Cardiorespiratory Phase-Coupling Is Reduced in Patients with Obstructive Sleep Apnea

Cardiac and respiratory rhythms reveal transient phases of phase-locking which were proposed to be an important aspect of cardiorespiratory interaction. The aim of this study was to quantify cardio-respiratory phase-locking in obstructive sleep apnea (OSA). We investigated overnight polysomnography data of 248 subjects with suspected OSA. Cardiorespiratory phase-coupling was computed from the R-R intervals of body surface ECG and respiratory rate, calculated from abdominal and thoracic sensors, using Hilbert transform. A significant reduction in phase-coupling was observed in patients with severe OSA compared to patients with no or mild OSA. Cardiorespiratory phase-coupling was also associated with sleep stages and was significantly reduced during rapid-eye-movement (REM) sleep compared to slow-wave (SW) sleep. There was, however, no effect of age and BMI on phase coupling. Our study suggests that the assessment of cardiorespiratory phase coupling may be used as an ECG based screening tool for determining the severity of OSA

Hengitystilavuuden jatkuvan seurannan toteutettavuus epäsuorin mittausmenetelmin

Respiratory rate is a routinely monitored vital parameter in hospitals. Despite the change in respiratory rate often being the first sign of patient deterioration, it is not always a sufficient indicator of patient’s ventilatory status. A number of adverse events could be reacted to earlier if also the respiratory volume was monitored. In this work, feasibility of indirect respiratory volume measurements was assessed. Impedance pneumography (IP) and respiratory inductance plethysmography (RIP) measurement data from 15 measurement sessions with voluntary test subjects were analyzed. Signal amplitude was used to track relative minute volume values. Furthermore, a signal quality indicator was developed to detect sections of signal where the relative volume estimate was unreliable. The average coefficient of determination, R2, for the best RIP signal evaluation method was 0.71 while it was 0.53 for IP. RIP is more accurate than IP, but requires an extra sensor whereas IP can be measured simultaneously with ECG using the same electrodes. The developed signal quality index method improved coefficient of determination between the reference method and IP measurement to R2 = 0.66. The relative volume information is lost with patient posture change, but this change could be detected using other methods. These results show that IP and RIP can detect trends in respiratory volume.Hengitystiheyttä seurataan sairaaloissa rutiininomaisesti. Vaikka muutos hengitystiheydessä usein kertoo potilaan tilan heikentymisestä, se ei yksin riitä kuvaamaan potilaan hengityksen tilaa. Useisiin haitallisiin tilanteisiin voitaisiin reagoida aiemmin jos seurattaisiin myös hengitystilavuutta. Tässä työssä tutkittiin hengitystilavuuden seurannan toteutettavuutta epäsuorin mittausmenetelmin. Impedanssipneumografia- (IP) ja induktanssipletysmografiasignaalit (RIP) mitattiin ja analysoitiin 15 mittauksesta vapaaehtoisilta koehenkilöiltä. Signaalin amplitudin perusteella laskettiin suhteellisia minuuttivolyymiarvoja. Myös signaalin laadun mittari kehitettiin havaitsemaan signaalin sellaiset osiot, joissa arvioitu suhteellinen minuuttitilavuus oli epäluotettava. Selitysasteen, R 2, keskiarvo parhaalle RIP-menetelmälle oli 0.71 ja IP- menetelmälle 0.53. RIP on tarkempi kuin IP, mutta RIP vaatii oman sensorin, kun taas IP voidaan mitata yhdenaikaisesti EKG:n kanssa samoista elektrodeista. Kehitetty signaalin laadun mittari paransi IP-menetelmän selitysastetta arvoon R2 = 0.66. Tieto suhteellisesta hengitystilavuudesta menetetään potilaan asennon muutoksen myötä, mutta asennon muutos voidaan havaita muilla menetelmillä. Tulokset osoittavat, että IP ja RIP havaitsevat hengitystilavuuden suhteelliset muutokset

Southwest Research Institute assistance to NASA in biomedical areas of the technology

