Multidimensional embedded MEMS motion detectors for wearable mechanocardiography and 4D medical imaging

Background: Cardiovascular diseases are the number one cause of death. Of these deaths, almost 80% are due to coronary artery disease (CAD) and cerebrovascular disease. Multidimensional microelectromechanical systems (MEMS) sensors allow measuring the mechanical movement of the heart muscle offering an entirely new and innovative solution to evaluate cardiac rhythm and function. Recent advances in miniaturized motion sensors present an exciting opportunity to study novel device-driven and functional motion detection systems in the areas of both cardiac monitoring and biomedical imaging, for example, in computed tomography (CT) and positron emission tomography (PET). Methods: This Ph.D. work describes a new cardiac motion detection paradigm and measurement technology based on multimodal measuring tools — by tracking the heart’s kinetic activity using micro-sized MEMS sensors — and novel computational approaches — by deploying signal processing and machine learning techniques—for detecting cardiac pathological disorders. In particular, this study focuses on the capability of joint gyrocardiography (GCG) and seismocardiography (SCG) techniques that constitute the mechanocardiography (MCG) concept representing the mechanical characteristics of the cardiac precordial surface vibrations. Results: Experimental analyses showed that integrating multisource sensory data resulted in precise estimation of heart rate with an accuracy of 99% (healthy, n=29), detection of heart arrhythmia (n=435) with an accuracy of 95-97%, ischemic disease indication with approximately 75% accuracy (n=22), as well as significantly improved quality of four-dimensional (4D) cardiac PET images by eliminating motion related inaccuracies using MEMS dual gating approach. Tissue Doppler imaging (TDI) analysis of GCG (healthy, n=9) showed promising results for measuring the cardiac timing intervals and myocardial deformation changes. Conclusion: The findings of this study demonstrate clinical potential of MEMS motion sensors in cardiology that may facilitate in time diagnosis of cardiac abnormalities. Multidimensional MCG can effectively contribute to detecting atrial fibrillation (AFib), myocardial infarction (MI), and CAD. Additionally, MEMS motion sensing improves the reliability and quality of cardiac PET imaging.Moniulotteisten sulautettujen MEMS-liiketunnistimien käyttö sydänkardiografiassa sekä lääketieteellisessä 4D-kuvantamisessa Tausta: Sydän- ja verisuonitaudit ovat yleisin kuolinsyy. Näistä kuolemantapauksista lähes 80% johtuu sepelvaltimotaudista (CAD) ja aivoverenkierron häiriöistä. Moniulotteiset mikroelektromekaaniset järjestelmät (MEMS) mahdollistavat sydänlihaksen mekaanisen liikkeen mittaamisen, mikä puolestaan tarjoaa täysin uudenlaisen ja innovatiivisen ratkaisun sydämen rytmin ja toiminnan arvioimiseksi. Viimeaikaiset teknologiset edistysaskeleet mahdollistavat uusien pienikokoisten liiketunnistusjärjestelmien käyttämisen sydämen toiminnan tutkimuksessa sekä lääketieteellisen kuvantamisen, kuten esimerkiksi tietokonetomografian (CT) ja positroniemissiotomografian (PET), tarkkuuden parantamisessa. Menetelmät: Tämä väitöskirjatyö esittelee uuden sydämen kineettisen toiminnan mittaustekniikan, joka pohjautuu MEMS-anturien käyttöön. Uudet laskennalliset lähestymistavat, jotka perustuvat signaalinkäsittelyyn ja koneoppimiseen, mahdollistavat sydämen patologisten häiriöiden havaitsemisen MEMS-antureista saatavista signaaleista. Tässä tutkimuksessa keskitytään erityisesti mekanokardiografiaan (MCG), joihin kuuluvat gyrokardiografia (GCG) ja seismokardiografia (SCG). Näiden tekniikoiden avulla voidaan mitata kardiorespiratorisen järjestelmän mekaanisia ominaisuuksia. Tulokset: Kokeelliset analyysit osoittivat, että integroimalla usean sensorin dataa voidaan mitata syketiheyttä 99% (terveillä n=29) tarkkuudella, havaita sydämen rytmihäiriöt (n=435) 95-97%, tarkkuudella, sekä havaita iskeeminen sairaus noin 75% tarkkuudella (n=22). Lisäksi MEMS-kaksoistahdistuksen avulla voidaan parantaa sydämen 4D PET-kuvan laatua, kun liikeepätarkkuudet voidaan eliminoida paremmin. Doppler-kuvantamisessa (TDI, Tissue Doppler Imaging) GCG-analyysi (terveillä, n=9) osoitti lupaavia tuloksia sydänsykkeen ajoituksen ja intervallien sekä sydänlihasmuutosten mittaamisessa. Päätelmä: Tämän tutkimuksen tulokset osoittavat, että kardiologisilla MEMS-liikeantureilla on kliinistä potentiaalia sydämen toiminnallisten poikkeavuuksien diagnostisoinnissa. Moniuloitteinen MCG voi edistää eteisvärinän (AFib), sydäninfarktin (MI) ja CAD:n havaitsemista. Lisäksi MEMS-liiketunnistus parantaa sydämen PET-kuvantamisen luotettavuutta ja laatua

