1
|
Sachdeva S, Bhatia S, Al Harrasi A, Shah YA, Anwer K, Philip AK, Shah SFA, Khan A, Ahsan Halim S. Unraveling the role of cloud computing in health care system and biomedical sciences. Heliyon 2024; 10:e29044. [PMID: 38601602 PMCID: PMC11004887 DOI: 10.1016/j.heliyon.2024.e29044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 03/24/2024] [Accepted: 03/28/2024] [Indexed: 04/12/2024] Open
Abstract
Cloud computing has emerged as a transformative force in healthcare and biomedical sciences, offering scalable, on-demand resources for managing vast amounts of data. This review explores the integration of cloud computing within these fields, highlighting its pivotal role in enhancing data management, security, and accessibility. We examine the application of cloud computing in various healthcare domains, including electronic medical records, telemedicine, and personalized patient care, as well as its impact on bioinformatics research, particularly in genomics, proteomics, and metabolomics. The review also addresses the challenges and ethical considerations associated with cloud-based healthcare solutions, such as data privacy and cybersecurity. By providing a comprehensive overview, we aim to assist readers in understanding the significance of cloud computing in modern medical applications and its potential to revolutionize both patient care and biomedical research.
Collapse
Affiliation(s)
| | - Saurabh Bhatia
- Natural & Medical Sciences Research Center, University of Nizwa, P.O. Box 33, 616 Birkat Al Mauz, Nizwa, Oman
- School of Health Science, University of Petroleum and Energy Studies, Prem Nagar, Dehradun, Uttarakhand, 248007, India
| | - Ahmed Al Harrasi
- Natural & Medical Sciences Research Center, University of Nizwa, P.O. Box 33, 616 Birkat Al Mauz, Nizwa, Oman
| | - Yasir Abbas Shah
- Natural & Medical Sciences Research Center, University of Nizwa, P.O. Box 33, 616 Birkat Al Mauz, Nizwa, Oman
| | - Khalid Anwer
- Department of Pharmaceutics, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia
| | - Anil K. Philip
- School of Pharmacy, University of Nizwa, Birkat Al Mouz, Nizwa, 616, Oman
| | - Syed Faisal Abbas Shah
- Faculty of Computer Science & Information Technology, Virtual University of Pakistan, Lahore, 54000, Pakistan
| | - Ajmal Khan
- Natural & Medical Sciences Research Center, University of Nizwa, P.O. Box 33, 616 Birkat Al Mauz, Nizwa, Oman
| | - Sobia Ahsan Halim
- Natural & Medical Sciences Research Center, University of Nizwa, P.O. Box 33, 616 Birkat Al Mauz, Nizwa, Oman
| |
Collapse
|
2
|
Alattas K, Wu Q. A framework to evaluate the barriers for adopting the internet of medical things using the extended generalized TODIM method under the hesitant fuzzy environment. APPL INTELL 2022. [DOI: 10.1007/s10489-021-03078-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
|
3
|
Palumbo A, Ielpo N, Calabrese B, Corchiola D, Garropoli R, Gramigna V, Perri G. SIMpLE: A Mobile Cloud-Based System for Health Monitoring of People with ALS. SENSORS 2021; 21:s21217239. [PMID: 34770548 PMCID: PMC8587347 DOI: 10.3390/s21217239] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 10/18/2021] [Accepted: 10/26/2021] [Indexed: 01/05/2023]
Abstract
Adopting telemonitoring services during the pandemic for people affected by chronic disease is fundamental to ensure access to health care services avoiding the risk of COVID-19 infection. Among chronic diseases, Amyotrophic Lateral Sclerosis (ALS), also known as Lou Gehrig’s disease, is a progressive neurodegenerative disease of adulthood, caused by the loss of spinal, bulbar and cortical motor neurons, which leads to paralysis of the voluntary muscles and, also, involves respiratory ones. Therefore, remote monitoring and teleconsulting are essential services for ALS patients with limited mobility, as the disease progresses, and for those living far from ALS centres and hospitals. In addition, the COVID 19 pandemic has increased the need to remotely provide the best care to patients, avoiding infection during ALS centre visits. The paper illustrates an innovative, secure medical monitoring and teleconsultation mobile cloud-based system for disabled people, such as those with ALS (Amyotrophic Lateral Sclerosis). The design aims to remotely monitor biosignals, such as ECG (electrocardiographic) and EMG (electromyographic) signals of ALS patients in order to prevent complications related to the pathology.
