Examining the Relationship between Sleep Posture and Morning Spinal Symptoms in the Habitual Environment Using Infrared Cameras

Introduction: Sleeping is generally considered a period for rest and recovery, however some people wake with spinal symptoms not present on going to sleep and seek treatment. It has been clinically postulated that some sleeping postures, especially those involving sustained end range rotation or extension, can provoke pain sensitive spinal tissues. While sleep research generally has blossomed, little attention has been paid to the physical effects of nocturnal posture on waking spinal symptoms. Furthermore, sleep research is generally conducted in high technology sleep laboratories that are expensive to operate and usually only accessible in metropolitan centers limiting availability to a broader population. We aimed to develop a recording protocol that was low cost, unobtrusive and portable, enabling sleep posture assessment to occur in a person’s habitual environment. Method: Fifteen participants were recruited by word of mouth. Participants completed a Pre-Sleep Questionnaire. Two infrared cameras (placed overhead and foot end of bed) plus associated recording equipment were installed in their habitual sleeping area. One camera recorded continuously, the other camera was activated by motion detection. Recordings occurred over two consecutive nights, commencing automatically at 2000hrs and stopping at 0800hrs. Four sleeping postures were defined; supine, prone, supported sidelying, where the spine is neutral and ¾ sidelying, where the spine is rotated and extended. Recordings were viewed, posture classified and the time spent in each posture calculated. Time spent in each posture for night one and night two was analyzed to determine the presence of a first night effect. Results: The protocol was effective in capturing good quality video data. Utilising motion detection reduced analysis time by 50%. The classification system had high intra-rater reliability for all four postures (ICC > 0.91). No first night effect was detected. Participants’ self-report was accurate for the proportion of the night spent in supine (ICC=0.7 95% CI 0.32 to 0.89) but not for the other three postures (ICC < 0.32 p ≤ 0.17). However when combining the two sidelying postures, self-report was accurate (ICC=0.57; 95%CI 0.10 to 0.83; p=0.01). There were no significant relationships found between the four postures and morning spinal symptoms. Conclusion: The protocol tested provided a low cost, reliable, unobtrusive and portable method to assess sleep posture in the habitual environment that should be suitable for clinical and research purposes

Sleeping mattress determinants and evaluation: a biomechanical review and critique

Background Sleeping mattress parameters significantly influence sleeping comfort and health, as reflected by the extensive investigations of sleeping support biomechanics to prevent sleep-related musculoskeletal problems. Methodology Herein, we review the current trends, research methodologies, and determinants of mattress biomechanics research, summarizing evidence published since 2008. In particular, we scrutinize 18 articles dealing with the development of new designs, recommendation criteria, instruments/methods of spine alignment evaluation, and comparative evaluation of different designs. Results The review demonstrated that mattress designs have strived for customization, regional features, and real-time active control to adapt to the biomechanical features of different body builds and postures. However, the suggested threshold or target values for desirable spine alignment and body pressure distribution during sleep cannot yet be justified in view of the lack of sufficient evidence. Conclusions It is necessary to formulate standard objectives and protocols for carrying out mattress evaluation

Design and Implementation of a Smart Sensor for Respiratory Rate Monitoring

This work presents the design, development and implementation of a smart sensor to monitor the respiratory rate. This sensor is aimed at overcoming the drawbacks of other systems currently available in market, namely, devices that are costly, uncomfortable, difficult-to-install, provide low detection sensitivity, and little-to-null patient-to-patient calibration. The device is based on capacitive sensing by means of an LC oscillator. Experimental results show that the sensor meets the necessary requirements, making feasible the proposed monitoring system with the technology usedMinisterio de Ciencia e Innovación y Unión Europea FPA2010-22131-C02-02Consejo Andaluz de Innovación, Ciencia y Empresa P08-TIC-04069 y P10-TIC- 631

