Machine Intelligence for Internet of Medical Things: Applications and Future Trends E-Book
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- Herausgeber: Bentham Science Publishers
- Kategorie: Fachliteratur
- Serie: Computational Intelligence For Data Analysis
- Sprache: Englisch
This book presents use-cases of IoT, AI and Machine Learning (ML) for healthcare delivery and medical devices. It compiles 15 topics that discuss the applications, opportunities, and future trends of machine intelligence in the medical domain. The objective of the book is to demonstrate how these technologies can be used to keep patients safe and healthy and, at the same time, to empower physicians to deliver superior care.
Readers will be familiarized with core principles, algorithms, protocols, emerging trends, security problems, and the latest concepts in e-healthcare services. It also includes a quick overview of deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, practical methodology, and how they can be used to provide better solutions to healthcare related issues. The book is a timely update for basic and advanced readers in medicine, biomedical engineering, and computer science.
Key topics covered in the book:
- An introduction to the concept of the Internet of Medical Things (IoMT)
- Cloud-edge based IoMT architecture and performance optimization in the context of Medical Big Data
- A comprehensive survey on different IoMT interference mitigation techniques for Wireless Body Area Networks (WBANs)
- Artificial Intelligence and the Internet of Medical Things
- A review of new machine learning and AI solutions in different medical areas.
- A Deep Learning based solution to optimize obstacle recognition for visually impaired patients
- A survey of the latest breakthroughs in Brain-Computer Interfaces and their applications
- Deep Learning for brain tumor detection
- Blockchain and patient data management
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Seitenzahl: 439
Veröffentlichungsjahr: 2009
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FOREWORD
The COVID-19 pandemic has shed light on the importance of having a more efficient healthcare system. In the era of Industry 4.0, Artificial Intelligence and the Internet of Things have introduced themselves today as must-have technologies in almost every sector, including healthcare.
This book introduces an emerging yet interesting concept, the Internet of Medical Things (IoMT). It refers to an infrastructure of highly connected healthcare devices that can communicate and share data to optimize different medical actions and interventions. The book goes further into suggesting solutions that can provide better performance and security for the Internet of Medical Things.
Moreover, this book presents different successful case studies of combinations of IoMT with Artificial Intelligence and their application in different medical use cases, such as preventing future pandemics, optimizing brain tumor detection, obstacle detection for visually impaired patients, etc.
In its last chapter, this book offers an opening to further development in the IoMT area by exploring the possibilities offered by Blockchain technology in securing medical data.
This book aspires to provide a relevant reference for students, researchers, engineers, and professionals working in the IoMT area, particularly those interested in grasping its diverse facets and exploring the latest advances in IoMT.
PREFACE
The growing development in the field of computing has encouraged the integration of a variety of sophisticated devices inside houses and facilities. These devices communicate with each other to help users in particular situations and according to their needs, such as safety, comfort, and even health. The devices form an object connection environment known as the Internet of Things (IoT). Healthcare professionals are now embracing the Internet of Medical Things (IoMT), which refers to a connected infrastructure of devices and software applications that can communicate with various healthcare IT systems. One of these technologies — Remote Patient Monitoring — is commonly used for the treatment and care of patients.
Often associated with the IoT, Artificial Intelligence (AI) opens the field of possibilities in the medical area, in particular, by allowing the development of new diagnostic and interpretation tools of exceptional reliability and by assessing the large volumes of data that can be generated through the networks by sensors and users.
OBJECTIVE OF THE BOOK
The objective of this book is to focus on how to use IoT, AI and Machine Learning (ML), to keep patients safe and healthy and, at the same time, to empower physicians to deliver superlative care.
This book discusses the applications, opportunities, and future trends of machine intelligence in the medical domain, including both basic and advanced topics.
This book provides core principles, algorithms, protocols, emerging trends, security problems, and the latest e-healthcare services findings. It also includes deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, practical methodology, and how they can be used to provide better solutions to healthcare-related issues.
ORGANIZATION OF THE BOOK
Chapters 1-3: The authors introduce the concept of the Internet of Medical Things (IoMT), its roles, challenges, and the opportunities it may present to the healthcare system.
Chapter 4: The authors present a cloud-edge-based IoMT architecture and discuss the performance optimization it may provide in the context of Medical Big Data.
