The Internet of Medical Things: Enabling technologies and emerging applications
2: DIT University, India
3: Department of Engineering and Architecture, University of Parma, Parma, Italy
4: Department of Informatics, South-West University "Neofit Rilski", Bulgaria
5: Department of Mechatronics and Robotics, Xi'an Jiaotong-Liverpool University, Suzhou, China
The Internet of Medical Things (IoMT) allows clinicians to monitor patients remotely via a network of wearable or implantable devices. The devices are embedded with software or sensors to enable them to send and receive data via the internet so that healthcare professionals can monitor health data such as vital statistics, metabolic rates or drug delivery regimens, and can provide advice or treatment plans based on this real-world, real-time data. This edited book discusses key loT technologies that facilitate and enhance this process, such as computer algorithms, network architecture, wireless communications, and network security. Providing a systemic review of trends, challenges and future directions of IoMT technologies, the book examines applications such as breast cancer monitoring systems, patient-centric systems for handling, tracking and monitoring virus variants, and video-based solutions for monitoring babies. The book discusses machine learning techniques for the management of clinical data and includes security issues such as the use of blockchain technology. Written by a range of international researchers, this book is a great resource for computer engineering researchers and practitioners in the fields of data mining, machine learning, artificial intelligence and the loT in the healthcare sector.
Inspec keywords: cloud computing; diseases; medical information systems; Internet of Things; health care
Other keywords: Internet of Medical Things; patient monitoring; Big Data; medical information systems; medical computing; Internet; blockchains; cloud computing; health care; diseases
Subjects: Biology and medical computing; Data security; Education and training; General electrical engineering topics; General and management topics; Computer communications; Medical administration; Internet software
- Book DOI: 10.1049/PBHE034E
- Chapter DOI: 10.1049/PBHE034E
- ISBN: 9781839532733
- e-ISBN: 9781839532740
- Page count: 384
- Format: PDF
-
Front Matter
- + Show details - Hide details
-
p.
(1)
-
1 Internet of medical things (IoMT): a systematic review of applications, trends, challenges, and future directions
- + Show details - Hide details
-
p.
1
–18
(18)
The Internet of medical things (IoMT) is rapidly changing the healthcare sector. IoMT paired with enabling technologies like artificial intelligence, cloud computing, wireless sensor networks can effectively monitor people's health continuously. In this chapter, the author provides a systematic review of the architectures of IoMT, applications, and trends in IoMT. IoMT applications to counter the COVID-19 pandemic are also dis cussed. IoMT and enabling technologies will improve the quality of human lives. This chapter addresses a few challenges while adopting IoMT in healthcare.
-
2 Non-invasive psycho-physiological driver monitoring through IoT-oriented systems
- + Show details - Hide details
-
p.
19
–33
(15)
The definition, analysis, and implementation of in-vehicle monitoring systems that collect data which are informative of the status of the joint driver-vehicle system represent a topic of strong interest from both academic players and industrial manufacturers. Many external factors, such as road design, road layout, traffic flow, and weather, can influence and increase driving-related stress, potentially increasing risks. The ubiquitous diffusion of Internet of Things (IoT) technologies allows one to collect heterogeneous data that can build the foundation for driver's psychophysiological characterization, with the aim of improving safety and security while driving. This chapter evaluates and discusses the feasibility and usefulness of a noninvasive IoT-oriented driver monitoring infrastructure aiming at collecting physiological parameters (such as heart rate variability, HRV) that may be adopted as biomarkers of the driver's psychophysiological state in different driving scenarios.
-
3 IoT-based biomedical healthcare approach
- + Show details - Hide details
-
p.
35
–53
(19)
The Internet of Things (IoT) enables physical items and devices to see, hear, and think by exchanging data. The IoT works in the other direction, converting ordinary items into intelligent ones. Embedded devices, communication protocols, sensor networks, Internet protocols, and applications are examples of IoT-specific technology. Certain IoT-based healthcare solutions, such as mobile health and telecare, as well as preventative, diagnostic, therapeutic, and monitoring systems, fundamentally modify everything. Wireless body area networks (WBANs) and radio frequency identification (RFID) are unquestionably important components of the IoT. This chapter is covered, in addition to research on the usage of IoT in the field of biomedical systems to be applied within the framework.
