Security and privacy issues in implantable medical devices: A comprehensive survey

Suitability of the Current Health Technology Assessment of Innovative Artificial Intelligence-Based Medical Devices: Scoping Literature Review

BACKGROUND

Artificial intelligence (AI)-based medical devices have garnered attention due to their ability to revolutionize medicine. Their health technology assessment framework is lacking.

OBJECTIVE

This study aims to analyze the suitability of each health technology assessment (HTA) domain for the assessment of AI-based medical devices.

METHODS

We conducted a scoping literature review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. We searched databases (PubMed, Embase, and Cochrane Library), gray literature, and HTA agency websites.

RESULTS

A total of 10.1% (78/775) of the references were included. Data quality and integration are vital aspects to consider when describing and assessing the technical characteristics of AI-based medical devices during an HTA process. When it comes to implementing specialized HTA for AI-based medical devices, several practical challenges and potential barriers could be highlighted and should be taken into account (AI technological evolution timeline, data requirements, complexity and transparency, clinical validation and safety requirements, regulatory and ethical considerations, and economic evaluation).

CONCLUSIONS

The adaptation of the HTA process through a methodological framework for AI-based medical devices enhances the comparability of results across different evaluations and jurisdictions. By defining the necessary expertise, the framework supports the development of a skilled workforce capable of conducting robust and reliable HTAs of AI-based medical devices. A comprehensive adapted HTA framework for AI-based medical devices can provide valuable insights into the effectiveness, cost-effectiveness, and societal impact of AI-based medical devices, guiding their responsible implementation and maximizing their benefits for patients and health care systems.

Miniaturized therapeutic systems for ultrasound-modulated drug delivery to the central and peripheral nervous system

Ultrasound is a promising technology to address challenges in drug delivery, including limited drug penetration across physiological barriers and ineffective targeting. Here we provide an overview of the significant advances made in recent years in overcoming technical and pharmacological barriers using ultrasound-assisted drug delivery to the central and peripheral nervous system. We commence by exploring the fundamental principles of ultrasound physics and its interaction with tissue. The mechanisms of ultrasonic-enhanced drug delivery are examined, as well as the relevant tissue barriers. We highlight drug transport through such tissue barriers utilizing insonation alone, in combination with ultrasound contrast agents (e.g., microbubbles), and through innovative particulate drug delivery systems. Furthermore, we review advances in systems and devices for providing therapeutic ultrasound, as their practicality and accessibility are crucial for clinical application.

Patient informed consent, ethical and legal considerations in the context of digital vulnerability with smart, cardiac implantable electronic devices

Advancements in digitalisation with cardiac implantable electronic devices (CIEDs) allow patients opportunities for improved autonomy, quality of life, and a potential increase in life expectancy. However, with the digital and functional practicalities of CIEDs, there exists also cyber safety issues with transferring wireless information. If a digital network were to be hacked, a CIED patient could experience both the loss of sensitive data and the loss of functional control of the CIED due to an unwelcome party. Moreover, if a CIED patient were to become victim of a cyber attack, which resulted in a serious or lethal event, and if this information were to become public, the trust in healthcare would be impacted and legal consequences could result. A cyber attack therefore poses not only a direct threat to the patient's health but also the confidentiality, integrity, and availability of the CIED, and these cyber threats could be considered "patient-targeted threats." Informed consent is a key component of ethical care, legally concordant practice, and promoting patient-as-partner therapeutic relationships [1]. To date, there are no standardised guidelines for listing cybersecurity risks within the informed consent or for discussing them during the consent process. Providers are responsible for adhering to the ethical principles of autonomy, beneficence, non-maleficence, and justice, both in medical practice generally and the informed consent process specifically. At present, the decision to include cybersecurity risks is mainly left to the provider's discretion, who may also have limited cyber risk information. Without effective and in-depth communication about all possible cybersecurity risks during the consent process, CIED patients can be left unaware of the privacy and physical risks they possess by carrying such a device. Therefore, cyber risk factors should be covered within the patients' informed consent and reviewed on an ongoing basis as new risk information becomes available. By including cyber risk information in the informed consent process, patients are given the autonomy to make the best-informed decision.

State of the science and recommendations for using wearable technology in sleep and circadian research

Wearable sleep-tracking technology is of growing use in the sleep and circadian fields, including for applications across other disciplines, inclusive of a variety of disease states. Patients increasingly present sleep data derived from their wearable devices to their providers and the ever-increasing availability of commercial devices and new-generation research/clinical tools has led to the wide adoption of wearables in research, which has become even more relevant given the discontinuation of the Philips Respironics Actiwatch. Standards for evaluating the performance of wearable sleep-tracking devices have been introduced and the available evidence suggests that consumer-grade devices exceed the performance of traditional actigraphy in assessing sleep as defined by polysomnogram. However, clear limitations exist, for example, the misclassification of wakefulness during the sleep period, problems with sleep tracking outside of the main sleep bout or nighttime period, artifacts, and unclear translation of performance to individuals with certain characteristics or comorbidities. This is of particular relevance when person-specific factors (like skin color or obesity) negatively impact sensor performance with the potential downstream impact of augmenting already existing healthcare disparities. However, wearable sleep-tracking technology holds great promise for our field, given features distinct from traditional actigraphy such as measurement of autonomic parameters, estimation of circadian features, and the potential to integrate other self-reported, objective, and passively recorded health indicators. Scientists face numerous decision points and barriers when incorporating traditional actigraphy, consumer-grade multi-sensor devices, or contemporary research/clinical-grade sleep trackers into their research. Considerations include wearable device capabilities and performance, target population and goals of the study, wearable device outputs and availability of raw and aggregate data, and data extraction, processing, and analysis. Given the difficulties in the implementation and utilization of wearable sleep-tracking technology in real-world research and clinical settings, the following State of the Science review requested by the Sleep Research Society aims to address the following questions. What data can wearable sleep-tracking devices provide? How accurate are these data? What should be taken into account when incorporating wearable sleep-tracking devices into research? These outstanding questions and surrounding considerations motivated this work, outlining practical recommendations for using wearable technology in sleep and circadian research.

Wireless Battery-free and Fully Implantable Organ Interfaces

Advances in soft materials, miniaturized electronics, sensors, stimulators, radios, and battery-free power supplies are resulting in a new generation of fully implantable organ interfaces that leverage volumetric reduction and soft mechanics by eliminating electrochemical power storage. This device class offers the ability to provide high-fidelity readouts of physiological processes, enables stimulation, and allows control over organs to realize new therapeutic and diagnostic paradigms. Driven by seamless integration with connected infrastructure, these devices enable personalized digital medicine. Key to advances are carefully designed material, electrophysical, electrochemical, and electromagnetic systems that form implantables with mechanical properties closely matched to the target organ to deliver functionality that supports high-fidelity sensors and stimulators. The elimination of electrochemical power supplies enables control over device operation, anywhere from acute, to lifetimes matching the target subject with physical dimensions that supports imperceptible operation. This review provides a comprehensive overview of the basic building blocks of battery-free organ interfaces and related topics such as implantation, delivery, sterilization, and user acceptance. State of the art examples categorized by organ system and an outlook of interconnection and advanced strategies for computation leveraging the consistent power influx to elevate functionality of this device class over current battery-powered strategies is highlighted.