Chapter 5: The authors provide a comprehensive survey on different IoMT interference mitigation techniques for Wireless Body Area Networks (WBANs).
Chapters 6 and 7: The authors explore the possibilities that Artificial Intelligence and the Internet of Things can provide to prevent future pandemics.
Chapters 8-10: The authors provide a comprehensive review of the newest Machine Learning based solutions in different medical areas.
Chapter 11: The authors go through the latest discoveries in curing cardiovascular diseases by implementing Artificial Intelligence in healthcare settings.
Chapter 12: The authors propose a Deep Learning based solution to optimize obstacle recognition for visually impaired patients.
Chapter 13: The authors provide a survey on the latest breakthroughs in Brain-Computer Interfaces and their applications.
Chapter 14: The authors propose a solution to optimize the performance of Deep Learning for brain tumor detection.
Chapter 15: The authors explore the possibilities that Blockchain may offer inpatient data management.
List of Contributors
Internet of Medical Things & Machine Intelligence
Inam Ullah Khan1,Mariya Ouaissa2,*,Mariyam Ouaissa2,Sarah El Himer3Abstract
Recently, the internet of medical things has been the widely utilized approach to interconnect various machines. While, IoT in combination with machine intelligence, has given new directions to the healthcare industry. Machine intelligence techniques can be used to promote healthcare solutions. The merger of IoT in medical things is a completely advanced approach. The intelligent behavior of machines provides accurate decisions, which greatly helps medical practitioners. For real-time analysis, artificial intelligence improves accuracy in different medicinal techniques. The use of telemedicine has increased so much due to COVID-19. Gathering unstructured data where the concept of electronic databases should be used in the health care industry for advancement. Big data and cyber security play an important role in IoMT. An intrusion detection system is used to identify cyber-attacks which helps to safeguard the entire network. This article provides a detailed overview of the internet of medical things using machine intelligence applications, future opportunities, and challenges. Also, some of the open research problems are highlighted, which gives insight into information about the internet of medical things. Different applications are discussed related to IoMT to improve communication standards. Apart from that, the use of unmanned aerial vehicles is increased, which are mostly utilized in rescuing and sending medical equipment from one place to another.
INTRODUCTION
With the development of IoT, the healthcare industry is revolutionized, where a massive amount of data can be transferred from one place to another. Therefore, IoMT is introduced to connect medical devices, which can improve decision-making process. Data resource management is the central point of discussion in IoMT. However, machine learning techniques enhance the accuracy level, which has shifted researcher’s attention to secure communication between nodes.
COVID-19 is considered the most dangerous virus which affects the respiratory system. Machine intelligence-based techniques can be used for the effective treatment of viruses. AI and machine learning refers to solving big problems related to healthcare [1, 2].
An advance in the healthcare industry has enhanced standards for different stakeholders like patients, doctors and researchers. Therefore, AI, machine learning, cyber security, big data and 5G can be integrated with IoMT to give optimal solutions [3]. Sensors and a high level of hardware equipment are needed to modify healthcare industry processes. Due to that, IoT with medical is quite helpful [4]. Integrated applications are designed using AI models for disease treatments [5, 6].
This research work provides novel ideas related to the internet of medical things using artificial intelligence, machine learning, and meta-heuristic search optimization to give directions to researchers. However, the major contribution of this article is as below:
Big data and AI-designed techniques for the health care industry.Machine learning concepts for IoMT.Applications for IoMT.Safeguarding IoMT from cyber-security attacks.Future advances and challenges.The contribution points are fully incorporated in the rest of the paper, which gives a detailed overview of IoMT applications, challenges, AI, big data and machine learning techniques. Fig. (1) illustrates the concept of tele-medicine, which was mostly used during COVID-19 for online consultation with medical doctors. Also, the whole architectural view of tele-medicine is presented.
Fig. (1)) Internet of medical things (tele-medicine).LITERATURE STUDY
IoT has interconnected patients, doctors and related equipment’s in the healthcare industry. However, different sensors are used to collect, send and manage the data. Various applications of IoT are utilized which use to tackle COVID-19. Therefore, IoT connects each and everything while machine learning techniques diagnose diseases [7]. The Internet of health things has changed the dynamics in health management. Federated learning is a new concept that is sub part of machine learning. This novel technique takes data in central servers and local devices, which makes the data safer in contrast with other traditional methods [8]. However, local models must be properly updated using 5G communication networks [9]. Protocols are designed while integrating 5G networks with federated learning [10]. Lightweight protocols are proposed to bring trust between two nodes in IoMT [11, 12].