A Multi-Sensor Platform for Microcurrent Skin Stimulation during Slow Wave Sleep

Insu cient and low quality sleep is related to several health issues and social outcomes. Regular sleep study conducted in a sleep laboratory is impractical and expensive. As a result, miniature and non-invasive sleep monitoring devices provide an accessible sleep data. Though not as accurate as polysomnography, these devices provide useful data to the subject by tracking sleep patterns regularly. On the other hand, proactive improvement of sleep quality has been limited to pharmacological solutions and cranial electrotherapy stimulation. An alternative approach and a potential solution to sleep deprivation is a non-pharmacological technique which involves the application of micro-current electrical stimulation on the palm during Slow Wave Sleep (SWS). This thesis presents the development of a miniature device for SWS detection and electrocutaneous stimulation. Several sensors are embedded in the prototype device to measure physiological data such as body movement, electrodermal activity, heart rate, and skin and ambient temperature. Furthermore, the prototype device provides local storage and wireless transfer for data acquisition. The quality of the sensor data during sleep are discussed in this thesis. For future work, the results of this thesis shall be the used as a baseline to develop a more re ned prototype for clinical trials in sleep laboratories

Smart Sensors for Healthcare and Medical Applications

This book focuses on new sensing technologies, measurement techniques, and their applications in medicine and healthcare. Specifically, the book briefly describes the potential of smart sensors in the aforementioned applications, collecting 24 articles selected and published in the Special Issue “Smart Sensors for Healthcare and Medical Applications”. We proposed this topic, being aware of the pivotal role that smart sensors can play in the improvement of healthcare services in both acute and chronic conditions as well as in prevention for a healthy life and active aging. The articles selected in this book cover a variety of topics related to the design, validation, and application of smart sensors to healthcare

Embedded neonatal respiration monitoring

Current neonatal monitoring methods are not very comfortable for the neonate. The sticky electrodes used to measure the heart and breathing rate, can cause skin irritations and skin lesions when being pulled off. Furthermore, all the wires create a barrier for parents to touch and interact with their child.The E-Nemo (Embedded Neonatal Monitoring) project intends to change the way in which (premature) neonates are monitored in the neonatal intensive care unit (NICU). The aim of E-Nemo is to create a patient support system that assures comfort for the neonate and provides a more friendly environment for parental bonding, whilst keeping the current quality of vital sign monitoring.This report concerns the work related to the monitoring of only one vitals sign, namely: respiration.The aim of the E-Nemo respiration monitoring project is to design and develop a neonatal respiration monitoring system using sensors embedded in a patient support system (e.g., a mattress).A key challenge of this system is achieving the same robustness and reliability as existing monitoring equipment for neonates.Before the respiration sensor can be moved from the chest of the neonate into the underlying support system some questions need to be answered. Such as: Where can we place this sensor? Is one sensor enough? Which type of sensor is most suitable?To answer these (and more) questions regarding the design of the neonatal respiration monitoring system, a clinical trial was conducted at the NICU of the Máxima Medical Centre in Veldhoven.During this trial firsthand knowledge on the position and movement of neonates in an incubator, and general NICU workflow issues was gained.The clinical trial has resulted in a list of design specifications for the neonatal respiration monitoring system and a better understanding of the workflow and possible measurement disturbances in a NICU.Furthermore, this project has successfully demonstrated the possibility of measuring the neonatal respiration signal without direct skin contact with the neonate. However, in order to achieve the quality and reliability needed for intensive care respiration monitoring more research is necessary.Measuring the deformation of the mattress is expected to be a better measure for the respiration movements, than the pressure changes underneath the mattress which were measured in this study.Furthermore, more research is needed to determine the accuracy that will be demanded of the system, as this research has demonstrated that the current gold standard (transthoracic impedance plethysmography) does not function continously either