An investigation of labour ward care to inform the design of a computerised decision support system for the management of childbirth

Merged with duplicate record 10026.1/622 on 03.04.2017 by CS (TIS)Patient monitoring is a complex task, particularly during childbirth, where assessment of the baby's condition is inferred from the continuous electronic recording of the baby's heart rate pattern and maternal uterine contractions (CTG). Computerised decision support has long been advocated, as difficulties in the interpretation of the CTG have led to failure to intervene and unnecessary intervention. The problem is large, for obstetric litigation now accounts for 80% of the UK National Health Service litigation bill. The Plymouth Perinatal Research Group has developed a computerised decision support system for patient monitoring during childbirth and the UK Medical Research Council has agreed to fund a multicentre randomised trial. The work of this thesis was an investigation of the labour ward care system to inform the human-centred design of the decision support system for patient monitoring in childbirth, prior to the clinical trial. It was recognised that many decision support systems have failed to gain clinical acceptance, as conventional design models were inadequate. Lack of attention to the organisational context of the care system and the process of the direct patient care led to the design of inflexible 'expert' systems, which constrained working practices. A pilot ethnographic study of an existing decision support system, used for the analysis of umbilical cord blood samples, was undertaken to clarify the research approach required for the main study. It was found that barriers to effective use within the wider work system included inadequate implementation and lack of organisational support. A case study approach produced a more comprehensive account of the context and process of the use of the computer system. The main study combined qualitative with quantitative techniques to investigate the system of care in childbirth, both outside and within the delivery room, to provide a unique, holistic perspective. The organisational context of the labour ward was investigated by direct observation of clinicians over the course of their work for 220 hours. Observations were documented and transcribed to computer text files. Patterns of actions and events were coded using ATLAS(ti) data analysis software. The codes were counted and tabulated to model the main features of this labour ward care system, which was expressed in the form of a rich picture diagram. These findings were confirmed by a limited study of five other UK labour wards. The core qualitative categories, derived from the observation data, found a complex and problematic relationship between communication, decision making and accountability. Decisions were often made outside the delivery room and were subject to misinterpretation and bias. The organisational hierarchy made it difficult for junior staff to question clinical management decisions. A system of tacit practice, external demands upon clinicians and transient allocation of junior midwives to labour ward militated against teamwork. This increased the vulnerability of the care of mothers to error. The process of direct patient care, within the individual delivery room, of 20 mothers in labour was captured in a novel audio-video observation study. The 111 hours of first stage labour and 12 hours of second stage labour were recorded and digitised to computer files. Recurrent actions and patterns of behaviour were coded both quantitatively and qualitatively using ATLAS(ti) data analysis software. Midwives left the room on average every 15 minutes to be absent for 27% of the first stage of labour. Record keeping occurred on average every 10 minutes and accounted for 19% of midwives' time. Midwives had little time to talk with mothers and only sat down at the bedside for 15% of the time. Psychosocial support was not given priority. Parents were generally excluded from communication between clinicians yet 108 clinicians took part in the care of the 20 women. Pressures from medicolegal directives and task-orientated imperatives overshadowed meaningful interaction with parents and caused spurious care priorities. This work has revealed the need for a critical reassessment of the type of support that is required for monitoring situations in all areas of medicine. A range of functions, such as shared information displays and models, have been suggested to augment roles and relationships between clinicians and parents to support patient-centred care. The present work has revealed that a combination of computer-based technology and changes to working practice can support the parents, their individual carers and their various roles. In this way the system of care can be more aligned to the objective of a safe and emotionally satisfying birth experience for parents and staff. A further programme of research is required to follow-up the existing studies, develop these new forms of interaction between technology and clinicians, and evaluate their effectiveness. The research methods employed in the present work will provide a more comprehensive evaluation of the decision support system in the forthcoming multicentre trial. The methods of investigation have also been shown to be of relevance to patient safety research, service delivery and training.Plymouth Perinatal Research Group Postgraduate Medical Schoo

