Huomaamattomat mittausmenetelmät unen laadun tarkkailussa

Sleep is an important part of health and well-being. While sleep quantity is directly measurable, sleep quality has traditionally been assessed with subjective methods such as questionnaires. The study of sleep disorders has for a long time been confined to clinical environments, and patients have had to endure cumbersome procedures involving multiple electrodes placed on the body. Recent developments in sensor technology as well as data analysis methods have enabled continuous, unobtrusive sleep data recording in the home environment. This has opened new possibilities for studying various sleep parameters and their effect on the quality of sleep. This thesis consists of two parts. The first part is a literature review examining the field of sleep quality research with focus on the application of intelligent methods and signal processing. The second part is a descriptive data analysis look at sleep data obtained with non-invasive sensors.Uni on terveyden ja hyvinvoinnin keskeinen tekijä. Unen määrä on helposti mitattavissa, mutta unen laatua on perinteisesti seurattu kyselylomakkeiden kaltaisin subjektiivisin menetelmin. Unihäiriöiden tutkiminen on pitkään rajoittunut kliinisiin ympäristöihin, ja potilaiden on täytynyt sietää hankalia tutkimusmenetelmiä useine kehoon kiinnitettävine elektrodeineen. Anturiteknologian ja data-analyysimenetelmien kehittyminen on mahdollistanut unidatan jatkuvan ja huomaamattoman tallentamisen kotiympäristössä. Tämä on avannut uusia mahdollisuuksia sekä unen ominaisuuksien että niiden unen laatuun vaikuttavien tekijöiden tutkimiselle. Tämä tutkimus jakautuu kahteen osaan. Ensimmäinen osa on kirjallisuuskatsaus unen laadun tutkimukseen, painopisteenä älykkäiden menetelmien ja signaalinkäsittelyn soveltaminen. Toisessa osassa esitellään huomaamattomilla sensoreilla kerättävän unidatan tutkimista ja sen deskriptiivistä data-analyysiä, esimerkkinä ballistokardiografia

The feasibility of the Emfit movement sensor as an automated screening tool for sleep apnea in the ischemic stroke patients

Stroke is a common cause of death and a major reason for disability. Stroke survivors can have very difficult symptoms and require very intensive and expensive rehabilitation. Sleep disordered breathing, sleep apnea, is common among stroke patients, it's a high risk factor for recurrent stroke and untreated sleep apnea has a negative influence on the stroke recovery. All stroke patients are recommended to be measured for sleep apnea, but the lack of resources don't allow it. Therefore there is a need for a screening tool to find the stroke patients who need the measurement most and who benefit the most of the treatment of the sleep apnea. We studied the possibility to use the Emfit movement sensor combined with a pulse oximeter as a screening tool. The Emfit movement sensor doesn't have connections to the patient, therefore it wouldn't require lots of resources to set up the measurement and there are no contacts that can cause interference during the measurement. The automatic scoring of the measurement would remove the need for an expert to manually score every measurement. The test subjects were measured at the same night using both the Emfit movement sensor and a conventional respiratory polygraphy device. The Emfit movement sensor and the standard respiratory polygraphy measurements were scored using Noxturnal's automatic analysis tool and the results were compared. The results were also compared to the manual scoring of the standard respiratory polygraphy. The Emfit movement sensor measurement slightly overestimates the apnea hypopnea index, as does the automatically scored standard respiratory polygraphy too. The automatic analysis ability to detect correctly the duration and timing of a respiratory event in the Emfit movement sensor measurement seems to depend on the amount of noise in the measurement. Our study indicates that the Emfit movement sensor has potential to be used as a screening tool for sleep apnea in the ischemic stroke patients, but the automatic analysis still needs improvements to provide more accurate results

High-Performance Accelerometer Based On Asymmetric Gapped Cantilevers For Physiological Acoustic Sensing

Continuous or mobile monitoring of physiological sounds is expected to play important role in the emerging mobile healthcare field. Because of the miniature size, low cost, and easy installation, accelerometer is an excellent choice for continuous physiological acoustic signal monitoring. However, in order to capture the detailed information in the physiological signals for clinical diagnostic purpose, there are more demanding requirements on the sensitivity/noise performance of accelerometers. In this thesis, a unique piezoelectric accelerometer based on the asymmetric gapped cantilever which exhibits significantly improved sensitivity is extensively studied. A meso-scale prototype is developed for capturing the high quality cardio and respiratory sounds on healthy people as well as on heart failure patients. A cascaded gapped cantilever based accelerometer is also explored for low frequency vibration sensing applications such as ballistocardiogram monitoring. Finally, to address the power issues of wireless sensors such as wireless wearable health monitors, a wide band vibration energy harvester based on a folded gapped cantilever is developed and demonstrated on a ceiling air condition unit