Access Control, Key Management, and Trust for Emerging Wireless Body Area Networks

Wireless Body Area Networks (WBANs) are an emerging industrial technology for monitoring physiological data. These networks employ medical wearable and implanted biomedical sensors aimed at improving quality of life by providing body-oriented services through a variety of industrial sensing gadgets. The sensors collect vital data from the body and forward this information to other nodes for further services using short-range wireless communication technology. In this paper, we provide a multi-aspect review of recent advancements made in this field pertaining to cross-domain security, privacy, and trust issues. The aim is to present an overall review of WBAN research and projects based on applications, devices, and communication architecture. We examine current issues and challenges with WBAN communications and technologies, with the aim of providing insights for a future vision of remote healthcare systems. We specifically address the potential and shortcomings of various Wireless Body Area Network (WBAN) architectures and communication schemes that are proposed to maintain security, privacy, and trust within digital healthcare systems. Although current solutions and schemes aim to provide some level of security, several serious challenges remain that need to be understood and addressed. Our aim is to suggest future research directions for establishing best practices in protecting healthcare data. This includes monitoring, access control, key management, and trust management. The distinguishing feature of this survey is the combination of our review with a critical perspective on the future of WBANs.

Organic Electronics in Biosensing: A Promising Frontier for Medical and Environmental Applications

The promising field of organic electronics has ushered in a new era of biosensing technology, thus offering a promising frontier for applications in both medical diagnostics and environmental monitoring. This review paper provides a comprehensive overview of organic electronics' remarkable progress and potential in biosensing applications. It explores the multifaceted aspects of organic materials and devices, thereby highlighting their unique advantages, such as flexibility, biocompatibility, and low-cost fabrication. The paper delves into the diverse range of biosensors enabled by organic electronics, including electrochemical, optical, piezoelectric, and thermal sensors, thus showcasing their versatility in detecting biomolecules, pathogens, and environmental pollutants. Furthermore, integrating organic biosensors into wearable devices and the Internet of Things (IoT) ecosystem is discussed, wherein they offer real-time, remote, and personalized monitoring solutions. The review also addresses the current challenges and future prospects of organic biosensing, thus emphasizing the potential for breakthroughs in personalized medicine, environmental sustainability, and the advancement of human health and well-being.

Current state of the art and future directions for implantable sensors in medical technology: Clinical needs and engineering challenges

Implantable sensors have revolutionized the way we monitor biophysical and biochemical parameters by enabling real-time closed-loop intervention or therapy. These technologies align with the new era of healthcare known as healthcare 5.0, which encompasses smart disease control and detection, virtual care, intelligent health management, smart monitoring, and decision-making. This review explores the diverse biomedical applications of implantable temperature, mechanical, electrophysiological, optical, and electrochemical sensors. We delve into the engineering principles that serve as the foundation for their development. We also address the challenges faced by researchers and designers in bridging the gap between implantable sensor research and their clinical adoption by emphasizing the importance of careful consideration of clinical requirements and engineering challenges. We highlight the need for future research to explore issues such as long-term performance, biocompatibility, and power sources, as well as the potential for implantable sensors to transform healthcare across multiple disciplines. It is evident that implantable sensors have immense potential in the field of medical technology. However, the gap between research and clinical adoption remains wide, and there are still major obstacles to overcome before they can become a widely adopted part of medical practice.

Patient-centered empirical research on ethically relevant psychosocial and cultural aspects of cochlear, glaucoma and cardiovascular implants - a scoping review

BACKGROUND

The significance of medical implants goes beyond technical functioning and reaches into everyday life, with consequences for individuals as well as society. Ethical aspects associated with the everyday use of implants are relevant for individuals' lifeworlds and need to be considered in implant care and in the course of technical developments.

METHODS

This scoping review aimed to provide a synthesis of the existing evidence regarding ethically relevant psychosocial and cultural aspects in cochlear, glaucoma and cardiovascular implants in patient-centered empirical research. Systematic literature searches were conducted in EBSCOhost, Philpapers, PsycNET, Pubmed, Web of Science and BELIT databases. Eligible studies were articles in German or English language published since 2000 dealing with ethically relevant aspects of cochlear, glaucoma and passive cardiovascular implants based on empirical findings from the perspective of (prospective) implant-wearers and their significant others. Following a descriptive-analytical approach, a data extraction form was developed and relevant data were extracted accordingly. We combined a basic numerical analysis of study characteristics with a thematically organized narrative synthesis of the data.

RESULTS

Sixty-nine studies were included in the present analysis. Fifty were in the field of cochlear implants, sixteen in the field of passive cardiovascular implants and three in the field of glaucoma implants. Implant-related aspects were mainly found in connection with autonomy, freedom, identity, participation and justice, whereas little to no data was found with regards to ethical principles of privacy, safety or sustainability.

CONCLUSIONS

Empirical research on ethical aspects of implant use in everyday life is highly relevant, but marked by ambiguity and unclarity in the operationalization of ethical terms and contextualization. A transparent orientation framework for the exploration and acknowledgment of ethical aspects in "lived experiences" may contribute to the improvement of individual care, healthcare programs and research quality in this area. Ethics-sensitive care requires creating awareness for cultural and identity-related issues, promoting health literacy to strengthen patient autonomy as well as adjusting healthcare programs accordingly. More consideration needs to be given to sustainability issues in implant development and care according to an approach of ethics-by-design.

NFC-Powered Implantable Device for On-Body Parameters Monitoring With Secure Data Exchange Link to a Medical Blockchain Type of Network

Implantable devices represent the future of remote medical monitoring and administration of both chemical and physical therapies to the patients. Although some of these devices are already in the market, the security mechanisms deployed inside them to withstand deliberate external influence are still decades away from the robust digital data security schemes employed in modern distributed networks these days. Medical data theft, spoofing, and disclosure pose serious threats that can ultimately lead to individual and social stigmas or even death. In this article, we present a small-form and batteryless implantable device with acquisition channels for biopotential (30-dB gain and 16-Hz bandwidth), arterial pulse oximetry, and temperature (0.12°C accuracy) recordings, suitable for cardiovascular, neuronal, and endocrine parameters assessment. The proposed device is powered by the near-field communication (NFC) interface with an external mobile phone, with a power consumption of 0.9 mW and achieving the full operation for distances close to 1 cm under the skin. In situ encryption of the acquired physiological signals is performed by a lightweight and short-term symmetric-key distribution scheme with data stream hopping, in order to ensure secure data transference over the air between the patient and trusted entities only, complemented by data storage, processing, and recovery through a medical blockchain type of network that involves the main stakeholders inside a medical community.

When brain devices go wrong: a patient with a malfunctioning deep brain stimulator (DBS) presents to the emergency department

A man in his 50s attended the emergency department with an acute deterioration in his Parkinson's symptoms, presenting with limb rigidity, widespread tremor, choreiform dyskinesia, dysarthria, intense sadness and a severe occipital headache. After excluding common differentials for sudden-onset parkinsonism (eg, infection, medication change), an error on the patient's deep brain stimulator was noted. The patient's symptoms only resolved once he was transferred to the specialist centre so that the programmer could reset the device settings. Due to COVID-19-related bed pressures on the ward, there was a delay in the patient receiving specialist attention-highlighting the need for non-specialist training in the emergency management of device errors.