Eine systematisierte Übersichtsarbeit

Zentrale Kriterien zur Identifikation einer Dekubitusgefährdung sind Mobilität und Aktivität. In der Praxis und Forschung ist es derzeitjedoch noch nicht möglich, diese Parameter ausreichend reliabel zu erfassen. Neu entwickelte technische Verfahren ermöglichendie metrische Messung der Bewegung von im Bett liegenden Menschen. Offen ist jedoch, wie die damit entstehenden Daten zurBewegungshäufigkeit zu interpretieren sind. Deswegen wurde eine systematisierte Literaturübersicht durchgeführt, um Normalwertezu Häufigkeiten von Bewegungen im Schlaf sowie kritische Werte zur Diagnostik der Dekubitusgefährdung zu ermitteln. Gesuchtwurde in den Datenbanken, MedLine, Cinahl, Trip Database, der Cochrane Library, PEDro, Google Scholar sowie in Referenzlistenfür den Zeitraum 2008–2013. Eingeschlossen werden konnten eine Übersichtsarbeit sowie neun Primärstudien. Allgemein sind in den Studien erhebliche methodische Mängel festzustellen. In den Studien der Schlaf- und Dekubitusforschung werden unterschiedlicheMessmethoden zur Erfassung von Bewegung im Schlaf bzw. im Bett eingesetzt. Die beobachtete Heterogenität zwischen denStudien macht einen Vergleich der Ergebnisse kaum möglich. In beiden Disziplinen werden zudem weniger Normalwerte berichtetals Zusammenhänge mit pathologischen Zuständen wie Schlafqualität und Dekubitusgefährdung. Nach der kritischen Durchsichtder Studien gibt es keine validen Zahlen zur Häufigkeit von Bewegung im Schlaf sowie zu kritischen Werten zur Diagnostik einerDekubitusgefährdung. Zur Interpretation der Ergebnisse neuer Messverfahren ist die Durchführung von Diagnostikstudien zuempfehlen, bei denen „Normalwerte“ und Cut-off-Punkte für dieses Instrument entwickelt sowie in darauffolgenden randomisierten,kontrollierten Studien auf ihre Wirksamkeit evaluiert werden

Data Processing for Device-Free Fine-Grained Occupancy Sensing Using Infrared Sensors

Fine-grained occupancy information plays an essential role for various emerging applications in smart homes, such as personalized thermal comfort control and human behavior analysis. Existing occupancy sensors, such as passive infrared (PIR) sensors generally provide limited coarse information such as motion. However, the detection of fine-grained occupancy information such as stationary presence, posture, identification, and activity tracking can be enabled with the advance of sensor technologies. Among these, infrared sensing is a low-cost, device-free, and privacy-preserving choice that detects the fluctuation (PIR sensors) or the thermal profiles (thermopile array sensors) from objects' infrared radiation. This work focuses on developing data processing models towards fine-grained occupancy sensing using the synchronized low-energy electronically chopped PIR (SLEEPIR) sensor or the thermopile array sensors. The main contributions of this dissertation include: (1) creating and validating the mathematical model of the SLEEPIR sensor output towards stationary occupancy detection; (2) developing the SLEEPIR detection algorithm using statistical features and long-short term memory (LSTM) deep learning; (3) building machine learning framework for posture detection and activity tracking using thermopile array sensors; and (4) creating convolutional neural network (CNN) models for facing direction detection and identification using thermopile array sensors

Ubiquitäre Systeme (Seminar) und Mobile Computing (Proseminar) WS 2016/17. Mobile und Verteilte Systeme. Ubiquitous Computing. Teil XIV

Diese Arbeit wird einen Überblick über virtuelle intelligente Assistenten (VIA), die im deutschen auch oft als Sprachassistenten bezeichnet werden, geben. Es werden die verschiedenen Arten von VIA gezeigt und in welchem Zusammenhang sie momentan schon genutzt werden. Als Beispiel werden einige aktuelle Assistenten dienen. Zudem werden neben den Möglichkeiten der Programme, auch noch die Grenzen dieser Technik dargestellt und mögliche Verbesserungen und Optimierungen für die Zukunft besprochen. Ebenfalls wird das empfindliche Thema Datenschutz mit Bezug auf die VIA behandelt. Am Ende des zweiten Teils gehen wir auf die aktuelle Beliebtheit und Nutzung der Anwendungen ein. Im dritten Abschnitt wird dann die Funktionsweise der Software im Hintergrund der Assistenten betrachtet. Es wird der allgemeine Aufbau eines VIA skizziert. Zudem werden zwei Modelle für die Arbeitsweise der Sprachassistenten betrachtet. Dazu werden auch einige theoretische Konzepte wie Ontologien, Knowledge Graphen und POMDP (partially observable Markov decision process) beleuchtet. Zum Schluss kommt ein Fazit über die weitere Entwicklung der VIA mit Überlegungen für Verbesserungen und Optimierungen