Collapse
Affiliation(s)
- Arrigo Palumbo
- Department of Medical and Surgical Sciences, Magna Graecia University of Catanzaro, 88100 Catanzaro, Italy; (A.P.); (N.I.)
| | - Nicola Ielpo
- Department of Medical and Surgical Sciences, Magna Graecia University of Catanzaro, 88100 Catanzaro, Italy; (A.P.); (N.I.)
| | - Barbara Calabrese
- Department of Medical and Surgical Sciences, Magna Graecia University of Catanzaro, 88100 Catanzaro, Italy; (A.P.); (N.I.)
- Correspondence:
| | | | - Remo Garropoli
- Garropoli Computer Science Consulting, 87100 Cosenza, Italy;
| | - Vera Gramigna
- Neuroscience Research Center, Magna Graecia University, 88100 Catanzaro, Italy;
| | - Giovanni Perri
- Radiological Center Perri-Bilotti, 87100 Cosenza, Italy;
| |
Collapse
|
4
|
Bai B, Zhao Y, Chen X, Chen Y, Luo Z. A smart portable ECG monitoring system with high precision and low power consumption. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021. [DOI: 10.3233/jifs-189715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
In this paper, a smart low-power wearable ECG monitoring and analyzing system which has an advanced architecture and low power consumption has been developed. There is a single channel ECG monitor that removes all loose wires from the system and minimizes the footprint on the user, ECG data can be continuously monitored for up to 14 days without affecting daily life. In addition, Bluetooth low energy (BLE), smartphone APP, analysis software and management platform have been added to the system for remote monitoring and whole process of heart health management. Clinical test to compare our wearable monitor with the Holter recorder are conducted on 108 groups under different ambulatory conditions. The results confirmed that it is equivalent to Holter in the clinical diagnosis of arrhythmia. This system can free patients from the short-range monitoring with lead wire entanglement to realize the long-term detection in daily life, early detection and early intervention; more convenient connections between patients and doctors, efficient use of medical resources, remote monitoring to reduce the burden of the medical and health system.
Collapse
Affiliation(s)
- Baodan Bai
- School of Medical Instruments, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Yufang Zhao
- Shaoxing Institute of Shanghai University, Shaoxing, China
| | - Xinrong Chen
- Academy for Engineering and Technology, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Shanghai, China
| | - Yingmin Chen
- Renji Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Zhangyuan Luo
- Shaoxing Institute of Shanghai University, Shaoxing, China
| |
Collapse
|
5
|
El-Rashidy N, El-Sappagh S, Islam SMR, M. El-Bakry H, Abdelrazek S. Mobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges. Diagnostics (Basel) 2021; 11:diagnostics11040607. [PMID: 33805471 PMCID: PMC8067150 DOI: 10.3390/diagnostics11040607] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 02/17/2021] [Accepted: 03/05/2021] [Indexed: 02/07/2023] Open
Abstract
Chronic diseases are becoming more widespread. Treatment and monitoring of these diseases require going to hospitals frequently, which increases the burdens of hospitals and patients. Presently, advancements in wearable sensors and communication protocol contribute to enriching the healthcare system in a way that will reshape healthcare services shortly. Remote patient monitoring (RPM) is the foremost of these advancements. RPM systems are based on the collection of patient vital signs extracted using invasive and noninvasive techniques, then sending them in real-time to physicians. These data may help physicians in taking the right decision at the right time. The main objective of this paper is to outline research directions on remote patient monitoring, explain the role of AI in building RPM systems, make an overview of the state of the art of RPM, its advantages, its challenges, and its probable future directions. For studying the literature, five databases have been chosen (i.e., science direct, IEEE-Explore, Springer, PubMed, and science.gov). We followed the (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) PRISMA, which is a standard methodology for systematic reviews and meta-analyses. A total of 56 articles are reviewed based on the combination of a set of selected search terms including RPM, data mining, clinical decision support system, electronic health record, cloud computing, internet of things, and wireless body area network. The result of this study approved the effectiveness of RPM in improving healthcare delivery, increase diagnosis speed, and reduce costs. To this end, we also present the chronic disease monitoring system as a case study to provide enhanced solutions for RPMs.