Implants with Sensing Capabilities

Because of the aging human population and increased numbers of surgical procedures being performed, there is a growing number of biomedical devices being implanted each year. Although the benefits of implants are significant, there are risks to having foreign materials in the body that may lead to complications that may remain undetectable until a time at which the damage done becomes irreversible. To address this challenge, advances in implantable sensors may enable early detection of even minor changes in the implants or the surrounding tissues and provide early cues for intervention. Therefore, integrating sensors with implants will enable real-time monitoring and lead to improvements in implant function. Sensor integration has been mostly applied to cardiovascular, neural, and orthopedic implants, and advances in combined implant-sensor devices have been significant, yet there are needs still to be addressed. Sensor-integrating implants are still in their infancy; however, some have already made it to the clinic. With an interdisciplinary approach, these sensor-integrating devices will become more efficient, providing clear paths to clinical translation in the future.

On the Design of Secured and Reliable Dynamic Access Control Scheme of Patient E-Healthcare Records in Cloud Environment

Traditional healthcare services have changed into modern ones in which doctors can diagnose patients from a distance. All stakeholders, including patients, ward boy, life insurance agents, physicians, and others, have easy access to patients' medical records due to cloud computing. The cloud's services are very cost-effective and scalable, and provide various mobile access options for a patient's electronic health records (EHRs). EHR privacy and security are critical concerns despite the many benefits of the cloud. Patient health information is extremely sensitive and important, and sending it over an unencrypted wireless media raises a number of security hazards. This study suggests an innovative and secure access system for cloud-based electronic healthcare services storing patient health records in a third-party cloud service provider. The research considers the remote healthcare requirements for maintaining patient information integrity, confidentiality, and security. There will be fewer attacks on e-healthcare records now that stakeholders will have a safe interface and data on the cloud will not be accessible to them. End-to-end encryption is ensured by using multiple keys generated by the key conclusion function (KCF), and access to cloud services is granted based on a person's identity and the relationship between the parties involved, which protects their personal information that is the methodology used in the proposed scheme. The proposed scheme is best suited for cloud-based e-healthcare services because of its simplicity and robustness. Using different Amazon EC2 hosting options, we examine how well our cloud-based web application service works when the number of requests linearly increases. The performance of our web application service that runs in the cloud is based on how many requests it can handle per second while keeping its response time constant. The proposed secure access scheme for cloud-based web applications was compared to the Ethereum blockchain platform, which uses internet of things (IoT) devices in terms of execution time, throughput, and latency.

Hospital cybersecurity risks and gaps: Review (for the non-cyber professional)

Background

Healthcare is facing a growing threat of cyberattacks. Myriad data sources illustrate the same trends that healthcare is one of the industries with the highest risk of cyber infiltration and is seeing a surge in security incidents within just a few years. The circumstances thus begged the question: are US hospitals prepared for the risks that accompany clinical medicine in cyberspace?

Objective

The study aimed to identify the major topics and concerns present in today's hospital cybersecurity field, intended for non-cyber professionals working in hospital settings.

Methods

Via structured literature searches of the National Institutes of Health's PubMed and Tel Aviv University's DaTa databases, 35 journal articles were identified to form the core of the study. Databases were chosen for accessibility and academic rigor. Eighty-seven additional sources were examined to supplement the findings.

Results

The review revealed a basic landscape of hospital cybersecurity, including primary reasons hospitals are frequent targets, top attack methods, and consequences hospitals face following attacks. Cyber technologies common in healthcare and their risks were examined, including medical devices, telemedicine software, and electronic data. By infiltrating any of these components of clinical care, attackers can access mounds of information and manipulate, steal, ransom, or otherwise compromise the records, or can use the access to catapult themselves to deeper parts of a hospital's network. Issues that can increase healthcare cyber risks, like interoperability and constant accessibility, were also identified. Finally, strategies that hospitals tend to employ to combat these risks, including technical, financial, and regulatory, were explored and found to be weak. There exist serious vulnerabilities within hospitals' technologies that many hospitals presently fail to address. The COVID-19 pandemic was used to further illustrate this issue.

Conclusions

Comparison of the risks, strategies, and gaps revealed that many US hospitals are unprepared for cyberattacks. Efforts are largely misdirected, with external-often governmental-efforts negligible. Policy changes, e.g., training employees in cyber protocols, adding advanced technical protections, and collaborating with several experts, are necessary. Overall, hospitals must recognize that, in cyber incidents, the real victims are the patients. They are at risk physically and digitally when medical devices or treatments are compromised.

PUFchain 2.0: Hardware-Assisted Robust Blockchain for Sustainable Simultaneous Device and Data Security in Smart Healthcare

This article presents the first-ever hardware-assisted blockchain for simultaneously handling device and data security in smart healthcare. This article presents the hardware security primitive physical unclonable functions (PUF) and blockchain technology together as PUFchain 2.0 with a two-level authentication mechanism. The proposed PUFchain 2.0 security primitive presents a scalable approach by allowing Internet of Medical Things (IoMT) devices to connect and obtain PUF keys from the edge server with an embedded PUF module instead of connecting a PUF module to each device. The PUF key, once assigned to a particular media access control (MAC) address by the miner, will be unique for that MAC address and cannot be assigned to other devices. PUFs are developed based on internal micro-manufacturing process variations during chip fabrication. This property of PUFs is integrated with blockchain by including the PUF key of the IoMT into blockchain for authentication. The robustness of the proposed Proof of PUF-Enabled authentication consensus mechanism in PUFchain 2.0 has been substantiated through test bed evaluation. Arbiter PUFs have been used for the experimental validation of PUFchain 2.0. From the obtained 200 PUF keys, 75% are reliable and the Hamming distance of the PUF module is 48%. Obtained database outputs along with other metrics have been presented for validating the potential of PUFchain 2.0 in smart healthcare.

An Overview of Medical Electronic Hardware Security and Emerging Solutions

Electronic healthcare technology is widespread around the world and creates massive potential to improve clinical outcomes and transform care delivery. However, there are increasing concerns with respect to the cyber vulnerabilities of medical tools, malicious medical errors, and security attacks on healthcare data and devices. Increased connectivity to existing computer networks has exposed the medical devices/systems and their communicating data to new cybersecurity vulnerabilities. Adversaries leverage the state-of-the-art technologies, in particular artificial intelligence and computer vision-based techniques, in order to launch stronger and more detrimental attacks on the medical targets. The medical domain is an attractive area for cybercrimes for two fundamental reasons: (a) it is rich resource of valuable and sensitive data; and (b) its protection and defensive mechanisms are weak and ineffective. The attacks aim to steal health information from the patients, manipulate the medical information and queries, maliciously change the medical diagnosis, decisions, and prescriptions, etc. A successful attack in the medical domain causes serious damage to the patient’s health and even death. Therefore, cybersecurity is critical to patient safety and every aspect of the medical domain, while it has not been studied sufficiently. To tackle this problem, new human- and computer-based countermeasures are researched and proposed for medical attacks using the most effective software and hardware technologies, such as artificial intelligence and computer vision. This review provides insights to the novel and existing solutions in the literature that mitigate cyber risks, errors, damage, and threats in the medical domain. We have performed a scoping review analyzing the four major elements in this area (in order from a medical perspective): (1) medical errors; (2) security weaknesses of medical devices at software- and hardware-level; (3) artificial intelligence and/or computer vision in medical applications; and (4) cyber attacks and defenses in the medical domain. Meanwhile, artificial intelligence and computer vision are key topics in this review and their usage in all these four elements are discussed. The review outcome delivers the solutions through building and evaluating the connections among these elements in order to serve as a beneficial guideline for medical electronic hardware security.