COVID-19 has disturbed our daily life routine, where we have to maintain social distancing and make people aware of vaccination [13, 14]. While, the health status of patients and much more information can be easily made available due to various advancements in IoT, cyber security, big data, AI and machine learning [15-19].
In addition, UAVs are widely used during COVID-19 to send medical equipment and rescue operations. Also, tele-medicine is nowadays commonly utilized by doctors to properly advise patients. Therefore, secure routing is needed between nodes.
BIG DATA & AI FOR HEALTHCARE
Artificial intelligence is making life easier for humans. Due to advanced communication technologies, life has become more comfortable. AI merger with big data has solved major problems related to healthcare. Electronic healthcare records are quite helpful in improving tumors to optimize treatment methods [20].
The healthcare industry is based on data that should be authentic. Due to this, decision-making process will be quite efficient. The data usually flow from patients to doctors where to share possible information to give possible treatment.
However, in traditional methods, the data or record cannot be preserved for a long period of time. While, digitalization utilizing big data analytics and artificial intelligence has improved the standards of technological equipment’s [21].
MACHINE LEARNING CONCEPTS FOR THE INTERNET OF MEDICAL THINGS
Machine learning techniques have played an important role in developing data and records more efficiently. Moreover, machine learning presented novel ideas to digitalize and improve computer-aided technologies [22]. The growth of mobile devices and the merger of the Internet of things has changed the dynamics of the medical field. The quality of service has solved unprecedented problems and given mobile medical services, including tele-medicines. Using mobile technology in the form of web services, patient consultation with the doctor is quite easy nowadays [23, 24]. Health applications like “Good Doctor Online” is utilized more for tele-medicine during COVID-19. Mobile data will be quite useful in the future to observe the needs of patients. While, for remote treatment, health expert systems provide many services like audio, video and short messages. Therefore, initial data will be taken from patients with the help of technology, and based on that, the doctor will give possible guidance [25].
In healthcare engineering, following machine learning techniques can be utilized to solve problems.
Classification & ClusteringPrediction & Anomaly identificationMACHINE LEARNING-BASED APPLICATIONS FOR IOMT
In addition, machine learning has many related applications that have improved healthcare standards. Some of the applications are as below:
Early Prediction of Illnesses
For better treatment, three diseases, coronavirus, heart disease and diabetes model, are formulated in the form of an android mobile application. A supervised learning model is utilized for training the database on real-time data, which shows results in android applications. Therefore, logistic regression is used for the early prediction of illness [26].
Healthcare E-Records
In the fourth industrial revolution, an electronic health record is an optimal way to save data. Medical data is so importantthat intruders can try to hijack the entire system, which is very dangerous for the patient. Medical healthcare systems are changed with the passage of time, but had vulnerabilities as well. Due to cyber-attacks, falsification, data loss, end-to-end delay, jitter and modification of packets are possible, which endanger the life of patient. Therefore, an intelligent & secure electronic health record system is designed to reduce cost and improve trust using blockchain [27].
Apart from that, many more applications are available, or either scientists or engineers are working to improve the healthcare industry, which is as below:
Humanoid robot surgeryNovel disease breakthroughDrug discovery and clinical trialsTable 1 describes the applications related to IoMT.
SAFEGUARDING IOMT FROM CYBER-ATTACKS
Wearable devices will be utilized in the near future to collect data from humans and send information to the external device. The data or information can either be viewed by using a laptop or computer or might be mobile. Emergency response sensors can be deployed at home or the workplace to monitor emergencies and send locations to the base station. The entire information can be viewed through web applications or mobile devices. Mobile applications are developed to facilitate patients for proper and timely medication. For this purpose, sometimes an alert message is sent to the mobile device of the patient.