Significant applications of aerospace technology were achieved. These applications include: a miniaturized, noninvasive system to telemeter electrocardiographic signals of heart transplant patients during their recuperative period as graded situations are introduced; and economical vital signs monitor for use in nursing homes and rehabilitation hospitals to indicate the onset of respiratory arrest; an implantable telemetry system to indicate the onset of the rejection phenomenon in animals undergoing cardiac transplants; an exceptionally accurate current proportional temperature controller for pollution studies; an automatic, atraumatic blood pressure measurement device; materials for protecting burned areas in contact with joint bender splints; a detector to signal the passage of animals by a given point during ecology studies; and special cushioning for use with below-knee amputees to protect the integrity of the skin at the stump/prosthesis interface

Non-contact video-based assessment of the respiratory function using a RGB-D camera

A fully automatic, non-contact method for the assessment of the respiratory function is proposed using an RGB-D camera-based technology. The proposed algorithm relies on the depth channel of the camera to estimate the movements of the body’s trunk during breathing. It solves in fixed-time complexity, O(1), as the acquisition relies on the mean depth value of the target regions only using the color channels to automatically locate them. This simplicity allows the extraction of real-time values of the respiration, as well as the synchronous assessment on multiple body parts. Two different experiments have been performed: a first one conducted on 10 users in a single region and with a fixed breathing frequency, and a second one conducted on 20 users considering a simultaneous acquisition in two regions. The breath rate has then been computed and compared with a reference measurement. The results show a non-statistically significant bias of 0.11 breaths/min and 96% limits of agreement of -2.21/2.34 breaths/min regarding the breath-by-breath assessment. The overall real-time assessment shows a RMSE of 0.21 breaths/min. We have shown that this method is suitable for applications where respiration needs to be monitored in non-ambulatory and static environments.This research was funded by Ministerio de Ciencia e Innovación with grant number PID2020-116011.Postprint (published version

Design of a Non-Contact Home Monitoring System for Audio Detection of Infant Apnea

Infant apnea is a widespread condition in which infants fail to effectively breathe, and can lead to death. Clinical solutions exist for continuous monitoring of respirations in a hospital setting and requiring constant skin contact. This thesis investigates the construction of a proof of concept device that performs in-home monitoring without skin contact and with commonly available off-the-shelf components. The device constructed used a directional microphone to detect breathing sounds, an omnidirectional microphone to detect ambient noise as a baseline to help isolate the breathing sounds, and LabVIEW software deployed on an inexpensive laptop computer to quantify incidents of apparent lapses in breathing meeting the clinical definition of apnea. Testing results indicate that these components are effective in capturing these events in pre-term infants as well as adults, which provides promising evidence that a low-cost system could be manufactured for home detection to assist in infant monitoring

Methods for Detecting and Monitoring of Sleep Disordered Breathing in Children using Overnight Polysomnography

Sleep is crucial for the health of every individual, especially children. One of the common causes of disturbed sleep in children is disordered breathing. Children who suffer from sleep disordered breathing are likely to have severe consequences for their physical growth, heart health and neuropsychological function. Sleep disordered breathing (SDB) comprises a spectrum of severity from a mild form of upper airway resistance syndrome (UARS) to severe form of obstructive sleep apnea syndrome (OSAS). While OSAS is considered clinically significant, UARS and its health consequences have been underestimated. The most common treatment for OSAS in children is adenotonsillectomy. However, breathing disturbances related to UARS may persist even after adenotonsillectomy. The current diagnostic marker for OSAS, the Apnea-Hypopnea Index (AHI) often overlooks the less severe conditions of breathing disturbances. Therefore, the research objective of this thesis is to investigate the new alternative markers for SDB in children using non-invasive physiological measurements, such as thoracoabdominal signals and the photoplethysmogram. As the body experiences an array of complex changes, specifically in respiratory and autonomic nervous system activation during breathing disturbances, advanced signal processing and analysis techniques were used to identify the physiological variables that could reflect changes in those systems in children with SDB. Thoraco-abdominal asynchrony (TAA), heart period (HP) and pulse wave amplitude (PWA) were the three physiological variables were investigated. A total of five studies were conducted on two high-quality clinical research datasets to test the potential of the proposed physiological variables to effectively identify children with SDB. In the thesis: 1) Hilbert transform was applied for TAA estimation on the childhood adenotonsillectomy trial (CHAT) dataset; 2) symbolic dynamic analysis on HP was used to assess the effect of adenotonsillectomy on autonomic activations in children with SDB; 3) the conventional method of estimating PWA was combined with joint symbolic analysis of PWA and HP to analyse the effect of SDB on autonomic activation compared to healthy controls; 4) to improve the performance of the previous PWA measurement technique, a more robust and simpler method was proposed to estimate PWA using a simple envelope method, and a more extensive dynamic analysis method was created to capture more complete information; and 5) adding TAA and HP information with AHI, unsupervised machine learning method K-means clustering and linear discriminant analysis were used to discover the pathophysiology nature difference of children with SDB in CHAT dataset. The main results from this thesis suggest that children with SDB have higher values in all three physiological variables, which indicates a high respiratory effort and elevated frequency of autonomic activation. Adenotonsillectomy showed to reverse the effects on these physiological variables, suggesting it assisted in the reduce of pathophysiological symptoms in those children. Interestingly, TAA was found inversely correlated with quality of life and unreported baseline difference in HP in children who had their AHI normalised spontaneously. These findings further indicate the limitation of AHI as the only marker for paediatric sleep disordered breathing. By combining the TAA and HP information with AHI, the alternative proposed diagnosing approach could help doctors predict who may benefit from adenotonsillectomy or not. In conclusion, this thesis provides new evidence that TAA, HP and PWA can provide additional information and may yield more effective markers for diagnosing paediatric sleep disordered breathing.Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 201

