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Cardiovasc. Med."],"abstract":"<jats:p>Heart failure (HF) remains a leading global cause of chronic disease-related disability and mortality, with rising incidence driven largely by population aging. Early diagnosis is challenging because initial symptoms are often subtle and non-specific, leading to delayed detection and poor prognosis. While conventional tools such as echocardiography and B-type natriuretic peptide (BNP) testing remain diagnostic gold standards, these approaches are limited by operator dependency, restricted accessibility, and dynamic monitoring. Recent advances in artificial intelligence (AI) and cloud computing have enabled a new generation of non-invasive, intelligent technologies that integrate wearable sensors (e.g., ReDS\u2122) with multimodal platforms (e.g., HeartLogic\u2122, CardioSignal) to support real-time risk tracking and personalized management. Indeed, supported by favorable policy environments and strengthened collaboration among manufacturers, clinicians, and researchers across multiple fields and disciplines, the development of intelligent non-invasive HF detection devices has accelerated, leading to rapid innovation, commercialization, and continuous emergence of novel technologies and products. This review systematically summarizes HF pathophysiological mechanisms and current clinical monitoring strategies. Moreover, this review critically evaluates emerging devices and AI-driven platforms, highlighting the associated underlying principles, data integration capabilities, and clinical applicability. Finally, the analysis addresses key challenges, including the \u201cblack box\u201d dilemma associated with AI, data bias, and privacy concerns, and proposes future directions for early screening, risk stratification, and precision intervention. By synthesizing technological comparisons and limitations, this review aims to provide a comprehensive reference for advancing intelligent HF diagnostics.<\/jats:p>","DOI":"10.31083\/rcm48196","type":"journal-article","created":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T11:06:15Z","timestamp":1783422375000},"source":"Crossref","is-referenced-by-count":0,"title":["Innovative Advances in Non-Invasive Detection Technologies for Heart Failure: Synergistic Application of Multimodal Sensing and Intelligent Algorithms"],"prefix":"10.31083","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-0665-3766","authenticated-orcid":true,"given":"Yixin","family":"Chen","sequence":"first","affiliation":[{"name":"Queen Mary College, Jiangxi Medical College, Nanchang University, 330006 Nanchang, Jiangxi, China"},{"name":"Department of Cardiothoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, 330006 Nanchang, Jiangxi, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7424-9242","authenticated-orcid":true,"given":"Qiyao","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Surgery, The First Affiliated Hospital of Zhejiang University, School of Medicine, 310003 Hangzhou, Zhejiang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8891-2463","authenticated-orcid":true,"given":"Hongfei","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Surgery, The First Affiliated Hospital of Zhejiang University, School of Medicine, 310003 Hangzhou, Zhejiang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-0272-0236","authenticated-orcid":true,"given":"Lingxian","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Cardiothoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, 330006 Nanchang, Jiangxi, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8395-7216","authenticated-orcid":true,"given":"Weidong","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Surgery, The