1
|
Lu ZX, Qian P, Bi D, Ye ZW, He X, Zhao YH, Su L, Li SL, Zhu ZL. Application of AI and IoT in Clinical Medicine: Summary and Challenges. Curr Med Sci 2021; 41:1134-50. [PMID: 34939144 DOI: 10.1007/s11596-021-2486-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 11/26/2021] [Indexed: 12/19/2022]
Abstract
The application of artificial intelligence (AI) technology in the medical field has experienced a long history of development. In turn, some long-standing points and challenges in the medical field have also prompted diverse research teams to continue to explore AI in depth. With the development of advanced technologies such as the Internet of Things (IoT), cloud computing, big data, and 5G mobile networks, AI technology has been more widely adopted in the medical field. In addition, the in-depth integration of AI and IoT technology enables the gradual improvement of medical diagnosis and treatment capabilities so as to provide services to the public in a more effective way. In this work, we examine the technical basis of IoT, cloud computing, big data analysis and machine learning involved in clinical medicine, combined with concepts of specific algorithms such as activity recognition, behavior recognition, anomaly detection, assistant decision-making system, to describe the scenario-based applications of remote diagnosis and treatment collaboration, neonatal intensive care unit, cardiology intensive care unit, emergency first aid, venous thromboembolism, monitoring nursing, image-assisted diagnosis, etc. We also systematically summarize the application of AI and IoT in clinical medicine, analyze the main challenges thereof, and comment on the trends and future developments in this field.
Collapse
|
2
|
Skobel E, Knackstedt C, Martinez-Romero A, Salvi D, Vera-Munoz C, Napp A, Luprano J, Bover R, Glöggler S, Bjarnason-Wehrens B, Marx N, Rigby A, Cleland J. Internet-based training of coronary artery patients: the Heart Cycle Trial. Heart Vessels 2016; 32:408-418. [PMID: 27730298 DOI: 10.1007/s00380-016-0897-8] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2016] [Accepted: 09/30/2016] [Indexed: 12/30/2022]
Abstract
Low adherence to cardiac rehabilitation (CR) might be improved by remote monitoring systems that can be used to motivate and supervise patients and tailor CR safely and effectively to their needs. The main objective of this study was to evaluate the feasibility of a smartphone-guided training system (GEX) and whether it could improve exercise capacity compared to CR delivered by conventional methods for patients with coronary artery disease (CAD). A prospective, randomized, international, multi-center study comparing CR delivered by conventional means (CG) or by remote monitoring (IG) using a new training steering/feedback tool (GEx System). This consisted of a sensor monitoring breathing rate and the electrocardiogram that transmitted information on training intensity, arrhythmias and adherence to training prescriptions, wirelessly via the internet, to a medical team that provided feedback and adjusted training prescriptions. Exercise capacity was evaluated prior to and 6 months after intervention. 118 patients (58 ± 10 years, 105 men) with CAD referred for CR were randomized (IG: n = 55, CG: n = 63). However, 15 patients (27 %) in the IG and 18 (29 %) in the CG withdrew participation and technical problems prevented a further 21 patients (38 %) in the IG from participating. No training-related complications occurred. For those who completed the study, peak VO2 improved more (p = 0.005) in the IG (1.76 ± 4.1 ml/min/kg) compared to CG (-0.4 ± 2.7 ml/min/kg). A newly designed system for home-based CR appears feasible, safe and improves exercise capacity compared to national CR. Technical problems reflected the complexity of applying remote monitoring solutions at an international level.
Collapse
Affiliation(s)
- Erik Skobel
- Clinic for Cardiac and Pulmonary Rehabilitation, Rosenquelle, Kurbrunnenstraße 5, 52077, Aachen, Germany. .,Department of Cardiology, Angiology, Pneumology and Intensive Care, Medicine, University Hospital, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany.
| | - Christian Knackstedt
- Department of Cardiology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | | | - Dario Salvi
- Life Supporting Technologies, Departamento de Tecnología Fotónica y Bioingeniería, Universidad Politécnica de Madrid, Madrid, Spain
| | - Cecilia Vera-Munoz
- Life Supporting Technologies, Departamento de Tecnología Fotónica y Bioingeniería, Universidad Politécnica de Madrid, Madrid, Spain
| | - Andreas Napp
- Department of Cardiology, Angiology, Pneumology and Intensive Care, Medicine, University Hospital, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany
| | - Jean Luprano
- Centre Suisse d'Electronique et de Microtechnique SA, 2002, Neuchâtel, Switzerland
| | - Ramon Bover
- Servicio de Cardiología, Hospital Clínico Universitario San Carlos de Madrid, Madrid, Spain
| | - Sigrid Glöggler
- Department of Cardiology, Angiology, Pneumology and Intensive Care, Medicine, University Hospital, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany.,Clinical Trial Center Aachen, Aachen, Germany
| | - Birna Bjarnason-Wehrens
- Institute for Cardiology and Sports Medicine, German Sports University Cologne, Cologne, Germany
| | - Nikolaus Marx
- Department of Cardiology, Angiology, Pneumology and Intensive Care, Medicine, University Hospital, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany
| | - Alan Rigby
- Hull-York Medical School, University of Hull, Hull, UK.,Department of Cardiology, Spire Hull and East Riding Hospital, Hull, UK
| | - John Cleland
- Hull-York Medical School, University of Hull, Hull, UK.,Department of Cardiology, Spire Hull and East Riding Hospital, Hull, UK
| |
Collapse
|
3
|
Vera-Muñoz C, Arredondo MT, Ottaviano M, Salvi D, Stut W. HeartCycle: user interaction and patient education. Annu Int Conf IEEE Eng Med Biol Soc 2013; 2013:6988-6991. [PMID: 24111353 DOI: 10.1109/embc.2013.6611166] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Cardiovascular Diseases are the most prevalent and serious chronic conditions existing nowadays. They are the primary cause of death in the world and generate enormous expenditures to the health systems. Tele-monitoring and personal health systems have proven to be good options for tackling this situation; however they are still lacking many functionalities. It is necessary to find solutions that allow health professionals to follow up patients more closely and efficiently, while reducing the non-adherence of patients to the treatment regime. HeartCycle research project (partially funded by the European Commission) has developed a personal health system for cardiovascular diseases management with the aim to address this problem. This paper describes the Patient Loop of this solution, including the different components, the adopted user interaction, and the implemented patients' education and coaching strategy.
Collapse
|