A Panoramic Study of Obstructive Sleep Apnea Detection Technologies

This study offers a literature research reference value for bioengineers and practitioner medical doctors. It could reduce research time and improve medical service efficiency regarding Obstructive Sleep Apnea (OSA) detection systems. Much of the past and the current apnea research, the vital signals features and parameters of the SA automatic detection are introduced.The applications for the earlier proposed systems and the related work on real-time and continuous monitoring of OSA and the analysis is given. The study concludes with an assessment of the current technologies highlighting their weaknesses and strengths which can set a roadmap for researchers and clinicians in this rapidly developing field of study

An interactive, real-time, high precision and portable monitoring system of obstructive sleep apnea

Obstructive sleep apnea (OSA) is the most common type of sleep apnea which is defined as the suspension of breathing. OSA is generally caused by complete or partial obstruction of airway during sleep, making the breathing pattern irregular and abnormal for prolonged periods of time. Apnea can contribute to a variety of life threatening medical conditions, and can be deadly if left untreated. Nowadays, out of 18 to 50 million people in the US, most cases remain undiagnosed due to the cost, cumbersome and resource limitations of overnight polysomnography (PSG) at sleep labs. Currently PSG relies on a doctor's experience. In order to improve the medical service efficiency, reduce diagnosis time and ensure a more accurate diagnosis, a quantitative and objective method is needed. In this dissertation, an innovative method in characterizing bio-signals for detecting epochs of sleep apnea with high accuracy is presented. Three data channels that are related to breath defect; respiratory sound, ECG and SpO2 are investigated, in order to extract physiological indicators that characterize sleep apnea. An automated method was used to analyze the respiratory sound to find pauses in breathing. Furthermore, the automated method analyzed ECG to find irregular heartbeats and SpO 2 to find rises and drops. The system consists of three main parts which are signal segmentation, features extraction and features classification. Feature extractions process is based on statistical measures. Features classification process is learned through Support Vector Machines (SVMs) and Neural Network (NN) classifiers. Moreover, a preprocessing technique is carried out to distinguish the R-wave from the other waves of the ECG signal. The approach presented in this dissertation was tested using downloaded polysomnographic ECG and SpO2 data from the Physionet database. In addition, to identifying sleep apnea using the acoustic signal of respiration; the characterization of breathing sound was carried by Voice Activity Detection (VAD) algorithm. VAD was used to measure the energy of the acoustic respiratory signal during breath and silence segments. From the experimental results for the three signals, it was concluded that the precision of classifying sleep apnea has an accuracy of 97%. This result offers a clinical reference value for identifying OSA instead of expensive PSG visual scoring method which is commonly used to asses sleep apnea, and could reduce diagnostic time and improve medical service efficiency

Medical Devices for Measuring Respiratory Rate in Children: a Review

Respiratory rate is an important vital sign used for diagnosing illnesses in children as well as prioritising patient care. All children presenting acutely to hospital should have a respiratory rate measured as part of their initial and ongoing assessment. However measuring the respiratory rate remains a subjective assessment and in children can be liable to measurement error especially if the child is uncooperative. Devices to measure respiratory rate exist but many provide only an estimate of respiratory rate due to the associated methodological complexities. Some devices are used within the intensive care, post-operative or more specialised investigatory settings none however have made their way into the everyday clinical setting. A non-contact device may be better tolerated in children and not cause undue stress distorting the measurement. Further validation and adaption to the acute clinical setting is needed before such devices can supersede current methods

Devices for Ambulatory Monitoring of Sleep-Associated Disorders in Children with Neurological Diseases