Internet of medical things architecture is divided into three phases which include:
Wireless Body Area Sensor NetworksWireless Personal Area NetworkWireless Wide Area NetworkMedical Server (Laptop or Mobile)Emergency Service ProviderDue to the extensive use of wireless communication technologies, the ratio of cyber-attacks is increasing. While, the medical industry is the main focus of intruders to take information or change the data [28]. Some of the commonly used attacks are discussed as under:
DoS Attack in IoMT
Denial of service is also called third-party attack. Due to this attack, the intruder tries to take full control of the network or either modify data packets. Broadcasting illegal data packets in a continuous pattern affects the process of the Internet of things [29].
DDoS Attack in IoMT
Distributed denial of service attack is considered the most dangerous threat to every network. In DDoS, the entire cluster or group attacks another to send false information to create congestion and take control. DDoS is the extended version of a DoS attack [30].
Some other attacks also disrupt the entire communication in IoMT, which are as under:
Routing AttackFalse Alarm AttackUnbalancing High Accuracy AttackOverhead AttackData Traffic AttackUnwanted Nodes AttackFig. (2)) Different types of attacks.Fig. (2) describes different types of security attacks which can affect overall communication in IoMT.
FUTURE ADVANCES & CHALLENGES
Machine learning techniques like supervised, unsupervised, and reinforcement have greatly changed the healthcare industry. Quality of service is improved due to technological inventions to modernize the healthcare field. ML in health technologies has given deep information to improve treatment methods. While, due to cognitive computing identification of different diseases can be easily treated in a better way. Drug discovery, medical imaging, behavioral medicines, a database for healthcare records and data collection will be improved with the help of machine learning algorithms [31]. However, AI-based telemedicine will give new directions to the entire world [32]. Moreover, unmanned aerial vehicles are widely used during COVID-19 to send medical equipment and maintain physical distancing.
With the usage of new technology, some of the problems to a normal human being exist. People should update their knowledge about every subject, especially healthcare, as information technology has improved.
CONCLUSION
The role of machine learning algorithms has a direct impact on the internet of medical things. Therefore, machines are trained to give an optimal prediction for illness or disease. AI-based tools have advanced the way of treatment. Also, IoMT is a combination of the internet of things and the medical field. This research paper gives knowledge related to big data, AI, machine learning, cyber-attacks, and various applications related to IoMT. In addition, future directions and challenges are incorporated, which is very much helpful for engineers, scientists, researchers and practitioners. AI, ML and meta-heuristic search algorithms will be deployed in the future to enhance communication within IoMT.
CONSENT FOR PUBLICATON
Declared none.
CONFLICT OF INTEREST
The author declares no conflict of interest, financial or otherwise.
ACKNOWLEDGEMENT
Declared none.
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First Workshop on IoT-enabled Healthcare and Wellness Technologies and Systems, June 30, 2016..Health Services and Applications Powered by the Internet of Medical Things
Briska Jifrina Premnath1,Namasivayam Nalini1,*Abstract
The traditional healthcare system model is now out of date. As the digital era progresses, new advanced technologies and service platforms are highly demanded. The Internet of Medical Things (IoMT), a subset of the Internet of Things, is one such technology. The Internet of Things (IoT) is a network of wireless, interconnected, and linked digital devices that can collect, send and store data without requiring human-to- human or human-to-computer interaction. Understanding how established and emerging IoT technologies help health systems provide safe and effective care is more important than ever. For example, the rapid spread of Coronavirus disease (COVID-19) has alerted the entire healthcare system. The Internet of Medical Things (IoMT) has dramatically improved the situation, and COVID-19 has inspired scientists to create a new 'Smart' healthcare system focused on early diagnosis, prevention of spread, education, and treatment to facilitate living in the new normal. This paper provides an overview of the IoMT design and how cloud storage technology can help healthcare applications. This chapter should assist researchers in considering previous applications, benefits, problems, challenges, and threats of IoMT in the healthcare field and the role of IoMT in the COVID-19 pandemic. This review will be helpful to researchers and professionals in the field, allowing them to recognize the enormous potential of IoT in the medical world.
INTRODUCTION
Significant changes have taken place in the healthcare industry over the last few years. One crucial factor in this change is the use of new information technology across the business right now. Hospitals and nursing homes need help from many different IT service platforms and cutting-edge technology to meet the growing healthcare demand. The Internet of Medical Things, or IoMT, is one of the most
commonly used technologies in the healthcare field today. A subset of the Internet of Things is the Internet of Medical Things [1].