Telemedicine

Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios

Characterisation and biomedical application of fabric sensors

The sensors commonly used today to measure human physiological parameters are hard and discrete and not suitable for long term monitoring. A wearable garment with integrated fabric sensors incorporated in an unobtrusive way is highly desirable for long term physiological monitoring, particularly in a non-clinical environment. The aim of this work is to investigate fabric sensors which can be integrated into a garment to allow the unobtrusive monitoring of physiological parameters, primarily for measuring the electrocardiograph (ECG) and respiration. The work focuses on using only dry fabric electrodes where skin preparation and the use of chemical gels or adhesives are not employed. The textile structure used in this study was designed to provide controlled contact pressure, enable construction using common textile processing methods, allow accurate placement of electrodes on the body, allow comfortable fit and be unobtrusive to wear. It was decided to use the knitting method to make bands which incorporated conductive electrodes in order to evaluate different fabric electrodes materials. The detection of respiration using fabric strain sensors did not require electrical contact with the skin. Preliminary experiments were conducted on a single subject to develop a device and methodology. Galvanic skin response and ECG was initially investigated to determine the effectiveness of electrode materials. ECG was established as a more reliable measure and was subsequently used to evaluate the initial performance of the fabric electrodes, and further refine the test methodology on a single subject. Experiments were then conducted on 10 male volunteer participants of reasonable general health having no known heart conditions, with ages 30-55 and BMI 20-30. It was found that fabric sensors which were soft, pliable and flexible have advantages in terms of ability to provide better quality ECG signals and a comfortable bio-interface. Variation in the pressure applied to the electrode directly affects the acquired signal level and a pressure of 2.5KPa is preferred. Multifilament conductive yarns are more easily processed into fabric than monofilament yarns and are generally preferred. Electrodes comprising a conductive polymer treated fabric gave better performance than metal or metal coated yarns. Fabric strain sensors were tested and used to detect respiration on a single subject. It was found that human respiration can be measured using strain sensors such as those comprised of a conductive polymer treated fabric or a fabric incorporating a rigid conductive monofilament fibre

Blind Source Separation for the Processing of Contact-Less Biosignals

(Spatio-temporale) Blind Source Separation (BSS) eignet sich für die Verarbeitung von Multikanal-Messungen im Bereich der kontaktlosen Biosignalerfassung. Ziel der BSS ist dabei die Trennung von (z.B. kardialen) Nutzsignalen und Störsignalen typisch für die kontaktlosen Messtechniken. Das Potential der BSS kann praktisch nur ausgeschöpft werden, wenn (1) ein geeignetes BSS-Modell verwendet wird, welches der Komplexität der Multikanal-Messung gerecht wird und (2) die unbestimmte Permutation unter den BSS-Ausgangssignalen gelöst wird, d.h. das Nutzsignal praktisch automatisiert identifiziert werden kann. Die vorliegende Arbeit entwirft ein Framework, mit dessen Hilfe die Effizienz von BSS-Algorithmen im Kontext des kamera-basierten Photoplethysmogramms bewertet werden kann. Empfehlungen zur Auswahl bestimmter Algorithmen im Zusammenhang mit spezifischen Signal-Charakteristiken werden abgeleitet. Außerdem werden im Rahmen der Arbeit Konzepte für die automatisierte Kanalauswahl nach BSS im Bereich der kontaktlosen Messung des Elektrokardiogramms entwickelt und bewertet. Neuartige Algorithmen basierend auf Sparse Coding erwiesen sich dabei als besonders effizient im Vergleich zu Standard-Methoden.(Spatio-temporal) Blind Source Separation (BSS) provides a large potential to process distorted multichannel biosignal measurements in the context of novel contact-less recording techniques for separating distortions from the cardiac signal of interest. This potential can only be practically utilized (1) if a BSS model is applied that matches the complexity of the measurement, i.e. the signal mixture and (2) if permutation indeterminacy is solved among the BSS output components, i.e the component of interest can be practically selected. The present work, first, designs a framework to assess the efficacy of BSS algorithms in the context of the camera-based photoplethysmogram (cbPPG) and characterizes multiple BSS algorithms, accordingly. Algorithm selection recommendations for certain mixture characteristics are derived. Second, the present work develops and evaluates concepts to solve permutation indeterminacy for BSS outputs of contact-less electrocardiogram (ECG) recordings. The novel approach based on sparse coding is shown to outperform the existing concepts of higher order moments and frequency-domain features