-
4 Impact of world pandemic "COVID-19" and an assessment of world health management and economics
- + Show details - Hide details
-
p.
55
–92
(38)
For the COVID-19 pandemic, international health facilities have been issued in financial section with difficulty. According to the economic status, several hospitals and healthcare facilities loses a month in sales. Furthermore, providing an adequate healthcare solution to COVID-19 could cost $52 billion (around $8.60 per person) for low- and middle-income countries (LMICs). Could burden have a significant effect on health treatment, surgeries, and outcomes through the use of COVID-19. This year the World Bank predicts that the global economy would contract by about 8%, with developing countries bearing the brunt of the burden. Lack of planning was a key in dealing with healthcare facility issues everywhere. On a national scale, items such as gowns, gloves, facemasks, syringes, disinfectants, and toilet paper ran out. Healthcare worldwide has felt threatened by COVID-19's findings and has responded by formulating new programs to deal with pandemics. In this article, we will talk about the financial implications of COVID 19 that include clinics, surgery, and medical procedures on both the US and foreign healthcare systems, in the United States and abroad.
-
5 Artificial intelligence in healthcare
- + Show details - Hide details
-
p.
93
–110
(18)
The presented chapter is 5-fold. First, the distinct data sources where the healthcare data is gathered from are discussed. Second, we talk about the moral and lawful difficulties of AI-driven medical care. Next, the structured and unstructured types of healthcare data have been analysed followed by the AI techniques applied to these types of data, such as ML, natural language processing (NLP), and DL. We then analyse the crucial disease areas such as cardiology, radiology, neurology, and cancer, where the health issues can be alleviated by employing AI techniques. In conclusion, we further discuss the areas where AI-based techniques are applied in real life.
-
6 Blockchain in IoT healthcare: case study
- + Show details - Hide details
-
p.
111
–126
(16)
A health monitoring system has been proposed to sense the vital body parameters and to store and share them in a secure environment. The vital body parameters are sensed from the patient using sensors. The sensed data is then stored into blockchain. The stored data can be accessed by the patient and doctors using a Web application. When a doctor needs to access the information about a patient from another doctor, they only need to transfer the patient ID between themselves to access the data. The proposed system addresses these challenges using IoT, blockchain, and a Web application. The model aims to provide secure storage along with monitoring and sharing of vital body parameters.
-
7 Adaptive dictionary-based fusion of multi-modal images for health care applications
- + Show details - Hide details
-
p.
127
–137
(11)
This chapter proposes a multimodal medical fusion method based on adaptive dictionary learning. Because the adaptive dictionary is trained based on the modified spatial frequency (MSF) indicator and used for the fusion of medical images, the suggested method is called MIFMSF.
-
8 Artificial intelligence for sustainable e-Health
- + Show details - Hide details
-
p.
139
–154
(16)
The study of exploring the improvement of efficiency in e-Health is done by means of regulating an access to electronic health records (EHRs). In the absence of appropriate apex bodies, EHR will continue to stay as lopsided and discrete network of lagging systems without much ability to attain accuracy and consistency, and thereby efficiencies. A multinational corporation (MNC) model is prescribed to cut down healthcare (HC) expenses and execute a coherent system wherein data, technology, and training are consistently upgraded to remove any interoperability-related problems. The literature review reveals that EHR interoperability issues may be met by generating architectures that drive fragmented systems to interoperate on the guidelines of watch dog agencies. This chapter suggests a fundamental technology driven model predicting the need to get over interoperability problems and followed by suggesting an organizational model that would be the most suitable solution catering to the needs of a coherent system where data, technology, and training are consistently and regularly upgraded. Hence, an artificial intelligence (AI)-driven model is prescribed to facilitate the improvement in the efficiency of e-Health to standardize HER. This treatise deliberates on the research opportunities to provide sustainable e-health solutions particularly during pandemic like COVID-19 and keeping in view diabetes HC as a case study.