Collapse
Affiliation(s)
- Nora El-Rashidy
- Machine Learning and Information Retrieval Department, Faculty of Artificial Intelligence, Kafrelsheiksh University, Kafrelsheiksh 13518, Egypt;
| | - Shaker El-Sappagh
- Centro Singular de Investigación en Tecnoloxías Intelixentes (CiTIUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
- Information Systems Department, Faculty of Computers and Artificial Intelligence, Benha University, Banha 13518, Egypt
- Correspondence: (S.E.-S.); (S.M.R.I.)
| | - S. M. Riazul Islam
- Department of Computer Science and Engineering, Sejong University, Seoul 05006, Korea
- Correspondence: (S.E.-S.); (S.M.R.I.)
| | - Hazem M. El-Bakry
- Information Systems Department, Faculty of Computers and Information, Mansoura University, Mansoura 13518, Egypt; (H.M.E.-B.); (S.A.)
| | - Samir Abdelrazek
- Information Systems Department, Faculty of Computers and Information, Mansoura University, Mansoura 13518, Egypt; (H.M.E.-B.); (S.A.)
| |
Collapse
|
6
|
End-To-End Deep Learning Framework for Coronavirus (COVID-19) Detection and Monitoring. ELECTRONICS 2020. [DOI: 10.3390/electronics9091439] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Coronavirus (COVID-19) is a new virus of viral pneumonia. It can outbreak in the world through person-to-person transmission. Although several medical companies provide cooperative monitoring healthcare systems, these solutions lack offering of the end-to-end management of the disease. The main objective of the proposed framework is to bridge the current gap between current technologies and healthcare systems. The wireless body area network, cloud computing, fog computing, and clinical decision support system are integrated to provide a comprehensive and complete model for disease detection and monitoring. By monitoring a person with COVID-19 in real time, physicians can guide patients with the right decisions. The proposed framework has three main layers (i.e., a patient layer, cloud layer, and hospital layer). In the patient layer, the patient is tracked through a set of wearable sensors and a mobile app. In the cloud layer, a fog network architecture is proposed to solve the issues of storage and data transmission. In the hospital layer, we propose a convolutional neural network-based deep learning model for COVID-19 detection based on patient’s X-ray scan images and transfer learning. The proposed model achieved promising results compared to the state-of-the art (i.e., accuracy of 97.95% and specificity of 98.85%). Our framework is a useful application, through which we expect significant effects on COVID-19 proliferation and considerable lowering in healthcare expenses.
Collapse
|
7
|
Gu D, Yang X, Deng S, Liang C, Wang X, Wu J, Guo J. Tracking Knowledge Evolution in Cloud Health Care Research: Knowledge Map and Common Word Analysis. J Med Internet Res 2020; 22:e15142. [PMID: 32130115 PMCID: PMC7064966 DOI: 10.2196/15142] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 10/28/2019] [Accepted: 12/15/2019] [Indexed: 11/26/2022] Open
Abstract
Background With the continuous development of the internet and the explosive growth in data, big data technology has emerged. With its ongoing development and application, cloud computing technology provides better data storage and analysis. The development of cloud health care provides a more convenient and effective solution for health. Studying the evolution of knowledge and research hotspots in the field of cloud health care is increasingly important for medical informatics. Scholars in the medical informatics community need to understand the extent of the evolution of and possible trends in cloud health care research to inform their future research. Objective Drawing on the cloud health care literature, this study aimed to describe the development and evolution of research themes in cloud health care through a knowledge map and common word analysis. Methods A total of 2878 articles about cloud health care was retrieved from the Web of Science database. We used cybermetrics to analyze and visualize the keywords in these articles. We created a knowledge map to show the evolution of cloud health care research. We used co-word analysis to identify the hotspots and their evolution in cloud health care research. Results The evolution and development of cloud health care services are described. In 2007-2009 (Phase I), most scholars used cloud computing in the medical field mainly to reduce costs, and grid computing and cloud computing were the primary technologies. In 2010-2012 (Phase II), the security of cloud systems became of interest to scholars. In 2013-2015 (Phase III), medical informatization enabled big data for health services. In 2016-2017 (Phase IV), machine learning and mobile technologies were introduced to the medical field. Conclusions Cloud health care research has been rapidly developing worldwide, and technologies used in cloud health research are simultaneously diverging and becoming smarter. Cloud–based mobile health, cloud–based smart health, and the security of cloud health data and systems are three possible trends in the future development of the cloud health care field.