Invasive and non-invasive assessment of upper airway obstruction and respiratory effort with nasal airflow and esophageal pressure analysis during sleep

La estimación del esfuerzo respiratorio durante el sueño es de una importancia crítica para la identificación correcta de eventos respiratorios en los trastornos respiratorios del sueño (TRS), el diagnóstico correcto de las patologías relacionadas con los TRS y las decisiones sobre la terapia correspondiente. Hoy en día el esfuerzo respiratorio suele ser estimado mediante la polisomnografía (PSG) nocturna con técnicas imprecisas y mediante la evaluación manual por expertos humanos, lo cual es un proceso laborioso que conlleva limitaciones significativas y errores en la clasificación. El objetivo principal de esta tesis es la presentación de nuevos métodos para la estimación automático, invasiva y no-invasiva del esfuerzo respiratorio y cambios en la obstrucción de las vías aéreas superiores (VAS). En especial, la aplicación de estos métodos debería permitir, entre otras cosas, la diferenciación automática invasiva y no-invasiva de eventos centrales y obstructivos durante el sueño. Con este propósito se diseñó y se obtuvo una base de datos de PSG nocturna completamente nueva de 28 pacientes con medición sistemática de presión esofágica (Pes). La Pes está actualmente considerada como el gold-standard para la estimación del esfuerzo respiratorio y la identificación de eventos respiratorios en los TRS. Es sin embargo una técnica invasiva y altamente compleja, lo cual limita su uso en la rutina clínica. Esto refuerza el valor de nuestra base de datos y la dificultad que ha implicado su adquisición. Todos los métodos de procesado propuestos y desarrollados en esta tesis están consecuentemente validados con la señal gold-standard de Pes para asegurar su validez.En un primer paso, se presenta un sistema automático invasivo para la clasificación de limitaciones de flujo inspiratorio (LFI) en los ciclos inspiratorios. La LFI se ha definido como una falta de aumento en flujo respiratorio a pesar de un incremento en el esfuerzo respiratorio, lo cual suele resultar en un patrón de flujo respiratorio característico (flattening). Un total de 38,782 ciclos respiratorios fueron automáticamente extraídos y analizados. Se propone un modelo exponencial que reproduzca la relación entre Pes y flujo respiratorio de una inspiración y permita la estimación objetiva de cambios en la obstrucción de las VAS. La capacidad de caracterización del modelo se estima mediante tres parámetros de evaluación: el error medio cuadrado en la estimación de la resistencia en la presión pico, el coeficiente de determinación y la estimación de episodios de LFI. Los resultados del modelo son comparados a los de los dos mejores modelos en la literatura. Los resultados finales indican que el modelo exponencial caracteriza la LFI y estima los niveles de obstrucción de las VAS con la mayor exactitud y objetividad. Las anotaciones gold-standard de LFI obtenidas, fueron utilizadas para entrenar, testear y validar un nuevo clasificador automático y no-invasivo de LFI basa en la señal de flujo respiratorio nasal. Se utilizaron las técnicas de Discriminant Analysis, Support Vector Machines y Adaboost para la clasificación no-invasiva de inspiraciones con las características extraídas de los dominios temporales y espectrales de los patrones de flujo inspiratorios. Este nuevo clasificador automático no-invasivo también identificó exitosamente los episodios de LFI, alcanzando una sensibilidad de 0.87 y una especificidad de 0.85. La diferenciación entre eventos respiratorios centrales y obstructivos es una de las acciones más recurrentes en el diagnostico de los TRS. Sin embargo únicamente la medición de Pes permite la diferenciación gold-standard de este tipo de eventos. Recientemente se han propuesto nuevas técnicas para la diferenciación no-invasiva de apneas e hipopneas. Sin embargo su adopción ha sido lenta debido a su limitada validación clínica, ya que la creación manual por expertos humanos de sets gold-standard de validación representa un trabajo laborioso. En esta tesis se propone un nuevo sistema para la diferenciación gold-standard automática y objetiva entre hipopneas obstructivas y centrales. Expertos humanos clasificaron manualmente un total de 769 hypopneas en 28 pacientes para crear un set de validación gold-standard. Como siguiente paso se extrajeron características específicas de cada hipopnea para entrenar y testear clasificadores (Discriminant Analysis, Support Vector Machines y adaboost) para diferenciar entre hipopneas centrales y obstructivas mediante la señal gold-standard Pes. El sistema de diferenciación automática alcanzó resultados prometedores, obteniendo una sensibilidad, una especificad y una exactitud de 0.90. Por lo tanto este sistema parece prometedor para la diferenciación automática, gold-standard de hipopneas centrales y obstructivas. Finalmente se propone un sistema no-invasivo para la diferenciación automática de hipopneas centrales y obstructivas. Se propone utilizar la señal de flujo respiratorio para la diferenciación utilizando características de los ciclos inspiratorios de cada hipopnea, entre ellos los patrones flattening. Este sistema automático no-invasivo es una combinación de los sistemas anteriormente presentados y se valida mediante las anotaciones gold-standard obtenidas mediante la señal de Pes por expertos humanos. Los resultados de este sistema son comparados a los resultados obtenidos por expertos humanos que utilizaron un nuevo algoritmo no-invasivo