Wearable and Nearable Biosensors and Systems for Healthcare

Biosensors and systems in the form of wearables and “nearables” (i.e., everyday sensorized objects with transmitting capabilities such as smartphones) are rapidly evolving for use in healthcare. Unlike conventional approaches, these technologies can enable seamless or on-demand physiological monitoring, anytime and anywhere. Such monitoring can help transform healthcare from the current reactive, one-size-fits-all, hospital-centered approach into a future proactive, personalized, decentralized structure. Wearable and nearable biosensors and systems have been made possible through integrated innovations in sensor design, electronics, data transmission, power management, and signal processing. Although much progress has been made in this field, many open challenges for the scientific community remain, especially for those applications requiring high accuracy. This book contains the 12 papers that constituted a recent Special Issue of Sensors sharing the same title. The aim of the initiative was to provide a collection of state-of-the-art investigations on wearables and nearables, in order to stimulate technological advances and the use of the technology to benefit healthcare. The topics covered by the book offer both depth and breadth pertaining to wearable and nearable technology. They include new biosensors and data transmission techniques, studies on accelerometers, signal processing, and cardiovascular monitoring, clinical applications, and validation of commercial devices

Detection and Assessment of Sleep-Disordered Breathing with Special Interest of Prolonged Partial Obstruction

Sleep-disordered breathing (SDB) has become more common and puts more strain on public health services than ever before. Obstructive sleep apnea (OSA) and its health consequences such as different cardiovascular diseases are nowadays well recognized. In addition to OSA, attention has recently been paid to another SDB; prolonged partial obstruction. However, it is often undiagnosed and easily left untreated because of the low number of respiratory events during polysomnography recording. This patient group has found to present with more atypical subjective symptoms than OSA patients.Polysomnography (PSG) is considered to be the gold standard in reference methods in SDB diagnostics. PSG is a demanding and laborious multichannel recording method and often requires subjects to spend one night in a sleep laboratory. There is long tradition in Finland to use mattress sensors in SDB diagnostics. Recently, smaller electromechanical film transducer (Emfit) mattresses have replaced the old Static Charge-Sensitive Bed (SCSB) mattresses. However, a proper clinical validation of Emfit mattresses in SDB diagnostics has not been carried out.In this work, the use of Emfit recording in the detection of sleep apneas, hypopneas, and prolonged partial obstruction with increased respiratory effort was evaluated. The general aim of the thesis is to develop and improve the diagnostic methods for sleep-related breathing disorders.Comparisons with both PSG with nasal pressure recording and transesophageal pressure were made. Special attention was paid to the existence of the spiking phenomenon in the Emfit mattress in relation to changes in negative intrathoracic pressure in estimating increased respiratory effort. This entails monitoring the esophageal pressure as a part of nocturnal polysomnography. The recording method is demanding and uncomfortable and is usually not used with ordinary sleep laboratory patients. Thus, reliable and easy indirect quantification methods for respiratory effort are needed in clinical work. According to the results presented in this work, the Emfit signal reveals increased respiratory effort as well as apneas/hypopneas.To find out the prevalence and consequences of prolonged partial obstruction among sleep laboratory patients was another aim of this thesis. This was done by retrospective analyses of sleep laboratory patients from one year. The prevalence of patients with prolonged partial obstruction was 11%. They were as sleepy as OSA patients, but their life quality was worse, as assessed by a survey. These results, along with the findings of the heart rate variation evaluation carried out in this thesis, suggest that prolonged partial obstruction and OSA should be considered as different entities of SDB.With the Emfit mattress sensor, the SDB types can be differentiated, which is expected to enhance the accuracy of diagnostics. However, there is increasing need for easy and cheap screening methods to evaluate nocturnal breathing. In this respect, the usability of compressed tracheal sound signal scoring in SDB screening was estimated. The method reveals apneas and hypopneas but, according to the present findings, it can also be used in the detection of prolonged partial obstruction. The findings encourage the use of compressed tracheal sound analysis in screening different SDB.The analysis of sleep recordings is still based on a doctor’s subjective and visual estimation. To date, no generally accepted and sufficiently reliable automatic analysis method exists. Robust, automatic quantification methods with easier techniques for non-invasive sleep recording would enable the analysis methods to be also used for screening purposes. In this technology-orientated world, people could take much more responsibility and take care of themselves better by following their own biosignals and by changing their health habits earlier. The need for good sleep as a necessity for good life and health is widely recognized

