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

Multiclass Classifier based Cardiovascular Condition Detection Using Smartphone Mechanocardiography

Cardiac translational and rotational vibrations induced by left ventricular motions are measurable using joint seismocardiography (SCG) and gyrocardiography (GCG) techniques. Multi-dimensional non-invasive monitoring of the heart reveals relative information of cardiac wall motion. A single inertial measurement unit (IMU) allows capturing cardiac vibrations in sufficient details and enables us to perform patient screening for various heart conditions. We envision smartphone mechanocardiography (MCG) for the use of e-health or telemonitoring, which uses a multi-class classifier to detect various types of cardiovascular diseases (CVD) using only smartphone’s built-in internal sensors data. Such smartphone App/solution could be used by either a healthcare professional and/or the patient him/herself to take recordings from their heart. We suggest that smartphone could be used to separate heart conditions such as normal sinus rhythm (SR), atrial fibrillation (AFib), coronary artery disease (CAD), and possibly ST-segment elevated myocardial infarction (STEMI) in multiclass settings. An application could run the disease screening and immediately inform the user about the results. Widespread availability of IMUs within smartphones could enable the screening of patients globally in the future, however, we also discuss the possible challenges raised by the utilization of such self-monitoring systems.</p

Towards a tricorder: clinical, health economic, and ethical investigation of point-of-care artificial intelligence electrocardiogram for heart failure

Heart failure (HF) is an international public health priority and a focus of the NHS Long Term Plan. There is a particular need in primary care for screening and early detection of heart failure with reduced ejection fraction (HFrEF) – the most common and serious HF subtype, and the only one with an abundant evidence base for effective therapies. Digital health technologies (DHTs) integrating artificial intelligence (AI) could improve diagnosis of HFrEF. Specifically, through a convergence of DHTs and AI, a single-lead electrocardiogram (ECG) can be recorded by a smart stethoscope and interrogated by AI (AI-ECG) to potentially serve as a point-of-care HFrEF test. However, there are concerning evidence gaps for such DHTs applying AI; across intersecting clinical, health economic, and ethical considerations. My thesis therefore investigates hypotheses that AI-ECG is 1.) Reliable, accurate, unbiased, and can be patient self-administered, 2.) Of justifiable health economic impact for primary care deployment, and 3.) Appropriate across ethical domains for deployment as a tool for patient self-administered screening. The theoretical basis for this work is presented in the Introduction (Chapter 1). Chapter 2 describes the first large-scale, multi-centre independent external validation study of AI-ECG, prospectively recruiting 1,050 patients and highlighting impressive performance: area under the curve, sensitivity, and specificity up to 0·91 (95% confidence interval: 0·88–0·95), 91·9% (78·1–98·3), and 80·2% (75·5–84·3) respectively; and absence of bias by age, sex, and ethnicity. Performance was independent of operator, and usability of the tool extended to patients being able to self-examine. Chapter 3 presents a clinical and health economic outcomes analysis using a contemporary digital repository of 2.5 million NHS patient records. A propensity-matched cohort was derived using all patients diagnosed with HF from 2015-2020 (n = 34,208). Novel findings included the unacceptable reality that 70% of index HF diagnoses are made through hospitalisation; where index diagnosis through primary care conferred a medium-term survival advantage and long-term cost saving (£2,500 per patient). This underpins a health economic model for the deployment of AI-ECG across primary care. Chapter 4 approaches a normative ethical analysis focusing on equity, agency, data rights, and responsibility for safe, effective, and trustworthy implementation of an unprecedented at-home patient self-administered AI-ECG screening programme. I propose approaches to mitigating any potential harms, towards preserving and promoting trust, patient engagement, and public health. Collectively, this thesis marks novel work highlighting AI-ECG as tool with the potential to address major cardiovascular public health priorities. Scrutiny through complimentary clinical, health economic, and ethical considerations can directly serve patients and health systems by blueprinting best-practice for the evaluation and implementation of DHTs integrating AI – building the conviction needed to realise the full potential of such technologies.Open Acces