Collapse
Affiliation(s)
- Dongxiao Gu
- The School of Management, Hefei University of Technology, Hefei, China
| | - Xuejie Yang
- The School of Management, Hefei University of Technology, Hefei, China
| | - Shuyuan Deng
- The Seidman College of Business, Grand Valley State University, Grand Rapids, MI, United States
| | - Changyong Liang
- The School of Management, Hefei University of Technology, Hefei, China
| | - Xiaoyu Wang
- The 1st Affiliated Hospital, Anhui University of Traditional Chinese Medicine, Hefei, China
| | - Jiao Wu
- College of Business Administration, Central Michigan University, Mount Pleasant, MI, United States
| | - Jingjing Guo
- The School of Management, Hefei University of Technology, Hefei, China
| |
Collapse
|
8
|
Karaca Y, Moonis M, Zhang YD, Gezgez C. Mobile cloud computing based stroke healthcare system. INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT 2019. [DOI: 10.1016/j.ijinfomgt.2018.09.012] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
|
9
|
Saba T, Khan SU, Islam N, Abbas N, Rehman A, Javaid N, Anjum A. Cloud‐based decision support system for the detection and classification of malignant cells in breast cancer using breast cytology images. Microsc Res Tech 2019; 82:775-785. [DOI: 10.1002/jemt.23222] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 11/14/2018] [Accepted: 12/30/2018] [Indexed: 12/16/2022]
Affiliation(s)
- Tanzila Saba
- College of Computer and Information SciencesPrince Sultan University Riyadh Saudi Arabia
| | - Sana Ullah Khan
- Department of Computer ScienceIslamia College University Peshawar KPK Pakistan
| | - Naveed Islam
- Department of Computer ScienceIslamia College University Peshawar KPK Pakistan
| | - Naveed Abbas
- Department of Computer ScienceIslamia College University Peshawar KPK Pakistan
| | - Amjad Rehman
- MIS Department COBAAl Yamamah University Riyadh Saudi Arabia
| | - Nadeem Javaid
- Department of Computer ScienceCOMSATS University Islamabad Pakistan
| | - Adeel Anjum
- Department of Computer ScienceCOMSATS University Islamabad Pakistan
| |
Collapse
|
10
|
An Edge Computing Based Smart Healthcare Framework for Resource Management. SENSORS 2018; 18:s18124307. [PMID: 30563267 PMCID: PMC6308405 DOI: 10.3390/s18124307] [Citation(s) in RCA: 103] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Revised: 11/28/2018] [Accepted: 12/03/2018] [Indexed: 02/06/2023]
Abstract
The revolution in information technologies, and the spread of the Internet of Things (IoT) and smart city industrial systems, have fostered widespread use of smart systems. As a complex, 24/7 service, healthcare requires efficient and reliable follow-up on daily operations, service and resources. Cloud and edge computing are essential for smart and efficient healthcare systems in smart cities. Emergency departments (ED) are real-time systems with complex dynamic behavior, and they require tailored techniques to model, simulate and optimize system resources and service flow. ED issues are mainly due to resource shortage and resource assignment efficiency. In this paper, we propose a resource preservation net (RPN) framework using Petri net, integrated with custom cloud and edge computing suitable for ED systems. The proposed framework is designed to model non-consumable resources and is theoretically described and validated. RPN is applicable to a real-life scenario where key performance indicators such as patient length of stay (LoS), resource utilization rate and average patient waiting time are modeled and optimized. As the system must be reliable, efficient and secure, the use of cloud and edge computing is critical. The proposed framework is simulated, which highlights significant improvements in LoS, resource utilization and patient waiting time.
Collapse
|
11
|
Majumder S, Chen L, Marinov O, Chen CH, Mondal T, Deen MJ. Noncontact Wearable Wireless ECG Systems for Long-Term Monitoring. IEEE Rev Biomed Eng 2018; 11:306-321. [PMID: 29993585 DOI: 10.1109/rbme.2018.2840336] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Electrocardiography (ECG) is the most common and extensively used vital sign monitoring method in modern healthcare systems. Different designs of ambulatory ECG systems were developed as alternatives to the commonly used 12-lead clinical ECG systems. These designs primarily focus on portability and user convenience, while maintaining signal integrity and lowering power consumption. Here, a wireless ECG monitoring system is developed using flexible and dry capacitive electrodes for long-term monitoring of cardiovascular health. Our capacitive-coupled dry electrodes can measure ECG signals over a textile-based interface material between the skin and electrodes. The electrodes are connected to a data acquisition system that receives the raw ECG signals from the electrodes and transmits the data using Bluetooth to a computer. A software application was developed to process, store, and display the ECG signal in real time. ECG measurements were obtained over different types of textile materials and in the presence of body movements. Our experimental results show that the performance of our ECG system is comparable to other reported ECG monitoring systems. In addition, to put this research into perspective, recent ambulatory ECG monitoring systems, ECG systems-on-chip, commercial ECG monitoring systems, and different state-of-the-art ECG systems are reviewed, compared, and critically discussed.
Collapse
|
12
|
Personalized Health Monitoring System for Managing Well-Being in Rural Areas. J Med Syst 2017; 42:22. [DOI: 10.1007/s10916-017-0854-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Accepted: 10/30/2017] [Indexed: 10/18/2022]
|
13
|
Fog computing architectures for healthcare. JOURNAL OF INFORMATION COMMUNICATION & ETHICS IN SOCIETY 2016. [DOI: 10.1108/jices-05-2016-0014] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Purpose
The purpose of this study is to analyze how embedding of self-powered wireless sensors into cloud computing further enables such a system to become a sustainable part of work environment.