First Affiliated Hospital of Zhejiang University, School of Medicine, 310003 Hangzhou, Zhejiang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6703-9087","authenticated-orcid":true,"given":"Yongbing","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Cardiothoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, 330006 Nanchang, Jiangxi, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"16242","published-online":{"date-parts":[[2026,6,24]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","unstructured":"GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. 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Digital Health. 2021; 2: 643\u2013648.","DOI":"10.1093\/ehjdh\/ztab083"},{"key":"ref83","doi-asserted-by":"publisher","unstructured":"Scholten J, Jansen WPJ, Horsthuis T, Mahes AD, Winter MM, Zwinderman AH, et al. Six-lead device superior to single-lead smartwatch ECG in atrial fibrillation detection. American Heart Journal. 2022; 253: 53\u201358.","DOI":"10.1016\/j.ahj.2022.06.010"},{"key":"ref84","doi-asserted-by":"publisher","unstructured":"Bachtiger P, Petri CF, Scott FE, Park SR, Kelshiker MA, Sahemey HK, et al. Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study. The Lancet. Digital Health. 2022; 4: e117\u2013e125.","DOI":"10.1016\/S2589-7500(21)00256-9"},{"key":"ref85","doi-asserted-by":"publisher","unstructured":"Kelshiker MA, B\u00e4chtiger P, Petri CF, Nakhare S, Mansell J, Chhatwal K, et al. Triple cardiovascular disease detection with an artificial intelligence-enabled stethoscope (TRICORDER) in the UK: a cluster-randomised controlled implementation trial. Lancet (London, England). 2026; 407: 704\u2013715.","DOI":"10.1016\/S0140-6736(25)02156-7"},{"key":"ref86","doi-asserted-by":"publisher","unstructured":"Schreiber D, Sattar A, Drigalla D, Higgins S. Ambulatory cardiac monitoring for discharged emergency department patients with possible cardiac arrhythmias. The Western Journal of Emergency Medicine. 2014; 15: 194\u2013198.","DOI":"10.5811\/westjem.2013.11.18973"},{"key":"ref87","doi-asserted-by":"publisher","unstructured":"Cui WJ, Ostrander LE, Lee BY. In vivo reflectance of blood and tissue as a function of light wavelength. IEEE Transactions on Bio-medical Engineering. 1990; 37: 632\u2013639.","DOI":"10.1109\/10.55667"},{"key":"ref88","doi-asserted-by":"publisher","unstructured":"Tamura T, Maeda Y, Sekine M, Yoshida M. Wearable Photoplethysmographic Sensors\u2014Past and Present. Electronics. 2014; 3: 282\u2013302.","DOI":"10.3390\/electronics3020282"},{"key":"ref89","unstructured":"Singh B, Jain A. Global Smartwatch Shipments Tracker by Model, Q1 2025. Counterpoint Research. 2025. Available at: https:\/\/counterpointresearch.com\/en\/reports\/global-smartwatch-shipments-tracker-by-model-q1-2025 (Accessed: 30 December 2025)."},{"key":"ref90","unstructured":"Demand Sage. Smartwatch Statistics (2025) \u2013 Global Users & Market Share [Internet]. 2025. Available at: https:\/\/www.demandsage.com\/smartwatch-statistics\/ (Accessed: 30 December 2025)."},{"key":"ref91","unstructured":"AliveCor, Inc. Personal EKG Devices by AliveCor \u2013 KardiaMobile 6L [Internet]. Mountain View (CA): AliveCor, Inc. 2022. Available at: https:\/\/kardia.com\/kardiamobile-6l (Accessed: 30 December 2025)."},{"key":"ref92","doi-asserted-by":"publisher","unstructured":"Lim J, Lee HS, Han GI, Kang S, Jang JH, Jo YY, et al. Artificial intelligence-enhanced six-lead portable electrocardiogram device for detecting left ventricular systolic dysfunction: a prospective single-centre cohort study. European Heart Journal. Digital Health. 2025; 6: 476\u2013485.","DOI":"10.1093\/ehjdh\/ztaf025"},{"key":"ref93","unstructured":"Wuxi Wenxin Electronic Technology Co., Ltd. About Wenxin Tech. 2015. Available at: https:\/\/wenxintech.com\/intro.html (Accessed: 30 December 2025)."