Point-of-Care Technologies for Precision Cardiovascular Care and Clinical Research

Point-of-care technologies (POC or POCT) are enabling innovative cardiovascular diagnostics that promise to improve patient care across diverse clinical settings. The National Heart, Lung, and Blood Institute convened a working group to discuss POCT in cardiovascular medicine. The multidisciplinary working group, which included clinicians, scientists, engineers, device manufacturers, regulatory officials, and program staff, reviewed the state of the POCT field; discussed opportunities for POCT to improve cardiovascular care, realize the promise of precision medicine, and advance the clinical research enterprise; and identified barriers facing translation and integration of POCT with existing clinical systems. A POCT development roadmap emerged to guide multidisciplinary teams of biomarker scientists, technologists, health care providers, and clinical trialists as they: 1) formulate needs assessments; 2) define device design specifications; 3) develop component technologies and integrated systems; 4) perform iterative pilot testing; and 5) conduct rigorous prospective clinical testing to ensure that POCT solutions have substantial effects on cardiovascular care

Smart Wearables for Cardiac Monitoring-Real-World Use beyond Atrial Fibrillation

The possibilities and implementation of wearable cardiac monitoring beyond atrial fibrillation are increasing continuously. This review focuses on the real-world use and evolution of these devices for other arrhythmias, cardiovascular diseases and some of their risk factors beyond atrial fibrillation. The management of nonatrial fibrillation arrhythmias represents a broad field of wearable technologies in cardiology using Holter, event recorder, electrocardiogram (ECG) patches, wristbands and textiles. Implementation in other patient cohorts, such as ST-elevation myocardial infarction (STEMI), heart failure or sleep apnea, is feasible and expanding. In addition to appropriate accuracy, clinical studies must address the validation of clinical pathways including the appropriate device and clinical decisions resulting from the surrogate assessed

Sensitive and quantitative lateral flow tests – with upconverting nanoparticle reporter technology