Unobtrusive Monitoring of Heart Rate and Respiration Rate during Sleep

Sleep deprivation has various adverse psychological and physiological effects. The effects range from decreased vigilance causing an increased risk of e.g. traffic accidents to a decreased immune response causing an increased risk of falling ill. Prevalence of the most common sleep disorder, insomnia can be, depending on the study, as high as 30 % in adult population. Physiological information measured unobtrusively during sleep can be used to assess the quantity and the quality of sleep by detecting sleeping patterns and possible sleep disorders. The parameters derived from the signals measured with unobtrusive sensors may include all or some of the following: heartbeat intervals, respiration cycle lengths, and movements. The information can be used in wellness applications that include self-monitoring of the sleep quality or it can also be used for the screening of sleep disorders and in following-up of the effect of a medical treatment. Unobtrusive sensors do not cause excessive discomfort or inconvenience to the user and are thus suitable for long-term monitoring. Even though the monitoring itself does not solve the sleeping problems, it can encourage the users to pay more attention on their sleep. While unobtrusive sensors are convenient to use, their common drawback is that the quality of the signals they produce is not as good as with conventional measurement methods. Movement artifacts, for example, can make the detection of the heartbeat intervals and respiration impossible. The accuracy and the availability of the physiological information extracted from the signals however depend on the measurement principle and the signal analysis methods used. Three different measurement systems were constructed in the studies included in the thesis and signal processing methods were developed for detecting heartbeat intervals and respiration cycle lengths from the measured signals. The performance of the measurement systems and the signal analysis methods were evaluated separately for each system with healthy young adult subjects. The detection of physiological information with the three systems was based on the measurement of ballistocardiographic and respiration movement signals with force sensors placed under the bedposts, the measurement of electrocardiographic (ECG) signal with textile electrodes attached to the bed sheet, and the measurement of the ECG signal with non-contact capacitive electrodes. Combining the information produced by different measurement methods for improving the detection performance was also tested. From the evaluated methods, the most accurate heartbeat interval information was obtained with contact electrodes attached to the bed sheet. The same method also provided the highest heart rate detection coverage. This monitoring method, however, has a limitation that it requires a naked upper body, which is not necessarily acceptable for everyone. For respiration cycle length detection, better results were achieved by using signals recorded with force sensors placed under a bedpost than when extracting the respiration information from the ECG signal recorded with textile bed sheet electrodes. From the data quality point of view, an ideal night-time physiological monitoring system would include a contact ECG measurement for the heart rate monitoring and force sensors for the respiration monitoring. The force sensor signals could also be used for movement detection

Continuous sensing and quantification of body motion in infants:A systematic review

Abnormal body motion in infants may be associated with neurodevelopmental delay or critical illness. In contrast to continuous patient monitoring of the basic vitals, the body motion of infants is only determined by discrete periodic clinical observations of caregivers, leaving the infants unattended for observation for a longer time. One step to fill this gap is to introduce and compare different sensing technologies that are suitable for continuous infant body motion quantification. Therefore, we conducted this systematic review for infant body motion quantification based on the PRISMA method (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). In this systematic review, we introduce and compare several sensing technologies with motion quantification in different clinical applications. We discuss the pros and cons of each sensing technology for motion quantification. Additionally, we highlight the clinical value and prospects of infant motion monitoring. Finally, we provide suggestions with specific needs in clinical practice, which can be referred by clinical users for their implementation. Our findings suggest that motion quantification can improve the performance of vital sign monitoring, and can provide clinical value to the diagnosis of complications in infants.</p

The Meaning of Sleep Quality: A Survey of Available Technologies

Sleep is an important part of the human daily routine. Restoring sleep is strongly related to a better physical, cognitive, and psychological well-being. By contrast, poor or disordered sleep leads to possible impairments of cognitive and psychological functioning and to a worsened general physical health. In this context, understanding changes in sleep quality becomes a research imperative that leads to the need for the definition of what restoring or quality sleep means. This understanding of what "sleep quality" means requires a cross-domain investigation. It arises the need for a comprehensive study that offers a complete taxonomy of sleep monitoring systems, with a focus on sleep quality, and that gives useful insights about which combination of metrics, signals, and sleep variables is the best in relation to different categories of users. The proposed study is focused on systematically categorizing the methods and approaches for sleep quality understanding, with an emphasis on technological approaches, including wearable, on-bed, and actigraphy devices. It offers a systematic review for researchers who are interested in sleep quality identification tasks, and highlights strengths and weaknesses of state-of-the-art metrics and solutions in order to suggest the best choice for new potential research challenges in the field. Another important outcome of the proposed work is the study of the impact on the identified signal metrics and solutions of the different target user populations with their specific user requirements