A comprehensive review on metallic implant biomaterials and their subtractive manufacturing

There is a tremendous increase in the demand for converting biomaterials into high-quality industrially manufactured human body parts, also known as medical implants. Drug delivery systems, bone plates, screws, cranial, and dental devices are the popular examples of these implants - the potential alternatives for human life survival. However, the processing techniques of an engineered implant largely determine its preciseness, surface characteristics, and interactive ability with the adjacent tissue(s) in a particular biological environment. Moreover, the high cost-effective manufacturing of an implant under tight tolerances remains a challenge. In this regard, several subtractive or additive manufacturing techniques are employed to manufacture patient-specific implants, depending primarily on the required biocompatibility, bioactivity, surface integrity, and fatigue strength. The present paper reviews numerous non-degradable and degradable metallic implant biomaterials such as stainless steel (SS), titanium (Ti)-based, cobalt (Co)-based, nickel-titanium (NiTi), and magnesium (Mg)-based alloys, followed by their processing via traditional turning, drilling, and milling including the high-speed multi-axis CNC machining, and non-traditional  abrasive water jet machining (AWJM), laser beam machining (LBM), ultrasonic machining (USM), and electric discharge machining (EDM) types of subtractive manufacturing techniques. However, the review further funnels down its primary focus on Mg, NiTi, and Ti-based alloys on the basis of the increasing trend of their implant applications in the last decade due to some of their outstanding properties. In the recent years, the incorporation of cryogenic coolant-assisted traditional subtraction of biomaterials has gained researchers' attention due to its sustainability, environment-friendly nature, performance, and superior biocompatible and functional outcomes fitting for medical applications. However, some of the latest studies reported that the medical implant manufacturing requirements could be more remarkably met using the non-traditional subtractive manufacturing approaches. Altogether, cryogenic  machining among the traditional routes and EDM among the non-traditional means along with their variants, were identified as some of the most effective subtractive manufacturing techniques for achieving the dimensionally accurate and biocompatible metallic medical implants with significantly modified surfaces.

Intelligent Telehealth in Pharmacovigilance: A Future Perspective

Pharmacovigilance improves patient safety by detecting and preventing adverse drug events. However, challenges exist that limit adverse drug event detection, resulting in many adverse drug events being underreported or inaccurately reported. One challenge includes having access to large data sets from various sources including electronic health records and wearable medical devices. Artificial intelligence, including machine learning methods, such as natural language processing and deep learning, can detect and extract information about adverse drug events, thus automating the pharmacovigilance process and improving the surveillance of known and documented adverse drug events. In addition, with the increased demand for telehealth services, for managing both acute and chronic diseases, artificial intelligence methods can play a role in detecting and preventing adverse drug events. In this review, we discuss two use cases of how artificial intelligence methods may be useful to improve the quality of pharmacovigilance and the role of artificial intelligence in telehealth practices.

Can Formal Security Verification Really Be Optional? Scrutinizing the Security of IMD Authentication Protocols

The need for continuous monitoring of physiological information of critical organs of the human body, combined with the ever-growing field of electronics and sensor technologies and the vast opportunities brought by 5G connectivity, have made implantable medical devices (IMDs) the most necessitated devices in the health arena. IMDs are very sensitive since they are implanted in the human body, and the patients depend on them for the proper functioning of their vital organs. Simultaneously, they are intrinsically vulnerable to several attacks mainly due to their resource limitations and the wireless channel utilized for data transmission. Hence, failing to secure them would put the patient's life in jeopardy and damage the reputations of the manufacturers. To date, various researchers have proposed different countermeasures to keep the confidentiality, integrity, and availability of IMD systems with privacy and safety specifications. Despite the appreciated efforts made by the research community, there are issues with these proposed solutions. Principally, there are at least three critical problems. (1) Inadequate essential capabilities (such as emergency authentication, key update mechanism, anonymity, and adaptability); (2) heavy computational and communication overheads; and (3) lack of rigorous formal security verification. Motivated by this, we have thoroughly analyzed the current IMD authentication protocols by utilizing two formal approaches: the Burrows-Abadi-Needham logic (BAN logic) and the Automated Validation of Internet Security Protocols and Applications (AVISPA). In addition, we compared these schemes against their security strengths, computational overheads, latency, and other vital features, such as emergency authentications, key update mechanisms, and adaptabilities.

A novel IoT sensor authentication using HaLo extraction method and memory chip variability

Since the inception of encrypted messages thousands of years ago, mathematicians and scientists have continued to improve encryption algorithms in order to create more secure means of communication. These improvements came by means of more complex encryption algorithms that have stronger security features such as larger keys and trusted third parties. While many new processors can handle these more complex encryption algorithms, IoT devices on the edge often struggle to keep up with resource intensive encryption standards. In order to meet this demand for lightweight, secure encryption on the edge, this paper proposes a novel solution, called the High and Low (HaLo) method, that generates Physical Unclonable Function (PUF) signatures based on process variations within flash memory. These PUF signatures can be used to uniquely identify and authenticate remote sensors, and help ensure that messages being sent from remote sensors are encrypted adequately without requiring computationally expensive methods. The HaLo method consumes 20x less power than conventional authentication schemes commonly used with IoT devices, it has an average latency of only 39ms for 512 bit signature generation, and the average error rate is below 0.06%. Due to its low latency, low error rate, and high power efficiency, the HaLo method can progress the field of IoT encryption standards by accurately and efficiently authenticating remote sensors without sacrificing encryption integrity.