Rapid diagnostic tests (RDTs) can be used in settings where access to a central laboratory is limited. These settings include point-of-care (POC) diagnostics performed near a patient during a physician’s appointment or in an ambulance. Also, POC testing is used in many resource-limited community healthcare stations, especially in low- and middle-income countries (LMIC). Lateral flow assay (LFA) is one of the dominant formats for RDT. Conventional lateral flow (LF) tests use visually detectable colored reporter technology, which is prone to limited sensitivity and subjective interpretation of the test read-out. Recently, there has been a growing interest towards applying luminescent label technologies in LFA. The use of such technology in combination with miniaturized reader device preserves most of the typical advantages of LF tests. It may also increase sensitivity and analyte quantification and rule out subjective interpretation of the result. The aim of this thesis was to develop LFAs employing upconverting nanoparticles (UCNPs) for improved detection of viral analytes and cardiac troponin I (cTnI). In LMIC there is a need for rapid diagnostics with performance equal to that of central laboratory diagnostics. Infections by viruses such as Hepatitis B and human immunodeficiency virus (HIV) represent major health problems in many areas. LFAs for Hepatis B virus surface antigen and anti-HIV antibodies were developed in this thesis and evaluated with clinical specimens. In addition to infectious diseases, non-communicable diseases pose an emerging threat to human health with number of cases increasing as the standards of living improve globally. Cardiovascular diseases for instance have become a leading cause of premature mortality. Particularly in the case of myocardial infarction, rapid and accurate diagnosis affects the clinical outcome of the patient. Quantitative determination of cTnI can provide information on the status of the patient experiencing acute chest pain. In this thesis, an LFA for cTnI was developed evaluated in terms of quantitative determination of cTnI concentration in patient samples. The results obtained show that the use of UCNPs in the LF platform improves sensitivity and enables quantitative analyte detection. UCNP-LF technology has the potential for use in simple and cost-efficient POC tests, and it offers improved performance in contrast to traditional visual LF technology.Herkkien ja kvantitatiivisten lateraalivirtaustestien kehitys käänteisviritteisten nanopartikkelileimojen avulla Diagnostisia pikatestejä käytetään sellaisissa olosuhteissa, joissa mahdollisuudet keskuslaboratoriodiagnostiikan hyödyntämiseen ovat rajatut – kuten esimerkiksi tyypillisessä vieritestaustilanteessa, jossa diagnostisen testin tulokset tulisi saada nopeasti lääkärikäynnin aikana oikean hoitopäätöksen mahdollistamiseksi. Tämän lisäksi pikatestejä käytetään matalan tulotason maissa olosuhteissa, joissa resurssit laboratoriodiagnostiikan käyttöön ovat rajalliset. Lateraalivirtaustesti on yksi tyypillisimmistä pikatestialustoista. Useimmat lateraalivirtaustestit perustuvat visuaaliseen tulosten lukuun testilastulta. Visuaalisten määritysten heikkoutena on rajallinen herkkyys sekä tulosten subjektiivinen tulkinta. Kiinnostus korvata visuaalisesti havaittavat värilliset nanopartikkelileimat erilaisilla luminoivilla leimoilla on kasvanut viime vuosina. Luminoivilla leimoilla ja helppokäyttöisellä lukijalaitteella voidaan parantaa sekä määrityksen herkkyyttä, että kvantitatiivisuutta, mutta myös vähentää tulosten tulkinnan subjektiivisuutta. Väitöstyössä kehitettiin lateraalivirtausmäärityksiä virusanalyyttien havaitsemiseen ja parannettiin määritysten herkkyyttä ja kvantitatiivisuutta käyttämällä käänteisviritteisiä nanopartikkelileimoja. Monilla resurssiköyhillä alueilla on tarve pikadiagnostiikalle, joka kuitenkin suorituskyvyltään vastaisi keskuslaboratoriodiagnostiikkaa. Hepatiitti B ja HI-virus ovat edelleen suurimpia taudinaiheuttajia näillä alueilla. Väitöskirjatyössä kehitettiin määritykset Hepatiitti B viruksen pintaantigeenin ja HI-virusvasta-aineiden havaitsemiseen. Kehitettyjen määritysten suorituskykyä arvioitiin potilasnäytteillä. Myös tarttumattomat taudit, kuten sydänsairaudet, ovat maailmanlaajuisesti kasvussa elintason noustessa ja ovat suurin syy eliniänodotteen alenemaan. Sydänkohtauksen sattuessa, nopea ja oikea diagnoosi vaikuttaa oleellisesti potilaan hoitoennusteeseen. Väitöskirjatyössä arvioitiin kehitetyn sydänperäistä troponiini I:tä havaitsevan lateraalivirtausmäärityksen suorituskykyä mitata kvantitatiivisesti sydänperäistä troponiini I:tä potilasnäytteissä. Tutkimuksen tulokset osoittavat, että hyödyntämällä käänteisviritteisiä nanopartikkelileimoja voidaan kehittää herkempiä ja kvantitatiivisia lateraalivirtaustestejä. Teknologia mahdollistaisi helppojen ja kustannustehokkaiden testien valmistamisen samalla parantaen testien suorituskykyä suhteessa perinteiseen visuaaliseen lateraalivirtaustekniikkaan

Diagnostic Challenges in Sports Cardiology

The foundations of sports cardiology include promoting physical activity and providing a safe environment for training and competition for all athletes at all levels, from professional to recreational. To combine these two aims, reliable tools to perform preparticipation screenings are needed. Moreover, those at high risk of potentially life-threatening events should be advised to limit their training load, while others should be reassured that there is no exercise-related cardiovascular risk. We are currently witnessing the advent of new portable devices for remote and mobile heart monitoring and several new and promising biochemical markers, which can support athletes’ diagnostic processes. In this Special Issue of the Diagnostics journal entitled “Diagnostic Challenges in Sports Cardiology”, we present a series of 13 manuscripts, including eight original works, three reviews, and two case reports, which give a glimpse into the current research topics in the area of sports cardiology