The term “Internet of Things” refers to a network of physical things, or “Things,” meant to communicate with each other through the Internet. Ashton first talked about the Internet of Things in 1999. Since then, it has overgrown, with about 10 billion connected devices today and an estimated 25 billion by 2025 [2].
Taking care of a person's physical, mental, or emotional well-being is called “health care,” usually done by trained and licensed professionals like doctors and other healthcare workers. There are not enough doctors, nurses, or hospital beds because there has been much growth in the population, and a lot more people are getting sick. Scientists who use the latest techniques and methodologies develop new medicine and healthcare trends every day. Researchers have recently focused their attention on the Internet of Things (IoT) because of its popularity as a perfect solution for healthcare systems that do not put much pressure on them [3].
Today, healthcare and modern technology businesses, especially healthcare systems, play a big part in our lives. The main goal of integrating technology into healthcare systems is to make it easier for patients and caregivers to communicate with each other. This will make medical devices and services more efficient and easier to get. The Internet of Medical Things (IoMT) has been essential in monitoring healthcare from afar (RHM). Wearable sensors and devices are often used to get data on patients remotely and store it in cloud databases. The Internet of Things (IoT) is used primarily for this. These data can be used by caregivers right away for analysis and planning [4].
IoMT consists of three main parts: the device layer [Body Sensor Network (BSN)], the fog layer, and the cloud service. The main goal of the device layer (sensing layer) is to build an effective and accurate sensing technology that can collect different types of health-based data. Communication technologies like Bluetooth, RFID (NFC), Wi-Fi, IrDA, UWB, and ZIGBEE help the IoMT system build network solutions and infrastructures. In the cloud layer (data layer), the data is processed and kept safe and sound. Furthermore, the cloud gets the patient's data to analyze, process, and store it. Healthcare workers can then use such data [5-12].
The IoMT is a group of medical strategies connected to networks. People can connect their smart glasses, head-mounted devices, belt-worn clothes, smartwatches, woven clothes, and smart wristbands to Wi-Fi, Bluetooth, or the Internet to get information about their health. Diagnostic machines such as ultrasonography, MRI machines, infusion pumps, ventilators, and X-ray machines in healthcare facilities use IOMT technologies. These IOMT wearable devices can be used to keep track of people's health of all ages. They are usually easy to wear and use. IOMT devices are used in applications and software, such as remote data analytics, medical assistance, operations augmentation, medicine monitoring, and accounting systems [13].
Remote Health Monitoring (RHM) is a way to track a person's health data regularly. People's heart rate, temperature, blood pressure, physical activities, and dietary habits are all monitored. The cloud sends health data wirelessly to both patients and caregivers. So, IoMT can make real-time, quick, remote, and trustworthy decisions for various disorders. This process generates many data, which is then analyzed and monitored. Due to the hectic pace of today's lives, most people do not go to the doctor regularly. In addition, healthcare costs are rising, and governments spend a lot of money on healthcare each year. People in Europe and the United States also prefer to get their health care at home rather than in a hospital. These problems can be solved if real-time healthcare monitoring can be done from afar and in real-time. The use of wearable gadgets and sensors to provide continuous monitoring for patients and the elderly has received a lot of interest [14-25].
Imagine a world where billions of things are connected through IP (Internet Protocol) networks and have built-in intelligence, communication, sensing, and actuation abilities. This is called the Internet of Things (IoT). Our current Internet has moved a lot away from hardware-based options (computers, fibers, and Ethernet connections) and toward market-based ones (such as apps) (Facebook, Amazon) [26].
This chapter will look at the technologies that make up IoMT and the benefits, problems, security concerns, and ways that IoMT can be used in healthcare. IoMT's role in COVID-19 is also addressed briefly.
CONCEPT FOR INTERNET-OF-THINGS-BASED HEALTHCARE
It is meant to allow for a wide range of types and services, each of which has a different set of Medicare solutions. There is not yet a complete list of IoT services in healthcare. Health care services can be hard to tell apart from other solutions or applications in some cases. It also looks at how potentially building blocks can be used in general service. In Medicare settings, IoT frameworks and protocols have been updated a little to make them work better. Simple, safe, low-power and quick discovery of new devices and services can be made and done quickly. There are many subtopics under the term “health service” that deal with future and emerging health services [3]. Fig. (1) illustrates the concept of IoMT in health care.