A contribution to unobtrusive measurement methods for sleep monitoring based on magnetic induction technique

Sleep monitoring is of major importance for various medical areas such as the detection and treatment of sleep disorders, assessment of different medical conditions or medications' effects over sleep quality, and mortality risk assessment associated with sleep patterns in adults and children. It is a challenging area of medical problems due to both privacy issues and technical considerations. It calls for monitoring methods in which the patient's natural state is less interfered. An ideal device would be non-invasive, minimally restrictive, robust enough to compensate movements of the patients, and would operate without relying on patient's cooperation. Non-contact methods for monitoring vital signs and physiological activities have been given lots of attention recently. In addition to the sleep monitoring, various other medical applications demand for less-obtrusive continuous respiratory and cardiac activity monitoring methods. Applications such as home health care, neonates and burned victims monitoring and applications in which using the traditional skin electrodes may worsen or disturb the conditions of the patient, call for new contact-less approaches for monitoring purposes. This thesis focuses on the design and development of an unobtrusive, vital sign monitoring system particularly suited for long-term monitoring. The system is a low-cost, non-contact planar system designed to be placed under the bed or mattress for applications such as sleep monitoring, neonates monitoring, etc. The system is based on the magnetic induction sensing method, designed to infer presence on the bed, breathing and cardiac activity and consists of two coils for excitation and detection. The receiver is an asymmetric planar gradiometer which has been optimized to minimize the impact of the primary magnetic field. The signal acquisition system has been designed using simple electronics to avoid ending up with a complex expensive system. Safety study indicates that the developed system is safe to be used for continuous monitoring of breathing and cardiac activity for patients, in terms of being exposed to magnetic fields. The experimental results were compared with reference signals obtained by other sensors (photoplethysmogram, respiratory pressure transducer), for benchmarking and identifying the advantages and drawbacks of the new system regarding other techniques. Experimental results confirm the suitability and safety of the sensor for long-term cardiac and respiratory monitoring. The system is able to detect respiration and cardiac activity as well as presence on the bed and changes in position.Los métodos sin contacto para monitorizar signos vitales y actividades fisiológicas reciben cada día más atención. Además de la monitorización del sueño, otras aplicaciones médicas requieren métodos de monitorización de la actividad respiratoria y cardiaca de forma continua y menos intrusiva. Aplicaciones como el cuidado de la salud en el hogar, los bebes prematuros y las víctimas de quemaduras, en las que el uso de los electrodos tradicionales sobre la piel puede empeorar o perturbar las condiciones del paciente, requieren nuevos enfoques de monitorización sin contacto. Esta tesis se centra en el diseño y desarrollo de un sistema de monitorización de signos vitales sin contacto y particularmente adecuado para la monitorización a largo plazo. El sistema es un sistema plano sin contacto de bajo coste diseñado para ser colocado bajo la cama o colchón para aplicaciones tales como monitoreo del sueño, monitoreo de recién nacidos, etc. El sistema se basa en el método de detección por inducción magnética, diseñado para inferir la presencia en la cama, la respiración y la actividad cardíaca y consiste en dos bobinas, una para excitación y otra para detección. El receptor es un nuevo gradiómetro plano asimétrico que ha sido optimizado para minimizar el impacto del campo magnético primario. El sistema de adquisición de señales ha sido diseñado utilizando una electrónica sencilla para evitar terminar con un sistema complicado y caro. Se ha realizado un estudio de seguridad, en términos de exposición a campos magnéticos, que indica que el sistema desarrollado es seguro para ser usado en la monitorización de la respiración y actividad cardiaca. Los resultados experimentales se compararon con las señales de referencia obtenidas por otros sensores (fotopletismografia y transductor de presión bajo el colchón), para realizar un benchmarking e identificación de las ventajas e inconvenientes del nuevo sistema con respecto a otras técnicas. Los resultados experimentales confirman la idoneidad y seguridad del sensor diseñado para monitorización continua y prolongada de la actividad cardiaca y respiratoria. El sistema es capaz de detectar la respiración y la actividad cardíaca, así como la presencia en la cama y los cambios de posiciónPostprint (published version