Design/methodology/approach
This is exemplified by an application scenario in healthcare that was developed in the context of the OpSIT project in Germany. A clearly outlined three-layer architecture, in the sense of Internet of Things, is presented. It provides the basis for integrating a broad range of sensors into smart healthcare infrastructure. More specifically, by making use of short-range communication sensors (sensing layer), gateways which implement data transmission and low-level computation (fog layer) and cloud computing for processing the data (application layer).
Findings
A technical in-depth analysis of the first two layers of the infrastructure is given to prove reliability and to determine the communication quality and availability in real-world scenarios. Furthermore, two example use-cases that directly apply to a healthcare environment are examined, concluding with the feasibility of the presented approach.
Practical implications
Finally, the next research steps, oriented towards the semantic tagging and classification of data received from sensors, and the usage of advanced artificial intelligence-based algorithms on this information to produce useful knowledge, are described together with the derived social benefits.
Originality/value
The work presents an innovative, extensible and scalable system, proven to be useful in healthcare environments.
Collapse
|
14
|
Dai M, Xiao X, Chen X, Lin H, Wu W, Chen S. A low-power and miniaturized electrocardiograph data collection system with smart textile electrodes for monitoring of cardiac function. AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE 2016; 39:1029-1040. [PMID: 27743384 DOI: 10.1007/s13246-016-0483-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2016] [Accepted: 08/31/2016] [Indexed: 11/29/2022]
Abstract
With the increasing aging population as well as health concerns, chronic heart disease has become the focus of public attention. A comfortable, low-powered, and wearable electrocardiogram (ECG) system for continuously monitoring the elderly's ECG signals over several hours is important for preventing cardiovascular diseases. Traditional ECG monitoring apparatus is often inconvenient to carry, has many electrodes to attach to the chest, and has a high-power consumption. There is also a challenge to design an electrocardiograph that satisfies requirements such as comfort, confinement, and compactness. Based on these considerations, this study presents a biosensor acquisition system for wearable, ubiquitous healthcare applications using three textile electrodes and a recording circuit specialized for ECG monitoring. In addition, several methods were adopted to reduce the power consumption of the device. The proposed system is composed of three parts: (1) an ECG analog front end (AFE), (2) digital signal processing and micro-control circuits, and (3) system software. Digital filter methods were used to eliminate the baseline wander, skin contact noise, and other interfering signals. A comparative study was conducted using this system to observe its performance with two commercial Holter monitors. The experimental results demonstrated that the total power consumption of this proposed system in a full round of ECG acquisition was only 29.74 mW. In addition, this low-power system performed well and stably measured the heart rate with an accuracy of 98.55 %. It can also contain a real-time dynamic display with organic light-emitting diodes (OLED) and wirelessly transmit information via a Bluetooth 4.0 module.
Collapse
Affiliation(s)
- Ming Dai
- Department of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, 518060, China
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, 518060, China
| | - Xueliang Xiao
- Key Laboratory of Eco-Textiles, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Xin Chen
- Department of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, 518060, China
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, 518060, China
- National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Shenzhen, 518060, China
| | - Haoming Lin
- Department of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, 518060, China
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, 518060, China
| | - Wanqing Wu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Shenzhen, 518055, China.
| | - Siping Chen
- Department of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, 518060, China.
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, 518060, China.
- National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Shenzhen, 518060, China.
| |
Collapse
|
15
|
Abstract
Mobile electrocardiographs consist of three components: a mobile device (e.g. a smartphone), an electrocardiographic device or accessory, and a mobile application. Mobile platforms are small computers with sufficient computational power, good quality display, suitable data storage, and several possibilities of data transmission. Electrocardiographic electrodes and sensors for mobile use utilize unconventional materials, e.g. rubber, e-textile, and inkjet-printed nanoparticle electrodes. Mobile devices can be handheld, worn as vests or T-shirts, or attached to patient's skin as biopatches. Mobile electrocardiographic devices and accessories may additionally record other signals including respiratory rate, activity level, and geolocation. Large-scale clinical studies that utilize electrocardiography are easier to conduct using mobile technologies and the collected data are suitable for "big data" processing. This is expected to reveal phenomena so far inaccessible by standard electrocardiographic techniques.