Good sleep quality is essential for a child’s wellbeing. Early sleep problems have been linked to the later development of emotional and behavioral disorders and can negatively impact the quality of life of the child and his or her family. Sleep-associated conditions are frequent in the pediatric population, and even more so in children with neurological problems. Monitoring devices can help to better characterize sleep efficiency and sleep quality. They can also be helpful to better characterize paroxysmal nocturnal events and differentiate between nocturnal seizures, parasomnias, and obstructive sleep apnea, each of which has a different management. Overnight ambulatory detection devices allow for a tolerable, low cost, objective assessment of sleep quality in the patient’s natural environment. They can also be used as a notification system to allow for rapid recognition and prompt intervention of events like seizures. Optimal monitoring devices will be patient- and diagnosis-specific, but may include a combination of modalities such as ambulatory electroencephalograms, actigraphy, and pulse oximetry. We will summarize the current literature on ambulatory sleep devices for detecting sleep disorders in children with neurological diseases

Diagnostic accuracy of oximetry for obstructive sleep apnea: a study on older adults in a home setting

OBJECTIVES: Owing to the fact that obstructive sleep apnea (OSA) is an underreported disease, the strategy used for the diagnosis of OSA has been extensively dissected to devise a simplified process that can be accessed by the public health services. Polysomnography (PSG) type I, the gold standard for the diagnosis of OSA, is expensive and difficult to access by low-income populations. In this study, we aimed to verify the accuracy of the oxyhemoglobin desaturation index (ODI) in comparison to the apnea-hypopnea index (AHI) using a portable monitor. METHODS: We evaluated 94 type III PSG home test results of 65 elderly patients (69.21±6.94 years old), along with information, such as the body mass index (BMI) and sex, using data obtained from a clinical trial database. RESULTS: A significant linear positive correlation (r=0.93, p<0.05) was observed between ODI and AHI, without any interference from sex, BMI, and positional component. The sensitivity of ODI compared to that of AHI increased with an increase in the severity of OSA, while the specificity of ODI in comparison to that of AHI was high for all degrees of severity. The accuracy of ODI was 80.7% for distinguishing between patients with mild and moderate apnea and 84.4% for distinguishing between patients with moderate and severe apnea. CONCLUSION: The ODI values obtained in uncontrolled conditions exhibited high sensitivity for identifying severe apnea compared to the AHI values, and correctly identified the severity of OSA in more than 80% of the cases. Thus, oximetry is promising strategy for diagnosing OSA

Positive airway pressure and electrical stimulation methods for obstructive sleep apnea treatment: a patent review (2005-2014)

Producción CientíficaIntroduction. Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a major health problem with significant negative effects on the health and quality of life. Continuous positive airway pressure (CPAP) is currently the primary treatment option and it is considered the most effective therapy for OSAHS. Nevertheless, comfort issues due to improper fit to patient’s changing needs and breathing gas leakage limit the patient’s adherence to treatment. Areas covered. The present patent review describes recent innovations in the treatment of OSAHS related to optimization of the positive pressure delivered to the patient, methods and systems for continuous self-adjusting pressure during inspiration and expiration phases, and techniques for electrical stimulation of nerves and muscles responsible for the airway patency. Expert opinion. In the last years, CPAP-related inventions have mainly focused on obtaining an optimal self-adjusting pressure according to patient’s needs. Despite intensive research carried out, treatment compliance is still a major issue. Hypoglossal electrical nerve stimulation could be an effective secondary treatment option when CPAP primary therapy fails. Several patents have been granted focused on selective stimulation techniques and parameter optimization of the stimulating pulse waveform. Nevertheless, there remain important issues to address, like effectiveness and adverse events due to improper stimulation.Ministerio de Economía y Competitividad (TEC2011-22987)Junta de Castilla y León (VA059U13

Predicting Arterial Oxygen Desaturation Events Via Patient Journal and Pulse Oximetry Data in Postoperative Ambulatory Surgery Patients