Fig. (1)) Concept of IoMT in healthcare.TECHNOLOGIES FOR HEALTHCARE SERVICE
The Internet of Things (IoT) healthcare services use many different technologies. However, the proposed system explains a few technologies at the heart of medical assistance.
Cloud Computing
If cloud computing is implemented, many cloud computing benefits come with IoT-based healthcare services. These features include always-on access to shared resources, services offered in response to network requests, and operations that meet the company's needs.
Grid Computing
Grid computing, also known as cluster computing, is the foundation of cloud computing. Grid computing makes it possible for all healthcare networks to deal with the computational limitations of sensor nodes spread out all over a patient's body.
Big Data
Big data collect essential health data from many different sensors all over our bodies. It also gives us tools that help us make the health diagnostic and monitoring stages and procedures more consistent.
Networks
The physical architecture of IoT-based healthcare networks includes a variety of networks ranging from short-range communications, such as 6LoWPANs, WPANs, WBANs, WLANs, and WSNs, to long-range communications, such as any type of cellular network. In developing low-power communication protocols and medical sensor devices, technologies such as Bluetooth Low Energy, radio frequency identification (RFID), and near-field communication (NFC) play a role.
Ambient Intelligence
Ambient Intelligence continuously monitors human activities and executes any action required for the recognized event. It is critical because it is constantly monitoring what individuals do.
Augmented Reality
Augmented reality emphasizes surgery and other standard patient examinations more than other technologies.
Wearable
Sensors like pulse, body temperature, pulse oximetry, and respiration rate are wearable because they are planned with soft, smooth, and easily wearable features. It is also easy to use and apply to the body of anyone. Wearables have many benefits, like gamification, connected data, and healthcare communities [3].
IOT'S HEALTHCARE BENEFITS
As with any new technology, there are some downsides to the Internet of Things, but it is primarily advantageous. The Internet of Things is causing a significant shift in medical health care. The Internet of Things applications and technologies have changed the world in ways that people did not think possible in the 1990s. Internet of Things created a significant change in people's communication with each other on the Internet. It led to the creation of many new and demanding fields, most notably in the area of medical things. Most people follow and utilize it due to its accurate and straightforward features. So, it bridges the gap between doctors, patients, and healthcare services. Thanks to the Internet of Things, health care workers can now do their jobs better and more quickly, with less effort and intelligence. This use of IoT in the medical field has been perfect for patients. IoT is also straightforward to use. People who use IoT can benefit from the following points:
Makes life easier.Cuts down on the cost of healthcare.Improves the health of patients.Diseases are taken care of in real-time.Improves the quality of life.Improves the end experience of users.The quality of care for patients is better.Expenses will be cut.The goal is for people to live longer with better health.Care and prevention of diseases should be done in the best way possible.The progress of children and parents who are old is kept on track.When there is a significant change in a patient's health, an automatic alarm is sent to many people, saving lives and time.Internet of Things (IoT) resources, as well as other IoT gadgets.There are rules about how to take medicine.Family members will be kept up to date on the patient's condition.The ability to make money.The ease of use.Making the best use of energy, including time.Think about money as an example, and you will get the idea.Doctors who use the Internet of Things to provide on-demand medical care [27].DIFFICULTIES IN IOMT
Before IOMT was widely used, many problems and consequences needed to be solved. These include data privacy and security, data management, scalability and upgradeability, legislation, interoperability and cost-effectiveness.
Confidentiality and Security of Data
One of the most challenging things to do in some applications is ensuring that cyber security works well in healthcare monitoring systems. The security of the massive amount of sensitive health data sent between systems is still an open question. Akhbarifar et al. (2020) came up with a way to make it easier to monitor people's health from afar in a cloud-based IoMT setting. Lin et al. (2021) suggested using a smartcard system for a single sign-on (SC-UCSSO) for telemedicine that protects patients' privacy while increasing security and performance. Covi-Chain uses “block-chain technology” to solve security and privacy problems while not exposing data and increasing storage capacity [28-31].
Data Management
Data management is the ability to get at, combine, control, and manage data information flow to make sense. There are numerous methods for providing computer programs with only the information they require while concealing other information. These methods include data anonymization, data integration, and data synchronization.