Collapse
Affiliation(s)
| | - Marek Malik
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| |
Collapse
|
16
|
Choi M, Jeong JJ, Kim SH, Kim SW. Reduction of Motion Artifacts and Improvement of R Peak Detecting Accuracy Using Adjacent Non-Intrusive ECG Sensors. SENSORS 2016; 16:s16050715. [PMID: 27196910 PMCID: PMC4883406 DOI: 10.3390/s16050715] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2016] [Revised: 05/05/2016] [Accepted: 05/11/2016] [Indexed: 11/16/2022]
Abstract
Non-intrusive electrocardiogram (ECG) monitoring has many advantages: easy to measure and apply in daily life. However, motion noise in the measured signal is the major problem of non-intrusive measurement. This paper proposes a method to reduce the noise and to detect the R peaks of ECG in a stable manner in a sitting arrangement using non-intrusive sensors. The method utilizes two capacitive ECG sensors (cECGs) to measure ECG, and another two cECGs located adjacent to the sensors for ECG are added to obtain the information on motion. Then, active noise cancellation technique and the motion information are used to reduce motion noise. To verify the proposed method, ECG was measured indoors and during driving, and the accuracy of the detected R peaks was compared. After applying the method, the sum of sensitivity and positive predictivity increased 8.39% on average and 26.26% maximally in the data. Based on the results, it was confirmed that the motion noise was reduced and that more reliable R peak positions could be obtained by the proposed method. The robustness of the new ECG measurement method will elicit benefits to various health care systems that require noninvasive heart rate or heart rate variability measurements.
Collapse
Affiliation(s)
- Minho Choi
- Department of Creative IT Engineering and Future IT Innovation Laboratory, Pohang University of Science and Technology (POSTECH), Pohang, Kyungbuk 790-784, Korea.
| | - Jae Jin Jeong
- Department of Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Kyungbuk 790-784, Korea.
| | - Seung Hun Kim
- Department of Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Kyungbuk 790-784, Korea.
| | - Sang Woo Kim
- Department of Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Kyungbuk 790-784, Korea.
| |
Collapse
|
17
|
Lin BS, Wong AM, Tseng KC. Community-Based ECG Monitoring System for Patients with Cardiovascular Diseases. J Med Syst 2016; 40:80. [PMID: 26802010 DOI: 10.1007/s10916-016-0442-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Accepted: 01/11/2016] [Indexed: 01/08/2023]
Abstract
This study aims to develop a community-based electrocardiogram (ECG) monitoring system for cardiac outpatients to wirelessly detect heart rate, provide personalized healthcare, and enhance interactive social contact because of the prevalence of deaths from cardiovascular disease and the growing problem of aging in the world. The system not only strengthens the performance of the ECG monitoring system but also emphasizes the ergonomic design of wearable devices and user interfaces. In addition, it enables medical professionals to diagnose cardiac symptoms remotely and electronically manage medical reports and suggestions. The experimental result shows high performance of the dry electrode, even in dynamic conditions. The comparison result with different ECG healthcare systems shows the essential factors that the system should possess and the capability of the proposed system. Finally, a user survey was conducted based on the unified theory of acceptance and users of technology (UTAUT) model.
Collapse
Affiliation(s)
- Bor-Shyh Lin
- Institute of Imaging and Biomedical Photonics, National Chiao Tung University, Hsinchu, Taiwan
| | - Alice M Wong
- Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital, Taoyuan, Taiwan.,Department of Industrial Design, Product Design and Development Laboratory, College of Management, Chang Gung University, 259 Wenhua 1st Road, Guishan District, Taoyuan, 33302, Taiwan, Republic of China
| | - Kevin C Tseng
- Department of Industrial Design, Product Design and Development Laboratory, College of Management, Chang Gung University, 259 Wenhua 1st Road, Guishan District, Taoyuan, 33302, Taiwan, Republic of China. .,Healthy Aging Research Centre, Chang Gung University, Taoyuan, Taiwan.