-
9 An innovative IoT-based breast cancer monitoring system with the aid of machine learning approach
- + Show details - Hide details
-
p.
155
–180
(26)
The increasingly revolutionary Internet of Things (IoT) grows rapidly in modern life with the intent of increasing the quality of life by integrating a variety of intelligent tools, technologies, and applications. The IoT Medical Devices will revolutionize the medical industry by creating an environment where patient data is transmitted to a cloud-based storage, processing and analysis network. This chapter provides novel tools for the continuous follow-up of breast cancer (BC) patient conditions - and iTBra that has incorporated sensors that monitor cell temperatures and transfer data on to a patient database in real time.
-
10 Patient-centric smart health-care systems for handling COVID-19 variants and future pandemics: technological review, research challenges, and future directions
- + Show details - Hide details
-
p.
181
–224
(44)
Information technology can play a vital role in future smart health-care systems. Using information technology, health-care services can be improved. This improvement includes shifting the specialization or department-centric health-care services to patient-centric health-care services. This shift is necessary to have better patient experiences and providing specialized health-care services to many patients with lesser resources. In information technology, the Internet of Things (IoT) is an advanced approach for ensuring this system. In IoT, industrial IoT (IIoT), Internet of nano things, Internet of robots, Internet of patients, and Internet of medical things (IoMT) are some of the concepts important to understand the functionality of smart health-care system. In addition to IoT or its variants, other IoT-associated solutions that include blockchain technology, parallel and distributed computing approaches (cloud/fog/edge), virtualization, cybersecurity, automated software development, and smart infrastructure development have shown great enhancements in recent times. The objective of this work is to explore different information-technology-based solutions that can make a patient-centric smart health-care system feasible in nearby times. In this work, recent developments of IoT that are used to interconnect health-care objects and made technical revolutions will be explored initially. Thereafter, IoT association with other technological approaches will be explored.
-
11 Application of intelligent techniques in health-care sector
- + Show details - Hide details
-
p.
225
–236
(12)
Artificial intelligence (AI) is more important in today's technological world. It is a cacophony of technology. AI has been instrumental in transforming several aspects of healthcare and has proven to be more efficient than human caregivers. The dynamic increase in the number of population of the world provides excess pressure over the health-care system. Hence, AI provides new technologies for delivering the benefits to human health and well-being. Thus, this chapter focuses on the importance of AI, health-care system in India followed by the future scope and the challenges.
-
12 Managing clinical data using machine learning techniques
- + Show details - Hide details
-
p.
237
–250
(14)
Analyzing clinical data is a great challenge in today's digital data world. This perspective imposes the need of machine learning (ML) algorithms to extract useful patterns in clinical data. This chapter improves patient care by diagnosing disease accurately. It also helps to study the importance of clinical data and managing into PySpark environment. Various disease datasets are trained to ML techniques (MLT) to identify the best model. It ensures the collection of clinical data from different sources, integrating and extracting the useful patterns with less time consumption. This approach improves the understanding of clinical data and improves patient care.
-
13 Use of IoT and mobile technology in virus outbreak tracking and monitoring
- + Show details - Hide details
-
p.
251
–267
(17)
We suggest a model for IoT-based health-care systems in this chapter, which can be used for both general systems and systems that monitor special conditions. Then, for each component of the proposed model, we submitted a detailed and systematic overview of the state-of-the-art works. Several nonintrusive, wearable sensors were demonstrated and evaluated, with a focus on those that monitor vital signs, BP, and blood oxygen levels. The suitability of short-range and long-range communication requirements for health-care applications was then compared. For short-range and long-range communications in healthcare, bilateral lower extremity and NarrowBand-Internet of Things (NB-IoT) emerged as the most suitable standards. Recent cloud-based data storage research was introduced, demonstrating that the cloud is the best option for storing and coordinating big data in healthcare. Several studies have also found that data processing in the cloud is much better than data processing on wearable devices with their limited resources. The most important dis-advantage of using the cloud is that it adds security risks; as a result, we introduced several works aimed at enhancing cloud security. Access control policies and encryption were discovered to substantially improve security, but no known standard is suitable for immediate implementation in a wearable, IoT-based health-care system. We found several important areas for future study based on our analysis of state-of-the-art technologies in the fields of wearable sensors, communication standards, and cloud technology. Machine learning and the development of a secure but lightweight encryption scheme for cloud storage are the two areas where're searchers looking to make substantial changes in the field of IoT-based healthcare have the most opportunities.