Associations between patient and procedural factors on the nature and quality of the immediate in-home recovery from anesthesia following ambulatory orthopedic surgery are unknown. Further, there is a paucity of outcomes research quantitatively categorizing in-home patient recovery and safety following discharge from same-day orthopedic procedures. Tools are available, however, to shed light on outcomes in this population, and integration of such available measures is critical. Ambulatory orthopedic surgery is a burgeoning specialty, with growth expected over the foreseeable future. The expected increased patient caseload subsequent to implementation of the Affordable Care Act and aging Baby Boom generation suggests greater morbidity and mortality is on the horizon unless aggressive measures are taken at mitigating risk. Similarly, as the obesity epidemic expands, obesity-related comorbid conditions including obstructive sleep apnea (OSA) are likely to grow. The purpose of this research was to explore the relationship between ambulatory orthopedic patient-reported activities (quality of life metrics) and diagnostic factors (physical and perioperative care data) in the immediate postoperative period that are predictive of arterial oxygen desaturation. Data was obtained using a novel patient journal exploring sleep, pain, nausea, tobacco use, alcohol use, and appetite in conjunction with a valid and reliable portable, wrist-worn pulse oximeter. Additional assessment data was taken from the preanesthetic assessment. All participants were scored according to the STOP-Bang questionnaire, an accepted survey of OSA risk. Patients were recruited from a busy metropolitan ambulatory surgery center in Richmond, Virginia that sees approximately 500 cases monthly, and a 309-bed tertiary care hospital in West Burlington, Iowa. The target sample included 52 individual patients with data collected over the first two post-operative nights following discharge. Two patients were excluded. Negative binomial regression, log10 transformation, and least-squares regression examined the relationships the STOP-Bang questionnaire, quality of life data, and physical perioperative data had on postoperative desaturation events. Results suggested the STOP-Bang score predicted desaturation events and that age and BMI were significant individual predictors. Opiate pain medication treatment, a happy mood, and home CPAP use were associated with decreased events. This study provided a unique perspective in patient safety research, relating human behaviors and experiences with postoperative oxygen desaturation. Future research projects aligned with postoperative monitoring, pulse oximetry, patient safety, and obstructive sleep apnea are potential following the findings of this study

Breathing Monitoring and Pattern Recognition with Wearable Sensors

This chapter introduces the anatomy and physiology of the respiratory system, and the reasons for measuring breathing events, particularly, using wearable sensors. Respiratory monitoring is vital including detection of sleep apnea and measurement of respiratory rate. The automatic detection of breathing patterns is equally important in other respiratory rehabilitation therapies, for example, magnetic resonance exams for respiratory triggered imaging, and synchronized functional electrical stimulation. In this context, the goal of many research groups is to create wearable devices able to monitor breathing activity continuously, under natural physiological conditions in different environments. Therefore, wearable sensors that have been used recently as well as the main signal processing methods for breathing analysis are discussed. The following sensor technologies are presented: acoustic, resistive, inductive, humidity, acceleration, pressure, electromyography, impedance, and infrared. New technologies open the door to future methods of noninvasive breathing analysis using wearable sensors associated with machine learning techniques for pattern detection

New organisation for follow-up and assessment of treatment efficacy in sleep apnoea

Obstructive sleep apnoea (OSA) is a highly prevalent disease, and there is an increased demand for OSA diagnosis and treatment. However, resources are limited compared with the growing needs for OSA diagnosis and management, and alternative strategies need to be developed to optimise the OSA clinical pathway. In this review, we propose a management strategy for OSA, and in general for sleep-disordered breathing, to be implemented from diagnosis to follow-up. For this purpose, the best current options seem to be: 1) networking at different levels of care, from primary physicians to specialised sleep laboratories; and 2) use of telemedicine. Telemedicine can contribute to the improved cost-effectiveness of OSA management during both the diagnostic and therapeutic phases. However, although the technology is already in place and different commercial platforms are in use, it is still unclear how to use telemedicine effectively in the sleep field. Application of telemedicine for titration of positive airway pressure treatment, follow-up to improve compliance to treatment through early identification and solution of problems, and teleconsultation all appear to be promising areas for improved OSA management