| |
Collapse
|
18
|
Development of Patient Status-Based Dynamic Access System for Medical Information Systems. Symmetry (Basel) 2015. [DOI: 10.3390/sym7021028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
|
19
|
A Wearable Context-Aware ECG Monitoring System Integrated with Built-in Kinematic Sensors of the Smartphone. SENSORS 2015; 15:11465-84. [PMID: 25996508 PMCID: PMC4481936 DOI: 10.3390/s150511465] [Citation(s) in RCA: 100] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2015] [Revised: 04/21/2015] [Accepted: 04/27/2015] [Indexed: 11/17/2022]
Abstract
Continuously monitoring the ECG signals over hours combined with activity status is very important for preventing cardiovascular diseases. A traditional ECG holter is often inconvenient to carry because it has many electrodes attached to the chest and because it is heavy. This work proposes a wearable, low power context-aware ECG monitoring system integrated built-in kinetic sensors of the smartphone with a self-designed ECG sensor. The wearable ECG sensor is comprised of a fully integrated analog front-end (AFE), a commercial micro control unit (MCU), a secure digital (SD) card, and a Bluetooth module. The whole sensor is very small with a size of only 58 × 50 × 10 mm for wearable monitoring application due to the AFE design, and the total power dissipation in a full round of ECG acquisition is only 12.5 mW. With the help of built-in kinetic sensors of the smartphone, the proposed system can compute and recognize user’s physical activity, and thus provide context-aware information for the continuous ECG monitoring. The experimental results demonstrated the performance of proposed system in improving diagnosis accuracy for arrhythmias and identifying the most common abnormal ECG patterns in different activities. In conclusion, we provide a wearable, accurate and energy-efficient system for long-term and context-aware ECG monitoring without any extra cost on kinetic sensor design but with the help of the widespread smartphone.
Collapse
|
20
|
|
21
|
Oh S, Cha J, Ji M, Kang H, Kim S, Heo E, Han JS, Kang H, Chae H, Hwang H, Yoo S. Architecture Design of Healthcare Software-as-a-Service Platform for Cloud-Based Clinical Decision Support Service. Healthc Inform Res 2015; 21:102-10. [PMID: 25995962 PMCID: PMC4434058 DOI: 10.4258/hir.2015.21.2.102] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2015] [Revised: 04/14/2015] [Accepted: 04/25/2015] [Indexed: 11/25/2022] Open
Abstract
Objectives To design a cloud computing-based Healthcare Software-as-a-Service (SaaS) Platform (HSP) for delivering healthcare information services with low cost, high clinical value, and high usability. Methods We analyzed the architecture requirements of an HSP, including the interface, business services, cloud SaaS, quality attributes, privacy and security, and multi-lingual capacity. For cloud-based SaaS services, we focused on Clinical Decision Service (CDS) content services, basic functional services, and mobile services. Microsoft's Azure cloud computing for Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) was used. Results The functional and software views of an HSP were designed in a layered architecture. External systems can be interfaced with the HSP using SOAP and REST/JSON. The multi-tenancy model of the HSP was designed as a shared database, with a separate schema for each tenant through a single application, although healthcare data can be physically located on a cloud or in a hospital, depending on regulations. The CDS services were categorized into rule-based services for medications, alert registration services, and knowledge services. Conclusions We expect that cloud-based HSPs will allow small and mid-sized hospitals, in addition to large-sized hospitals, to adopt information infrastructures and health information technology with low system operation and maintenance costs.
Collapse
Affiliation(s)
- Sungyoung Oh
- R&D Institute, ezCaretech Co. Ltd., Seoul, Korea
| | - Jieun Cha
- R&D Institute, ezCaretech Co. Ltd., Seoul, Korea
| | - Myungkyu Ji
- R&D Institute, ezCaretech Co. Ltd., Seoul, Korea
| | | | - Seok Kim
- Center for Medical Informatics, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Eunyoung Heo
- Center for Medical Informatics, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Jong Soo Han
- Health Promotion Center & Department of Family Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
| | | | - Hoseok Chae
- R&D Institute, ezCaretech Co. Ltd., Seoul, Korea
| | - Hee Hwang
- Center for Medical Informatics, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Sooyoung Yoo
- Center for Medical Informatics, Seoul National University Bundang Hospital, Seongnam, Korea
| |
Collapse
|
22
|
Griebel L, Prokosch HU, Köpcke F, Toddenroth D, Christoph J, Leb I, Engel I, Sedlmayr M. A scoping review of cloud computing in healthcare. BMC Med Inform Decis Mak 2015; 15:17. [PMID: 25888747 PMCID: PMC4372226 DOI: 10.1186/s12911-015-0145-7] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2014] [Accepted: 03/04/2015] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Cloud computing is a recent and fast growing area of development in healthcare. Ubiquitous, on-demand access to virtually endless resources in combination with a pay-per-use model allow for new ways of developing, delivering and using services. Cloud computing is often used in an "OMICS-context", e.g. for computing in genomics, proteomics and molecular medicine, while other field of application still seem to be underrepresented. Thus, the objective of this scoping review was to identify the current state and hot topics in research on cloud computing in healthcare beyond this traditional domain. METHODS MEDLINE was searched in July 2013 and in December 2014 for publications containing the terms "cloud computing" and "cloud-based". Each journal and conference article was categorized and summarized independently by two researchers who consolidated their findings. RESULTS 102 publications have been analyzed and 6 main topics have been found: telemedicine/teleconsultation, medical imaging, public health and patient self-management, hospital management and information systems, therapy, and secondary use of data. Commonly used features are broad network access for sharing and accessing data and rapid elasticity to dynamically adapt to computing demands. Eight articles favor the pay-for-use characteristics of cloud-based services avoiding upfront investments. Nevertheless, while 22 articles present very general potentials of cloud computing in the medical domain and 66 articles describe conceptual or prototypic projects, only 14 articles report from successful implementations. Further, in many articles cloud computing is seen as an analogy to internet-/web-based data sharing and the characteristics of the particular cloud computing approach are unfortunately not really illustrated. CONCLUSIONS Even though cloud computing in healthcare is of growing interest only few successful implementations yet exist and many papers just use the term "cloud" synonymously for "using virtual machines" or "web-based" with no described benefit of the cloud paradigm. The biggest threat to the adoption in the healthcare domain is caused by involving external cloud partners: many issues of data safety and security are still to be solved. Until then, cloud computing is favored more for singular, individual features such as elasticity, pay-per-use and broad network access, rather than as cloud paradigm on its own.