-
14 Video-based solutions for newborn monitoring
- + Show details - Hide details
-
p.
269
–281
(13)
Efficient monitoring of vital signs is a fundamental tool in disease prevention and medical diagnostics. Main physiological parameters to monitor are not only heartrate, blood pressure, respiratory rate and body temperature, but motion analysis may also provide essential information about the clinical status of a patient. Very specific pathological movements can indeed be signs of important or potentially threatening disorders. Besides being almost exclusively performed in hospital settings, conventional monitoring often requires a contact with the body of the patient that makes traditional systems possibly invasive and uncomfortable, especially if applied on new-borns. To make home care more accessible and comfortable, novel methods for remote and contactless monitoring have been developed in the recent years. Among others, appealing solutions that have received recent research attention are based on video processing techniques that allow to capture and analyse the movements of a patient in a contactless fashion.
-
15 IoT sensor networks in healthcare
- + Show details - Hide details
-
p.
283
–304
(22)
Over the past few years, there have been numerous advances in the health-care industry. Incorporation of Internet of Things (IoT) in the health-care application shas unlocked numerous possibilities in the way healthcare operates now. This chapter concentrates on IoT sensor networks in healthcare. The suitability of sensor networks in healthcare is presented. The applications in which IoT sensor networks play a crucial role, and thus related sensors are presented. Key sensors, and their applications in healthcare, are presented. The most common and popular use cases of IoT sensor networks in healthcare are discussed. The wireless communication technologies used in IoT sensor networks for healthcare are described along with their characteristics. Even though health-care IoT (H-IoT) networks have been in use for some time, and their incorporation in health-care services is only expected to increase further over the years, their implementation and adoption is still a challenge. This chapter discusses those challenges in detail. The potential con-temporary technologies that help in overcoming these challenges are explained.
-
16 Machine learning for Healthcare 4.0: technologies, algorithms, vulnerabilities, and proposed solutions
- + Show details - Hide details
-
p.
305
–329
(25)
Healthcare 4.0 is motivated from Industrie 4.0. It is a boon to the present health care system due to its widespread applications that have boosted its efficiency and enhanced its services. Healthcare 4.0 is a vision that integrates all the leading technologies together given that each technology has different benefits to offer to the system. Various technologies such as big data, Health Cloud (HC), Health Fog (HF), Internet of Things (IoT), blockchain, and machine learning (ML) are incorporated in Healthcare 4.0. There are many applications of Healthcare 4.0 for patients, health-care professionals, resource management, etc. This chapter aims to study ML with respect to Healthcare 4.0 and highlights different ML algorithms and its applications for healthcare in different phases such as prognosis, diagnosis, treatment, and clinical workflow. ML provides many solutions for Healthcare 4.0 which have applicability for patients, health-care professionals, as well as health care facilities. However, there is some vulnerability for ML in healthcare that needs to be checked. This chapter highlights these vulnerabilities and presents the recently proposed solutions in this regard.
-
17 Big data analytics and data mining for healthcare and smart city applications
- + Show details - Hide details
-
p.
331
–353
(23)
The unprecedented growth of population in urban areas has been causing a challenge for the citizens in their day-to-day lives such as road congestion, public security, environmental pollution, electricity shortage and water shortage. This chapter explores the current challenges that are faced during the indigenous development of smart cities. Furthermore, the chapter discusses the theoretical background of smart cities with the explanation of their components. Moreover, the chapter describes the necessity of computational infrastructure for smart cities in a framework of big data and DM. The chapter highlights some mining methods for extracting important information from huge and mixed data. Additionally, the chapter examines the advancement of healthcare sector in smart cities in context of big data and DM.
-
Back Matter
- + Show details - Hide details
-
p.
(1)