Cardio-ML: Detection of malicious clinical programmings aimed at cardiac implantable electronic devices based on machine learning and a missing values resemblance framework

Patients with life-threatening arrhythmias are often treated with cardiac implantable electronic devices (CIEDs), such as pacemakers and implantable cardioverter defibrillators (ICDs). Recent advancements in CIEDs have enabled advanced functionality and connectivity that make such devices (particularly ICDs) vulnerable to cyber-attacks. One of the most dangerous attacks on CIED ecosystems is a data manipulation attack from a compromised programmer device that sends malicious clinical programmings to the CIED. Such attacks can affect the CIED functioning and impact patient's survival and quality of life. In this paper, we propose Cardio-ML - an automated system for the detection of malicious clinical programmings that is based on machine learning algorithms and a novel missing values resemblance framework. Our system is designed to detect new variants of existing attacks and, more importantly, new unknown (zero-day) attacks, aimed at ICDs. We collected 1651 legitimate clinical programmings from 514 patients, over a four-year period, from programmer devices at two medical centers. Our collection also includes 28 core malicious functionalities created by cardiac electrophysiology experts that were later used to create different variants of malicious programmings. Cardio-ML was evaluated extensively in three comprehensive experiments and showed high detection capabilities in most attack scenarios. We achieved perfect classification results for detecting newly created variants of existing core malicious functionalities, with an AUC of 100%; for completely new unknown (zero-day) malicious clinical programmings, an AUC of 80% was obtained, which is 14% better than the state-of-the-art method. We were able to further improve our detection results by identifying the best combination of legitimate and zero-day malicious programmings in the dataset, achieving an AUC of 87%. CIED clinical programmings have many parameters without values for a large number of samples (programmings). To cope with the extreme amount of missing values in our dataset, we developed a novel missing values-based resemblance framework and evaluated it using three dataset-creation approaches: a standard expert-driven approach, our novel data-driven approach, and a combined approach incorporating both approaches. The results showed that our novel framework handles missing values in the data better than the expert-driven approach which yields an empty dataset. In particular, the combined approach showed a 40% improvement in data utilization compared to the data-driven approach.

Securing Bio-Cyber Interface for the Internet of Bio-Nano Things using Particle Swarm Optimization and Artificial Neural Networks based parameter profiling

Internet of bio-nano things (IoBNT) is a novel communication paradigm where tiny, biocompatible and non-intrusive devices collect and sense biological signals from the environment and send them to data centers for processing through the internet. The concept of the IoBNT has stemmed from the combination of synthetic biology and nanotechnology tools which enable the fabrication of biological computing devices called Bio-nano things. Bio-nano things are nanoscale (1-100 nm) devices that are ideal for in vivo applications, where non-intrusive devices can reach hard-to-access areas of the human body (such as deep inside the tissue) to collect biological information. Bio-nano things work collaboratively in the form of a network called nanonetwork. The interconnection of the biological world and the cyber world of the Internet is made possible by a powerful hybrid device called Bio Cyber Interface. Bio Cyber Interface translates biochemical signals from in-body nanonetworks into electromagnetic signals and vice versa. Bio Cyber Interface can be designed using several technologies. In this paper, we have selected bio field-effect transistor (BioFET) technology, due to its characteristics of being fast, low-cost, and simple The main concern in this work is the security of IoBNT, which must be the preliminary requirement, especially for healthcare applications of IoBNT. Once the human body is accessible through the Internet, there is always a chance that it will be done with malicious intent. To address the issue of security in IoBNT, we propose a framework that utilizes Particle Swarm Optimization (PSO) algorithm to optimize Artificial Neural Networks (ANN) and to detect anomalous activities in the IoBNT transmission. Our proposed PSO-based ANN model was tested for the simulated dataset of BioFET based Bio Cyber Interface communication features. The results show an improved accuracy of 98.9% when compared with Adam based optimization function.

A robust and lightweight secure access scheme for cloud based E-healthcare services

Traditional healthcare services have transitioned into modern healthcare services where doctors remotely diagnose the patients. Cloud computing plays a significant role in this change by providing easy access to patients' medical records to all stakeholders, such as doctors, nurses, patients, life insurance agents, etc. Cloud services are scalable, cost-effective, and offer a broad range of mobile access to patients' electronic health record (EHR). Despite the cloud's enormous benefits like real-time data access, patients' EHR security and privacy are major concerns. Since the information about patients' health is highly sensitive and crucial, sharing it over the unsecured wireless medium brings many security challenges such as eavesdropping, modifications, etc. Considering the security needs of remote healthcare, this paper proposes a robust and lightweight, secure access scheme for cloud-based E-healthcare services. The proposed scheme addresses the potential threats to E-healthcare by providing a secure interface to stakeholders and prohibiting unauthorized users from accessing information stored in the cloud. The scheme makes use of multiple keys formed through the key derivation function (KDF) to ensure end-to-end ciphering of information for preventing misuse. The rights to access the cloud services are provided based on the identity and the association between stakeholders, thus ensuring privacy. Due to its simplicity and robustness, the proposed scheme is the best fit for protecting data security and privacy in cloud-based E-healthcare services.

Deep brain stimulation and electromagnetic interference

Deep brain stimulation (DBS) has evolved into an approved and efficacious treatment for movement, obsessive-compulsive, and epilepsy disorders that are refractory to medical therapy, with current investigation into other disease conditions. However, there are unintentional and intentional sources of external electromagnetic interference (EMI) that can lead to either malfunctioning or damaged DBS devices, as well as injury to human tissue. Comprehensive studies and guidelines on such topics in the medical literature are scarce. Herein, we review the principles behind EMI, as well as the various potential sources of interference, both unintentional (e.g. stray EMI fields) and intentional (e.g. MRI scans, "brainjacking"). Additionally, we employ the Manufacturer and User Device Facility Experience (MAUDE) database to assess real-world instances of EMI (e.g., airport body scanners, magnetic resonance imaging (MRI), and electrosurgery) affecting DBS devices commonly implanted in the United States (US).

Retrospective study in clinical governance and financing system impacts of the COVID-19 pandemic in the hand surgery and microsurgery HUB center

Introduction

The authors presented a retrospective study in the surgical activity of the HUB center for Hand Surgery and Microsurgery in Emilia-Romagna comparing the data between March and April 2020, in the peak of Covid pandemic, with the same period in 2019.

Materials and methods

During the two months period of March–April 2020 versus 2019 the authors analyzed the surgical procedures performed in elective and emergency surgery with hospitalization and Day or Outpatient surgery regime. Surgical treatments with no hospitalization were planned in the Day-Surgery Service. The financing system impacts were analyzed according to the Diagnosis Related Groups (DRG), the costs accounting method mostly used in European countries.

Results

An overall reduction of 68.5% was recorded in surgical procedures, with a more relevant reduction of 92.3% in elective surgery and a significantly less relevant reduction of 37.2% in urgent one. Replantation did not present a reduction in number of cases, while cutting lesions of tendons at the hand and fingers increased such as the bone and ligament injuries during domestic accidents. The negative impact in the financial system recorded a reduction of 32.5%.

Discussion

The epidemiology of hand trauma looks not only at the artisanal and industrial injuries, but also mostly at the accidents in daily life activities. The data of the study evidenced the significantly increase in the injuries occurring in the domestic environment. Elective surgery was canceled. The 86% of surgical procedures performed were urgent ones and the 72.8% of these were possible in Day and Outpatient surgery with significantly reduction in hospitalization. All procedures followed a rigid process for patient and healthcare workers with regard for personal protection and safety. Telemedicine was arranged in emergencies, and economic damage was analyzed also in the following rebound effect during summer period.

Conclusions

The significantly less reduction recorded in urgent surgery vs the more relevant reduction in elective one showed how the hand injuries remained a major issue also during the lockdown. The data highlighted the relevant role of the organizational aspects of the surgical procedures and planning in hand trauma. Despite the financial impact of the elective surgery, the presence of a functional and skill Emergency Service and Day-Surgery Service resulted fundamental in the efficacy and efficiency of the patient management and in containment of economic damage. The telemedicine was significantly limited by liability and risk management issues.