},{"key":"ref94","unstructured":"Eko Health, Inc. CORE 500\u2122 Digital Stethoscope with ECG & AI [Internet]. 2023. Available at: https:\/\/www.ekohealth.eu\/en\/1-eko-core-500-digital-stethoscope.html (Accessed: 30 December 2025)."},{"key":"ref95","doi-asserted-by":"publisher","unstructured":"Hughes A, Shandhi MMH, Master H, Dunn J, Brittain E. Wearable Devices in Cardiovascular Medicine. 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Integration of a Smartphone HF-Dedicated App in the Remote Monitoring of Heart Failure Patients with Cardiac Implantable Electronic Devices: Patient Access, Acceptance, and Adherence to Use. Journal of Clinical Medicine. 2023; 12: 5528.","DOI":"10.3390\/jcm12175528"},{"key":"ref99","doi-asserted-by":"publisher","unstructured":"Zito A, Restivo A, Ciliberti G, Laborante R, Princi G, Romiti GF, et al. Heart failure management guided by remote multiparameter monitoring: A meta-analysis. International Journal of Cardiology. 2023; 388: 131163.","DOI":"10.1016\/j.ijcard.2023.131163"},{"key":"ref100","doi-asserted-by":"publisher","unstructured":"Quer G, Arnaout R, Henne M, Arnaout R. Machine Learning and the Future of Cardiovascular Care: JACC State-of-the-Art Review. 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Development and validation of a prediction model based on machine learning algorithms for predicting the risk of heart failure in middle-aged and older US people with prediabetes or diabetes. Clinical Cardiology. 2023; 46: 1234\u20131243.","DOI":"10.1002\/clc.24104"},{"key":"ref104","doi-asserted-by":"publisher","unstructured":"Stehlik J, Schmalfuss C, Bozkurt B, Nativi-Nicolau J, Wohlfahrt P, Wegerich S, et al. Continuous Wearable Monitoring Analytics Predict Heart Failure Hospitalization: The LINK-HF Multicenter Study. Circulation. Heart Failure. 2020; 13: e006513.","DOI":"10.1161\/CIRCHEARTFAILURE.119.006513"},{"key":"ref105","doi-asserted-by":"publisher","unstructured":"Brouwers RWM, Kraal JJ, Regis M, Spee RF, Kemps HMC. Effectiveness of Cardiac Telerehabilitation With Relapse Prevention: SmartCare-CAD Randomized Controlled Trial. 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Construction of risk prediction model for predicting death or readmission in acute heart failure patients during vulnerable phase based on machine learning. Journal of Army Medical University. 2024; 46: 738\u2013745.","DOI":"10.16016\/j.2097-0927.202312147"},{"key":"ref118","doi-asserted-by":"publisher","unstructured":"McConnell MV, Shcherbina A, Pavlovic A, Homburger JR, Goldfeder RL, Waggot D, et al. Feasibility of Obtaining Measures of Lifestyle From a Smartphone App: The MyHeart Counts Cardiovascular Health Study. JAMA Cardiology. 2017; 2: 67\u201376.","DOI":"10.1001\/jamacardio.2016.4395"},{"key":"ref119","doi-asserted-by":"publisher","unstructured":"Studer R, Sartini C, Suzart-Woischnik K, Agrawal R, Natani H, Gill SK, et al. Identification and Mapping Real-World Data Sources for Heart Failure, Acute Coronary Syndrome, and Atrial Fibrillation. Cardiology. 2022; 147: 98\u2013106.","DOI":"10.1159\/000520674"},{"key":"ref120","doi-asserted-by":"publisher","unstructured":"Petek BJ, Al-Alusi MA, Moulson N, Grant AJ, Besson C, Guseh JS, et al. Consumer Wearable Health and Fitness Technology in Cardiovascular Medicine: JACC State-of-the-Art Review. Journal of the American College of Cardiology. 2023; 82: 245\u2013264.","DOI":"10.1016\/j.jacc.2023.04.054"},{"key":"ref121","doi-asserted-by":"publisher","unstructured":"Jabbour S, Fouhey D, Shepard S, Valley TS, Kazerooni EA, Banovic N, et al. Measuring the Impact of AI in the Diagnosis of Hospitalized Patients: A Randomized Clinical Vignette Survey Study. JAMA. 2023; 330: 2275\u20132284.","DOI":"10.1001\/jama.2023.22295"},{"key":"ref122","doi-asserted-by":"publisher","unstructured":"Xu J, Xiao Y, Wang WH, Ning Y, Shenkman EA, Bian J, et al. Algorithmic fairness in computational medicine. EBioMedicine. 