Collapse
Affiliation(s)
- Lena Griebel
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Hans-Ulrich Prokosch
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Felix Köpcke
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Dennis Toddenroth
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Jan Christoph
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Ines Leb
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Igor Engel
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Martin Sedlmayr
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| |
Collapse
|
23
|
Fazio M, Celesti A, Puliafito A, Villari M. Big Data Storage in the Cloud for Smart Environment Monitoring. ACTA ACUST UNITED AC 2015. [DOI: 10.1016/j.procs.2015.05.023] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
|
24
|
Pérez GM, Swart W, Munyenyembe JK, Saranchuk P. Barriers to pilot mobile teleophthalmology in a rural hospital in Southern Malawi. Pan Afr Med J 2014; 19:136. [PMID: 25767656 PMCID: PMC4345219 DOI: 10.11604/pamj.2014.19.136.5196] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2014] [Accepted: 08/26/2014] [Indexed: 11/11/2022] Open
Abstract
INTRODUCTION Malawi has one of the highest HIV prevalences in Sub-Saharan Africa. The rate of eligible HIV-infected people being initiated on antiretroviral therapy (ART) and retained in HIV-care is currently far from adequate. Consequently, many people continue present with advanced immunosuppression at public health facilities, often with undiagnosed opportunistic infections (OIs). METHODS In this context, mHealth was the innovation chosen to assist Eye Clinical Officers in early diagnosis of HIV-related diseases having eye manifestations in a rural hospital in Thyolo, Southern Malawi. RESULTS The mTeleophthalmology program began in October 2013, but was stopped prematurely due to organizational and technological barriers that compromised its feasibility. CONCLUSION Sharing these barriers might be useful to inform the design of similar innovations in other resource-limited settings with a high HIV prevalence and a dearth of eye specialists with capacity to diagnose HIV-related retinopathies.
Collapse
Affiliation(s)
| | - Wayne Swart
- Department of Mechanics and Mechatronics, University of Stellenbosch, South Africa
| | | | - Peter Saranchuk
- Southern Africa Medical Unit, Médecins Sans Frontières, Cape Town, Southern Africa
| |
Collapse
|
25
|
A mobile device system for early warning of ECG anomalies. SENSORS 2014; 14:11031-44. [PMID: 24955946 PMCID: PMC4118409 DOI: 10.3390/s140611031] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2014] [Revised: 06/05/2014] [Accepted: 06/10/2014] [Indexed: 12/05/2022]
Abstract
With the rapid increase in computational power of mobile devices the amount of ambient intelligence-based smart environment systems has increased greatly in recent years. A proposition of such a solution is described in this paper, namely real time monitoring of an electrocardiogram (ECG) signal during everyday activities for identification of life threatening situations. The paper, being both research and review, describes previous work of the authors, current state of the art in the context of the authors' work and the proposed aforementioned system. Although parts of the solution were described in earlier publications of the authors, the whole concept is presented completely for the first time along with the prototype implementation on mobile device—a Windows 8 tablet with Modern UI. The system has three main purposes. The first goal is the detection of sudden rapid cardiac malfunctions and informing the people in the patient's surroundings, family and friends and the nearest emergency station about the deteriorating health of the monitored person. The second goal is a monitoring of ECG signals under non-clinical conditions to detect anomalies that are typically not found during diagnostic tests. The third goal is to register and analyze repeatable, long-term disturbances in the regular signal and finding their patterns.
Collapse
|