Enhancements of Loading Capacity and Moving Ability by Microstructures for Wireless Soft Robot Boats

Because of its promising applications in various fields such as in vivo drug treatment, in-pipe inspection, and so forth, there is an increasing interest on wireless soft robot boats taking advantages of their shape adaptability. The loading capacity and mobility, however, are always fundamental challenges to restrict their applications. In this study, a graphene-based soft robot boat, which could be programmable-driven by a remote near-infrared light, is proposed. Different microstructures underneath the boat are carefully designed and employed to improve both the loading capacity and the moving ability. It reveals that, compared to that without microstructures, the soft robot boat with square pillar arrays (120-160 μm of period, duty cycle, and aspect ratio at active Wenzel/Cassie transition point) could enhance the loading capacity by 12.75% and the moving velocity by 16.70%. For the robot boat with grating structures, a strong driving anisotropy is revealed, with an enhancement of 2.24% for the loading capacity and 34.65% for the driving response along the grating lines. A boat prototype with a self-weight of 6.05 g is finally developed and can achieve continuous navigation in a closed narrow space for in situ monitoring, which may find applications in the inspection of other narrow terrains (e.g., blood vessels).

An IoT-based framework for early identification and monitoring of COVID-19 cases

The world has been facing the challenge of COVID-19 since the end of 2019. It is expected that the world will need to battle the COVID-19 pandemic with precautious measures, until an effective vaccine is developed. This paper proposes a real-time COVID-19 detection and monitoring system. The proposed system would employ an Internet of Things (IoTs) framework to collect real-time symptom data from users to early identify suspected coronaviruses cases, to monitor the treatment response of those who have already recovered from the virus, and to understand the nature of the virus by collecting and analyzing relevant data. The framework consists of five main components: Symptom Data Collection and Uploading (using wearable sensors), Quarantine/Isolation Center, Data Analysis Center (that uses machine learning algorithms), Health Physicians, and Cloud Infrastructure. To quickly identify potential coronaviruses cases from this real-time symptom data, this work proposes eight machine learning algorithms, namely Support Vector Machine (SVM), Neural Network, Naïve Bayes, K-Nearest Neighbor (K-NN), Decision Table, Decision Stump, OneR, and ZeroR. An experiment was conducted to test these eight algorithms on a real COVID-19 symptom dataset, after selecting the relevant symptoms. The results show that five of these eight algorithms achieved an accuracy of more than 90 %. Based on these results we believe that real-time symptom data would allow these five algorithms to provide effective and accurate identification of potential cases of COVID-19, and the framework would then document the treatment response for each patient who has contracted the virus.

The Telematic solutions in plastic surgery during COVID-19 pandemic

During the COVID-19 pandemic, surgical elective procedures were stopped in our plastic surgery unit. Limitations for consultations and for follow-up of previous surgical procedures were imposed in order to minimize the risk of contagion in waiting rooms and outpatient clinics. We have identified telemedicine as an alternative way to follow patients during the lockdown. Nevertheless, we have experienced different difficulties. We have not had the possibility to use a secure teleconferencing software. In our unit we had not technological devices. Surgeons in our department were not able to use remote video technology for patient management. Guidelines for an appropriate selection of patients which could be served via telemedicine had to be created. Telemedicine must be regulated by healthcare organizations for legal, ethical, medico-legal and risk management aspects. Even if we have experienced an important need to use telematic solutions during the COVID-19 lockdown, liability and risk management issues has greatly limited this possibility in our unit. The need of telemedicine in the time of COVID-19 pandemic has encouraged us to implement future virtual encounters in order to reduce unnecessary in-person visits by taking into consideration all legal, ethical and medico-legal aspects.

Emerging Wireless Sensor Networks and Internet of Things Technologies-Foundations of Smart Healthcare

Future smart healthcare systems - often referred to as Internet of Medical Things (IoMT) - will combine a plethora of wireless devices and applications that use wireless communication technologies to enable the exchange of healthcare data. Smart healthcare requires sufficient bandwidth, reliable and secure communication links, energy-efficient operations, and Quality of Service (QoS) support. The integration of Internet of Things (IoT) solutions into healthcare systems can significantly increase intelligence, flexibility, and interoperability. This work provides an extensive survey on emerging IoT communication standards and technologies suitable for smart healthcare applications. A particular emphasis has been given to low-power wireless technologies as a key enabler for energy-efficient IoT-based healthcare systems. Major challenges in privacy and security are also discussed. A particular attention is devoted to crowdsourcing/crowdsensing, envisaged as tools for the rapid collection of massive quantities of medical data. Finally, open research challenges and future perspectives of IoMT are presented.

Risk management-based security evaluation model for telemedicine systems

Background

Infectious diseases that can cause epidemics, such as COVID-19, SARS-CoV, and MERS-CoV, constitute a major social issue, with healthcare providers fearing secondary, tertiary, and even quaternary infections. To alleviate this problem, telemedicine is increasingly being viewed as an effective means through which patients can be diagnosed and medications prescribed by doctors via untact Thus, concomitant with developments in information and communication technology (ICT), medical institutions have actively analyzed and applied ICT to medical systems to provide optimal medical services. However, with the convergence of these diverse technologies, various risks and security threats have emerged. To protect patients and improve telemedicine quality for patient safety, it is necessary to analyze these risks and security threats comprehensively and institute appropriate countermeasures.

Methods

The security threats likely to be encountered in each of seven telemedicine service areas were analyzed, and related data were collected directly through on-site surveys by a medical institution. Subsequently, an attack tree, the most popular reliability and risk modeling approach for systematically characterizing the potential risks of telemedicine systems, was examined and utilized with the attack occurrence probability and attack success probability as variables to provide a comprehensive risk assessment method.

Results

In this study, the most popular modelling method, an attack tree, was applied to the telemedicine environment, and the security concerns for telemedicine systems were found to be very large. Risk management and evaluation methods suitable for the telemedicine environment were identified, and their benefits and potential limitations were assessed.

Conclusion

This research should be beneficial to security experts who wish to investigate the impacts of cybersecurity threats on remote healthcare and researchers who wish to identify new modeling opportunities to apply security risk modeling techniques.

Secure Processing of Stream Cipher Encrypted Data Issued from IOT: Application to a Connected Knee Prosthesis

In this paper, we propose a secure protocol that allows processing encrypted data emitted by a medical IOT device. Its originality stands on a new fast algorithm which makes possible the conversion of Combined Linear Congruential Generator (CLCG) encrypted data into data homomorphically encrypted with the Damgard-Jurik (D-J) cryptosystem. By doing so, an honest-but-curious third party, like a smartphone, can process data issued from the IOT devices (e.g. raising a health alert) without endangering data privacy while CLCG can be integrated in an IOT of low computation capabilities. Moreover, in order to reduce communication and computation complexities compared to existing solutions and to achieve a real time solution, we further propose a secure packed version of CLCG in the D-J domain. With it a medical IOT can encrypt several pieces of data at once while allowing a third party to independently convert and process them in their D-J homomorphic encrypted form. We theoretically and experimentally demonstrate the performance of our solution in the case of a connected knee prosthesis, the data of which are processed for patient monitoring.

