygen saturation, were evaluated. A total of 90 subjects who underwent sleep study between March 2019 and October 2019 were included. Currently, there is no pharmacotherapy available for MCI; therefore, identifying the risk factors and attempting to reverse or mitigate their effect is pivotal in slowing down the rate of cognitive deterioration. Further characterization of sleep parameters in this group of patients could open up opportunities for potentially beneficial interventions.

Keywords: apnoea hypopnea index, mild cognitive impairment, sleep architecture, sleep study

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Authors: Pragathi Gurumurthy, Christina Hagen, Patricia Ulloa, Martin A. Koch, Thorsten M. Buzug

Abstract:

Obstructive sleep apnea (OSA) is a sleep disorder where the patient suffers a disturbed airflow during sleep due to partial or complete occlusion of the pharyngeal airway. Recently, numerical simulations have been used to better understand the mechanism of pharyngeal collapse. However, to gain confidence in the solutions so obtained, an experimental validation is required. Therefore, in this study an experimental validation of computational fluid dynamics (CFD) used for the study of human pharyngeal flow patterns during OSA is performed. A stationary incompressible Navier-Stokes equation solved using the finite element method was used to numerically study the flow patterns in a computed tomography-based human pharynx model. The inlet flow rate was set to 250 ml/s and such that a flat profile was maintained at the inlet. The outlet pressure was set to 0 Pa. The experimental technique used for the validation of CFD of fluid flow patterns is phase contrast-MRI (PC-MRI). Using the same computed tomography data of the human pharynx as in the simulations, a phantom for the experiment was 3 D printed. Glycerol (55.27% weight) in water was used as a test fluid at 25°C. Inflow conditions similar to the CFD study were simulated using an MRI compatible flow pump (CardioFlow-5000MR, Shelley Medical Imaging Technologies). The entire experiment was done on a 3 T MR system (Ingenia, Philips) with 108 channel body coil using an RF-spoiled, gradient echo sequence. A comparison of the axial velocity obtained in the pharynx from the numerical simulations and PC-MRI shows good agreement. The region of jet impingement and recirculation also coincide, therefore validating the numerical simulations. Hence, the experimental validation proves the reliability and correctness of the numerical simulations.

Keywords: computational fluid dynamics, experimental validation, phase contrast-MRI, obstructive sleep apnea

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Authors: Imèn Khanchouch, Malika Charrad, Mohamed Limam

Abstract:

The interpretation of the quality of clusters and the determination of the optimal number of clusters is still a crucial problem in clustering. We focus in this paper on multi-SOM clustering method which overcomes the problem of extracting the number of clusters from the SOM map through the use of a clustering validity index. We then tested multi-SOM using real and artificial data sets with different evaluation criteria not used previously such as Davies Bouldin index, Dunn index and silhouette index. The developed multi-SOM algorithm is compared to k-means and Birch methods. Results show that it is more efficient than classical clustering methods.

Keywords: clustering, SOM, multi-SOM, DB index, Dunn index, silhouette index

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Authors: Rosyidah, Permata Wulandari

Abstract:

We investigate the price effect of addition and deletions from the Indonesia Sharia Stock Index (ISSI) and Jakarta Islamic Index (JII). Using event study methodology, we measure abnormal returns for firms over the period June 2019 - to December 2021. Through the sample of 107 additions and 95 deletions, we find evidence to support the theory of Muslim country investment behavior. We find that additions to the Islamic index led to a significant positive stock market reaction and deletions to the Islamic index led to a negative stock market reaction on Jakarta Islamic Index (JII) and there is no significant reaction of addition and deletion on Indonesia Sharia Stock Index (ISSI).

Keywords: abnormal return, abnormal volume, event study, index changes, sharia index

Procedia PDF Downloads 129

Authors: Sat Sharma, Antonella Conflitti, Hilary Reiter

Abstract:

Introduction: The study's purpose was to assess the efficacy of the oral appliance device O2Vent Optima + ExVent as compared to Optima in the treatment of OSA. Methods: A prospective, open-label study conducted at 3 sites included subjects with mild to moderate OSA (AHI ≥ 5 and ≤ 30). Screening Phase: A diagnostic in-lab PSG study was performed to confirm a diagnosis of mild to moderate OSA. Treatment I: Subjects used O2Vent Optima for 6 weeks and underwent an in-lab PSG sleep night while using the O2Vent Optima. Treatment II: Subjects used O2Vent Optima + ExVent for 6 weeks and underwent an in-lab PSG sleep night while using the O2Vent Optima + ExVent Primary Effectiveness Measure: Change in AHI between baseline vs. O2Vent Optima MAD vs. O2Vent Optima + ExVent. Results: Treatment with Optima, Optima + ExVent reduced AHI from 22.5±6.4/hr to 12.6±4.5/hr to 5.9±2.7 (p< 0.005 baseline vs. Optima and Optima + ExVent; p<0.05 Optima MAD vs. Optima + ExVent). The average reduction in AHI with Optima was 43%, and with Optima + ExVent was 72%. The lowest oxygen during sleep increased from 84.6±2.7% to 88.6±2.9% to 91.6±3.2% (p< 0.005 baseline vs. Optima and Optima + ExVent; p<0.05 Optima vs. Optima + ExVent). During the trial, patients on treatment with Optima and Optima + ExVent demonstrated no excessive adverse events or device malfunction. Conclusion: Treatment with O2Vent Optima and O2Vent Optima + ExVent significantly improved OSA compared to the baseline. An even greater benefit was observed with the addition of ExVent to the Optima in mild to moderate OSA.

Keywords: oral appliance, O2Vent, sleep dentistry, sleep apnea

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Authors: Adian Fatchur Rochim, Abdul Muis, Riri Fitri Sari

Abstract:

H-index has been widely used as a performance indicator of researchers around the world especially in Indonesia. The Government uses Scopus and Google scholar as indexing references in providing recognition and appreciation. However, those two indexing services yield to different H-index values. For that purpose, this paper evaluates the difference of the H-index from those services. Researchers indexed by Webometrics, are used as reference’s data in this paper. Currently, Webometrics only uses H-index from Google Scholar. This paper observed and compared corresponding researchers’ data from Scopus to get their H-index score. Subsequently, some researchers with huge differences in score are observed in more detail on their paper’s publisher. This paper shows that the H-index of researchers in Google Scholar is approximately 2.45 times of their Scopus H-Index. Most difference exists due to the existence of uncertified publishers, which is considered in Google Scholar but not in Scopus.

Keywords: Google Scholar, H-index, Scopus, performance indicator

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Authors: P. Góes, J. Manzi

Abstract:

This paper focuses on the development of an energy efficiency index that will be applied to reactive systems, which is based in the First and Second Law of Thermodynamics, by giving particular consideration to the concept of maximum entropy. Among the requirements of such energy efficiency index, the practical feasibility must be essential. To illustrate the performance of the proposed index, such an index was used as decisive factor of evaluation for the optimization process of an industrial reactor. The results allow the conclusion to be drawn that the energy efficiency index applied to the reactive system is consistent because it extracts the information expected of an efficient indicator, and that it is useful as an analytical tool besides being feasible from a practical standpoint. Furthermore, it has proved to be much simpler to use than tools based on traditional methodologies.

Keywords: energy, efficiency, entropy, reactive

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Authors: Chen-Yu Tsai, Wen-Te Liu, Chen-Chen Lo, Kang Lo, Yin-Tzu Lin

Abstract:

Background: Driving drowsiness related to insufficient or disordered sleep accounts for a major percentage of vehicular accidents. Sleep deprivation is the primary reason related to low sleep efficiency. Nevertheless, the mechanism of sleep deprivation induces driving fatigue to remain unclear. Objective: The objective of this study is to associate the relationship between insufficient sleep efficiency and driving fatigue. Methodologies: The physical condition while driving was obtained from the questionnaires to classify the state of driving fatigue. Sleep efficiency was quantified as the polysomnography (PSG), and the sleep stages were sentenced by the reregistered Technologist during examination in a hospital in New Taipei City (Taiwan). The independent T-test was used to investigate the correlation between sleep efficiency, sleep stages ratio, and driving drowsiness. Results: There were 880 subjects recruited in this study, who had been done polysomnography for evaluating severity for obstructive sleep apnea syndrome (OSAS) as well as completed the driver condition questionnaire. Four-hundred-eighty-four subjects (55%) were classified as fatigue group, and 396 subjects (45%) were served as the control group. The ratio of stage three sleep (N3) (0.032 ± 0.056) in fatigue group were significantly lower than the control group (p < 0.01). The significantly higher value of snoring index (242.14 ± 205.51 /hours) was observed in the fatigue group (p < 0.01). Conclusion: We observe the considerable correlation between deep sleep reduce and driving drowsiness. To avoid drowsy driving, the sleep deprivation, and the snoring events during the sleeping time should be monitored and alleviated.

Keywords: driving drowsiness, sleep deprivation, stage three sleep, snoring index

Procedia PDF Downloads 143