2022; 84: 104250.","DOI":"10.1016\/j.ebiom.2022.104250"},{"key":"ref123","doi-asserted-by":"publisher","unstructured":"Paolillo EW, Lee SY, VandeBunte A, Djukic N, Fonseca C, Kramer JH, et al. Wearable Use in an Observational Study Among Older Adults: Adherence, Feasibility, and Effects of Clinicodemographic Factors. Frontiers in Digital Health. 2022; 4: 884208.","DOI":"10.3389\/fdgth.2022.884208"},{"key":"ref124","unstructured":"European Commission. European Health Data Space Regulation (EHDS). 2025. Available at: https:\/\/health.ec.europa.eu\/ehealth-digital-health-and-care\/european-health-data-space-regulation-ehds_en (Accessed: 25 December 2025)."},{"key":"ref125","unstructured":"Institute of Electrical and Electronics Engineers. IEEE Std 11073-20601-2022. Health informatics - Device interoperability - Part 20601: Optimized exchange protocol. IEEE In IEEE. 2022."},{"key":"ref126","doi-asserted-by":"publisher","unstructured":"Lee S, Do H. Comparison and Analysis of ISO\/IEEE 11073, IHE PCD-01, and HL7 FHIR Messages for Personal Health Devices. Healthcare Informatics Research. 2018; 24: 46\u201352.","DOI":"10.4258\/hir.2018.24.1.46"},{"key":"ref127","doi-asserted-by":"publisher","unstructured":"Edith Chan AW. The shape of artificial intelligence: Just a black box? Chemical Biology & Drug Design. 2020; 96: 882\u2013885.","DOI":"10.1111\/cbdd.13793"},{"key":"ref128","doi-asserted-by":"publisher","unstructured":"Luo Y. Evaluating the state of the art in missing data imputation for clinical data. Briefings in Bioinformatics. 2022; 23: bbab489.","DOI":"10.1093\/bib\/bbab489"},{"key":"ref129","doi-asserted-by":"crossref","unstructured":"Ribeiro MT, Singh S, Guestrin C. \"Why Should I Trust You?\": Explaining the Predictions of Any Classifier. In . Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2016.","DOI":"10.1145\/2939672.2939778"},{"key":"ref130","unstructured":"US Food and Drug Administration. Good Machine Learning Practice for Medical Device Development: Guiding Principles. 2021. Available at: https:\/\/www.fda.gov\/medical-devices\/software-medical-device-samd\/good-machine-learning-practice-medical-device-development-guiding-principles (Accessed: 25 December 2025)."},{"key":"ref131","doi-asserted-by":"publisher","unstructured":"Kaplow K, Downey M, Stewart D, Massie AB, Motter JD, Taylor L, et al. Data professionals' attitudes on data privacy, sharing, and consent in healthcare and research. Digital Health. 2024; 10: 20552076241290964.","DOI":"10.1177\/20552076241290964"},{"key":"ref132","doi-asserted-by":"publisher","unstructured":"Sheahen B, O'Hagan ET, Cho K, Shaw T, Lee A, Lal S, et al. Barriers and Enablers to Routine Clinical Implementation of Cardiac Implantable Electronic Device Remote Monitoring in Australia Among Cardiologists, Cardiac Physiologists, Nurses, and Patients: Interview Study. JMIR Cardio. 2025; 9: e67758.","DOI":"10.2196\/67758"},{"key":"ref133","doi-asserted-by":"publisher","unstructured":"Farkowski MM, Scherr D, Boriani G, Kazakiewicz D, Haim M, Huculeci R, et al. Arrhythmia care in ESC member countries: the 2025 ESC-EHRA atlas on heart rhythm disorders. Europace. 2025; 27: euaf124.","DOI":"10.1093\/europace\/euaf124"},{"key":"ref134","doi-asserted-by":"publisher","unstructured":"Boriani G, Brachmann J, Lewalter T, Wright DJ, Badertscher P, Gale CP, et al. Access and reimbursement of ambulatory cardiac monitoring across Europe. European Heart Journal. 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