para la diferenciación manual de hipopneas. Los resultados del sistema automático no-invasivo son prometedores y muestran la viabilidad de la metodología empleada. Una vez haya sido validado extensivamente, se ha propuesto este algoritmo para su utilización en dispositivos de terapia de TRS desarrollados por uno de los socios cooperantes en este proyecto.The assessment of respiratory effort during sleep is of major importance for the correct identification of respiratory events in sleep-disordered breathing (SDB), the correct diagnosis of SDB-related pathologies and the consequent choice of treatment. Currently, respiratory effort is usually assessed in night polysomnography (NPSG) with imprecise techniques and manually evaluated by human experts, resulting in a laborious task with significant limitations and missclassifications.The main objective of this thesis is to present new methods for the automatic, invasive and non-invasive assessment of respiratory effort and changes in upper airway (UA) obstruction. Specifically, the application of these methods should, in between others, allow the automatic invasive and non-invasive differentiation of obstructive and central respiratory events during sleep.For this purpose, a completely new NPSG database consisting of 28 patients with systematic esophageal pressure (Pes) measurement was acquired. Pes is currently considered the gold-standard to assess respiratory effort and identify respiratory events in SDB. However, the invasiveness and complexity of Pes measurement prevents its use in clinical routine, underlining the importance of this new database. . . All the processing methods developed in this thesis will consequently be validated with the gold-standard Pes-signal in order to ensure their clinical validity.In a first step, an (invasive) automatic system for the classification of inspiratory flow limitation (IFL) in the inspiratory cycles is presented.IFL has been defined as a lack of increase in airflow despite increasing respiratory effort, which normally results in a characteristic inspiratory airflow pattern (flattening). A total of 38,782 breaths were extracted and automatically analyzed. An exponential model is proposed to reproduce the relationship between Pes and airflow of an inspiration and achieve an objective assessment of changes in upper airway obstruction. The characterization performance of the model is appraised with three evaluation parameters: mean-squared-error when estimating resistance at peakpressure,coefficient of determination and assessment of IFL episodes. The model's results are compared to the two best-performing models in the literature. The results indicated that the exponential model characterizes IFL and assesses levels of upper airway obstruction with the highest accuracy and objectivity.The obtained gold-standard IFL annotations were then employed to train, test and validate a new automatic, non-invasive IFL classification system by means of the nasal airflow signal. Discriminant Analysis, Support Vector Machines and Adaboost algorithms were employed to objectively classify breaths non-invasively with features extracted from the time and frequency domains of the breaths' flow patterns. The new non-invasive automatic classification system also succeeded identifying IFL episodes, achieving a sensitivity of 0.87 and a specificity of 0.85.The differentiation between obstructive and central respiratory events is one of the most recurrent tasks in the diagnosis of sleep disordered breathing, but only Pes measurement allows the gold-standard differentiation of these events. Recently new techniques have been proposed to allow the non-invasive differentiation of hypopneas. However, their adoption has been slow due to their limited clinical validation, as the creation of manual, gold-standard validation sets by human experts is a cumbersome procedure. In this study, a new system is proposed for an objective automatic, gold-standard differentiation between obstructive and central hypopneas with the esophageal pressure signal. An overall of 769 hypopneas of 28 patients were manually scored by human experts to create a gold-standard validation set. Then, features were extracted from each hypopnea to train and test classifiers (Discriminant Analysis, Support Vector Machines and adaboost classifiers) to differentiate between central and obstructive hypopneas with the gold-standard esophageal pressure signal. The automatic differentiation system achieved promising results, with a sensitivity of 0.82, a specificity of 0.87 and an accuracy of 0.85. Hence, this system seems promising for an automatic, goldstandard differentiation between obstructive and central hypopneas.Finally, a non-invasive system is proposed for the automatic differentiation of central and obstructive hypopneas. Only the airflow signal is used for the differentiation, as features of the inspiratory cycles of the hypopnea, such as the flattening patterns, is used. The automatic, non-invasive system represents a combination of the systems that have been presented before and it was validated with the gold-standard scorings obtained with the Pes-signal by human experts. The outcome is compared to the results obtained by human scorers that applied a new non-invasive algorithm for the manual differentiation of hypopneas. The non-invasive system's results are promising and show the viability of this technique. Once validated, this algorithm has been proposed to be used in therapy devices developed by one of the partner institutions cooperating in this project