Cyber Attacks on Healthcare Devices Using Unmanned Aerial Vehicles

The growing use of wireless technology in healthcare systems and devices makes these systems particularly open to cyber-based attacks, including denial of service and information theft via sniffing (eaves-dropping) and phishing attacks. Evolving technology enables wireless healthcare systems to communicate over longer ranges, which opens them up to greater numbers of possible threats. Unmanned aerial vehicles (UAV) or drones present a new and evolving attack surface for compromising wireless healthcare systems. An enumeration of the types of wireless attacks capable via drones are presented, including two new types of cyber threats: a stepping stone attack and a cloud-enabled attack. A real UAV is developed to test and demonstrate the vulnerabilities of healthcare systems to this new threat vector. The UAV successfully attacked a simulated smart hospital environment and also a small collection of wearable healthcare sensors. Compromise of wearable or implanted medical devices can lead to increased morbidity and mortality.

Evaluation of Secrecy Capacity for Next-Generation Leadless Cardiac Pacemakers

Secure communication can be considered as an integral part of the next generation implantable medical devices. With the advent of Physical Layer Security (PLS) methods, confidential messages can be transmitted without the use of encryption keys. For analyzing the effectiveness of PLS for next-generation leadless cardiac pacemakers, we provide secrecy analysis using a performance metric of secrecy capacity. Secrecy capacity defines the secure transmission rate between legitimate nodes without leakage of information to an eavesdropper and depends on respective channel attenuations. The legitimate and eavesdropper channel attenuations are evaluated by 3D numerical electromagnetic simulations using a detailed human model. We do not assume eavesdropper to be located in specific directions or positions and considers it to be located anywhere around the body. We evaluate the secrecy capacity by defining a spherical grid for eavesdropper positions around the body with a radius of 1 m. The secrecy capacity of the entire space is evaluated by extrapolating the grid to different radial distances using free space path loss model. Moreover, by fixing application based secure communication rate, the entire space is divided into secure and in-secure volumes. The in-secure volume consists of all the eavesdropper positions from which the pacemaker can be eavesdropped. We also evaluated the angle from which the maximum leakage of information takes place and referred it as "Eve's sweet spot angle." Data for channel attenuations from phantom and in-vivo experiments is also utilized to validate and observe the differences between simulations and experiments. This article will help in design of the communication module of implanted leadless cardiac pacemakers with enhanced security on the physical layer.

The Future of Cardiovascular Stents: Bioresorbable and Integrated Biosensor Technology

Cardiovascular disease is the greatest cause of death worldwide. Atherosclerosis is the underlying pathology responsible for two thirds of these deaths. It is the age-dependent process of "furring of the arteries." In many scenarios the disease is caused by poor diet, high blood pressure, and genetic risk factors, and is exacerbated by obesity, diabetes, and sedentary lifestyle. Current pharmacological anti-atherosclerotic modalities still fail to control the disease and improvements in clinical interventions are urgently required. Blocked atherosclerotic arteries are routinely treated in hospitals with an expandable metal stent. However, stented vessels are often silently re-blocked by developing "in-stent restenosis," a wound response, in which the vessel's lumen renarrows by excess proliferation of vascular smooth muscle cells, termed hyperplasia. Herein, the current stent technology and the future of biosensing devices to overcome in-stent restenosis are reviewed. Second, with advances in nanofabrication, new sensing methods and how researchers are investigating ways to integrate biosensors within stents are highlighted. The future of implantable medical devices in the context of the emerging "Internet of Things" and how this will significantly influence future biosensor technology for future generations are also discussed.

Keep an eye on your personal belongings! The security of personal medical devices and their ecosystems

Today, personal medical devices (PMDs) play an increasingly important role in healthcare ecosystems as patient life support equipment. As a result of technological advances, PMDs now encompass many components and functionalities that open the door to a variety of cyber-attacks. In this paper we present a taxonomy of ten widely-used PMDs based on the five diseases they were designed to treat. We also provide a comprehensive survey that covers 17 possible attacks aimed at PMDs, as well as the attacks' building blocks. For each PMD type, we create an ecosystem and data and attack flow diagram, which comprehensively describes the roles and interactions of the players associated with the PMD and presents the most vulnerable vectors and components within the PMDs' ecosystems; such knowledge can increase security awareness among PMD users and their healthcare providers. We also present the basic, yet important, building blocks that constitute the steps by which each of the attacks presented is carried out. Doing so allowed us to establish the foundations for the future development of a novel risk analysis methodology for medical devices. For each attack we mapped the building blocks required to carry out the attack and found that 50% of the attacks rely upon the ability to remotely connect to the PMD, while 61% of them rely on the physical proximity of the attacker to the PMD. Finally, by surveying 21 existing security mechanisms and mapping their coverage for the attacks, we identify the gaps between PMDs' security mechanisms and the possible attacks. We show that current security mechanisms generally fail to provide protection from all of the attacks against PMDs and suggest the development of a comprehensive framework to secure PMDs and protect the patients that rely upon them.

Non-Linear Dynamical Analysis of Resting Tremor for Demand-Driven Deep Brain Stimulation

Parkinson's Disease (PD) is currently the second most common neurodegenerative disease. One of the most characteristic symptoms of PD is resting tremor. Local Field Potentials (LFPs) have been widely studied to investigate deviations from the typical patterns of healthy brain activity. However, the inherent dynamics of the Sub-Thalamic Nucleus (STN) LFPs and their spatiotemporal dynamics have not been well characterized. In this work, we study the non-linear dynamical behaviour of STN-LFPs of Parkinsonian patients using ε -recurrence networks. RNs are a non-linear analysis tool that encodes the geometric information of the underlying system, which can be characterised (for example, using graph theoretical measures) to extract information on the geometric properties of the attractor. Results show that the activity of the STN becomes more non-linear during the tremor episodes and that ε -recurrence network analysis is a suitable method to distinguish the transitions between movement conditions, anticipating the onset of the tremor, with the potential for application in a demand-driven deep brain stimulation system.

Cybersecurity in health – disentangling value tensions

Purpose

Cybersecurity in healthcare has become an urgent matter in recent years due to various malicious attacks on hospitals and other parts of the healthcare infrastructure. The purpose of this paper is to provide an outline of how core values of the health systems, such as the principles of biomedical ethics, are in a supportive or conflicting relation to cybersecurity.

Design/methodology/approach

This paper claims that it is possible to map the desiderata relevant to cybersecurity onto the four principles of medical ethics, i.e. beneficence, non-maleficence, autonomy and justice, and explore value conflicts in that way.

Findings

With respect to the question of how these principles should be balanced, there are reasons to think that the priority of autonomy relative to beneficence and non-maleficence in contemporary medical ethics could be extended to value conflicts in health-related cybersecurity.

Research limitations/implications

However, the tension between autonomy and justice, which relates to the desideratum of usability of information and communication technology systems, cannot be ignored even if one assumes that respect for autonomy should take priority over other moral concerns.