Airway surgery for obstructive sleep apnea and partial upper airway obstruction during sleep

This study analyzed the feasibility and efficacy of surgical therapies in patients with sleep-disordered breathing ranging from partial upper airway obstruction during sleep to severe obstructive sleep apnea syndrome. The surgical procedures evaluated were tracheostomy, laser-assisted uvulopalatoplasty (LUPP) and uvulopalatopharyngoplasty (UPPP) with laser or ultrasound scalpel. Obstructive sleep apnea and partial upper airway obstruction during sleep were measured with the static charge-sensitive bed (SCSB) and pulse oximeter. The patients with severe obstructive sleep apnea syndrome were treated with tracheostomy. Palatal surgery was performed only if the upper airway narrowing occurred exclusively at the soft palate level in patients with partial upper airway obstruction during sleep. The ultrasound scalpel technique was compared to laser-assisted UPPP. The efficacy of LUPP to reduce partial upper airway obstruction during sleep was assessed and histology of uvulopalatal specimen was compared to body fat distributional parameters and sleep study findings. Tracheostomy was effective therapy in severe obstructive sleep apnea. Partial upper airway obstruction and arterial oxyhemoglobin desaturation index during sleep decreased significantly after LUPP. The minimal retropalatal airway dimension increased and soft palate collapsibility decreased at the level where the velopharyngeal obstruction had occurred before the surgery. Ultrasound scalpel did not offer any significant benefits over the laser-assisted technique, except fewer postoperative haemorrhage events. The loose connective tissue as a manifestation of edema was the only histological finding showing correlation with partial upper airway obstruction parameters of SCSB. Tracheostomy remains a life-saving therapy and also long-term option when adherence to CPAP fails in patients with obstructive sleep apnea syndrome. LUPP effectively reduces partial upper airway obstruction during sleep provided that obstruction at the other levels than the soft palate and uvula were preoperatively excluded. Technically the ultrasound scalpel or laser surgeries are equal. In patients with partial upper airway obstruction the loose connective tissue is more important than fat accumulation in the soft palate. This supports the hypothesis that edema is a primary trigger for aggravation of upper airway narrowing during sleep at the soft palate level and evolution towards partial or complete upper airway obstruction during sleep.Siirretty Doriast

Liikkuva potilas: moniparametrisen hengitystaajuusmittauksen käyttökelpoisuus

Respiratory rate is one of the vital signs used to measure the body’s general physical health. Abnormal respiratory rate or a change in breathing frequency may indicate deterioration in the condition of a patient. Thus, respiratory rate measurement would benefit the mobile patients on general hospital wards where no continuous monitoring exists. This environment requests wireless and reliable respiratory monitoring that would be robust against motion artefacts that impede the reliability of common respiratory rate measurements currently available. Electrocardiography (ECG) and photoplethysmography (PPG) are common measurements in intensive care but also in sub-acute care setting. Respiration modulates the ECG and PPG waveforms in several ways that can be exploited to derive respiratory rate from these physiological signals. In ECG, the effect of breathing is seen as both amplitude and frequency modulation, whereas in PPG also baseline modulation is present. This thesis investigated the feasibility of ECG and pulse oximetry derived respiratory rate measurements during different activities and motion states. The performances of these derived methods were evaluated together with impedance pneumography and respiratory inductive plethysmography against capnography reference using statistical analysis. A major part of this thesis consisted of the data collection, signal processing and algorithm development required to create these derived methods. According to the results acquired, the use of ECG-derived respiration (EDR) methods based on QRS-amplitude as part of a multi-parameter respiratory rate algorithm would be feasible. However, all evaluated pulse oximetry derived respiration (PDR) methods were found to be unfit for use due to high susceptibility to motion artefacts. The development of a multi-parameter respiratory rate algorithm continues.Hengitystaajuus luetaan yhdeksi kehon yleisestä terveydestä kertovaksi vitaaliparametriksi. Epänormaali hengitystaajuus tai hengitystaajuuden muutos voi olla merkki potilaan kunnon huononemisesta ja siksi hengitystaajuuden seurannasta olisi hyötyä myös sairaaloiden vuodeosastoilla, missä potilaat liikkuvat ilman jatkuvaa valvontaa. Tällaisessa ympäristössä hengityksen seurannan tulisi toimia langattomasti ja luotettavasti. Monet yleisesti käytetyt hengitystaajuusmittaukset kärsivät kuitenkin liikkeen aiheuttamista häiriöistä, jotka heikentävät menetelmien luotettavuutta. Elektrokardiografia (EKG) ja fotopletysmografia (PPG) ovat yleisiä mittauksia myös tehohoidon ulkopuolella. Hengitys vaikuttaa näiden fysiologisten signaalien muotoon usealla tavalla, joita voidaan hyödyntää hengitystiedon johtamiseen näistä parametreistä. Sydänsähkökäyrän QRS-kompeksien amplitudi ja sykevälivaihtelu ovat yhteydessä hengitykseen samoin kuin fotopletysmografisen pulssiaallon perusviiva, amplitudi sekä pulssivälivaihtelu. Tässä diplomityössä tutkittiin EKG:stä ja PPG:stä johdettujen hengitystaajuusmittausten käyttökelpoisuutta erilaisissa liiketilanteissa. Näiden johdettujen menetelmien suorituskykyä verrattiin tilastollisen analyysin keinoin impedanssipneumografian ja hengitysinduktiivisen pletysmografian kanssa kapnografialla mitattuja vertailuarvoja vastaan. Työ koostui suurelta osin myös näiden menetelmien luomiseen vaaditusta aineiston keräämisestä, signaalinkäsittelystä sekä algoritmikehityksestä. Saatujen tulosten perusteella EKG:stä johdetut amplitudipohjaiset menetelmät olisivat hyödyllisiä moniparametrisessa hengitystaajuusmittauksessa käytettynä. Sen sijaan kaikki kehitetyt PPG:stä johdetut hengitystaajuusmenetelmät todettiin käyttökelvottomiksi liikkeen aiheuttamien häiriöiden vuoksi. Moniparametrisen hengitystaajuusmittauksen kehitystyö jatkuu