Originality/value

In terms of value conflicts, most discussions in healthcare deal with the conflict of balancing efficiency and privacy given the sensible nature of health information. In this paper, the authors provide a broader and more detailed outline.

Cybersecurity in cardiac implantable electronic devices

INTRODUCTION

Cardiac implantable electronic devices (CIEDs) integrate numerous automatic and monitor functions. Nowadays, most CIEDs are connected to the Internet (via Wi-Fi, Bluetooth or smartphone) to ensure remote monitoring of technical and clinical data: despite the importance of such a monitoring, especially from a clinical point of view, concerns have been raised about information (IT) security in terms of both privacy and security for CIEDs' carriers.

AREAS COVERED

This review will provide an outline of remote monitoring of CIEDs, main IT security issues that have affected them so far, main cybervulnerabilities and possible solutions.

EXPERT OPINION

Although there is no evidence that cyber-attacks have been carried out against any CIED so far, they may occur in the future. Cyber-attacks are usually aimed at stealing sensitive information or granting access to the IT systems to which CIEDs are connected; the possibility of an active reprogramming of CIEDs by cyber-attacks is extremely low. Political, regulatory, scientific, and clinical integration is essential to provide not only effective IT solutions for CIEDs and their carriers, but also for the development of educational programs; it should also promote cooperation between stakeholders in order to reduce the risk of CIEDs' cybervulnerability and increase patient safety.

Design and Analysis of a True Random Number Generator Based on GSR Signals for Body Sensor Networks

Today, medical equipment or general-purpose devices such as smart-watches or smart-textiles can acquire a person's vital signs. Regardless of the type of device and its purpose, they are all equipped with one or more sensors and often have wireless connectivity. Due to the transmission of sensitive data through the insecure radio channel and the need to ensure exclusive access to authorised entities, security mechanisms and cryptographic primitives must be incorporated onboard these devices. Random number generators are one such necessary cryptographic primitive. Motivated by this, we propose a True Random Number Generator (TRNG) that makes use of the GSR signal measured by a sensor on the body. After an exhaustive analysis of both the entropy source and the randomness of the output, we can conclude that the output generated by the proposed TRNG behaves as that produced by a random variable. Besides, and in comparison with the previous proposals, the performance offered is much higher than that of the earlier works.

An Investigation into Healthcare-Data Patterns

Visualising complex data facilitates a more comprehensive stage for conveying knowledge. Within the medical data domain, there is an increasing requirement for valuable and accurate information. Patients need to be confident that their data is being stored safely and securely. As such, it is now becoming necessary to visualise data patterns and trends in real-time to identify erratic and anomalous network access behaviours. In this paper, an investigation into modelling data flow within healthcare infrastructures is presented; where a dataset from a Liverpool-based (UK) hospital is employed for the case study. Specifically, a visualisation of transmission control protocol (TCP) socket connections is put forward, as an investigation into the data complexity and user interaction events within healthcare networks. In addition, a filtering algorithm is proposed for noise reduction in the TCP dataset. Positive results from using this algorithm are apparent on visual inspection, where noise is reduced by up to 89.84%.

A Survey of Healthcare Monitoring Systems for Chronically Ill Patients and Elderly

The demand of healthcare systems for chronically ill patients and elderly has increased in the last few years. This demand is derived by the necessity to allow patients and elderly to be independent in their homes without the help of their relatives or caregivers. The prosperity of the information technology plays an essential role in healthcare by providing continuous monitoring and alerting mechanisms. In this paper, we survey the most recent applications in healthcare monitoring. We organize the applications into categories and present their common architecture. Moreover, we explain the standards used and challenges faced in this field. Finally, we make a comparison between the presented applications and discuss the possible future research paths.

Experimental Phantom-Based Security Analysis for Next-Generation Leadless Cardiac Pacemakers

With technological advancement, implanted medical devices can treat a wide range of chronic diseases such as cardiac arrhythmia, deafness, diabetes, etc. Cardiac pacemakers are used to maintain normal heart rhythms. The next generation of these pacemakers is expected to be completely wireless, providing new security threats. Thus, it is critical to secure pacemaker transmissions between legitimate nodes from a third party or an eavesdropper. This work estimates the eavesdropping risk and explores the potential of securing transmissions between leadless capsules inside the heart and the subcutaneous implant under the skin against external eavesdroppers by using physical-layer security methods. In this work, we perform phantom experiments to replicate the dielectric properties of the human heart, blood, and fat for channel modeling between in-body-to-in-body devices and from in-body-to-off-body scenario. These scenarios reflect the channel between legitimate nodes and that between a legitimate node and an eavesdropper. In our case, a legitimate node is a leadless cardiac pacemaker implanted in the right ventricle of a human heart transmitting to a legitimate receiver, which is a subcutaneous implant beneath the collar bone under the skin. In addition, a third party outside the body is trying to eavesdrop the communication. The measurements are performed for ultrawide band (UWB) and industrial, scientific, and medical (ISM) frequency bands. By using these channel models, we analyzed the risk of using the concept of outage probability and determine the eavesdropping range in the case of using UWB and ISM frequency bands. Furthermore, the probability of positive secrecy capacity is also determined, along with outage probability of a secrecy rate, which are the fundamental parameters in depicting the physical-layer security methods. Here, we show that path loss follows a log-normal distribution. In addition, for the ISM frequency band, the probability of successful eavesdropping for a data rate of 600 kbps (Electromyogram (EMG)) is about 97.68% at an eavesdropper distance of 1.3 m and approaches 28.13% at an eavesdropper distance of 4.2 m, whereas for UWB frequency band the eavesdropping risk approaches 0.2847% at an eavesdropper distance of 0.22 m. Furthermore, the probability of positive secrecy capacity is about 44.88% at eavesdropper distance of 0.12 m and approaches approximately 97% at an eavesdropper distance of 0.4 m for ISM frequency band, whereas for UWB, the same statistics are 96.84% at 0.12 m and 100% at 0.4 m. Moreover, the outage probability of secrecy capacity is also determined by using a fixed secrecy rate.

ECG-RNG: A Random Number Generator Based on ECG Signals and Suitable for Securing Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are a promising technology with applications in many areas such as environment monitoring, agriculture, the military field or health-care, to name but a few. Unfortunately, the wireless connectivity of the sensors opens doors to many security threats, and therefore, cryptographic solutions must be included on-board these devices and preferably in their design phase. In this vein, Random Number Generators (RNGs) play a critical role in security solutions such as authentication protocols or key-generation algorithms. In this article is proposed an avant-garde proposal based on the cardiac signal generator we carry with us (our heart), which can be recorded with medical or even low-cost sensors with wireless connectivity. In particular, for the extraction of random bits, a multi-level decomposition has been performed by wavelet analysis. The proposal has been tested with one of the largest and most publicly available datasets of electrocardiogram signals (202 subjects and 24 h of recording time). Regarding the assessment, the proposed True Random Number Generator (TRNG) has been tested with the most demanding batteries of statistical tests (ENT, DIEHARDERand NIST), and this has been completed with a bias, distinctiveness and performance analysis. From the analysis conducted, it can be concluded that the output stream of our proposed TRNG behaves as a random variable and is suitable for securing WSNs.

A critical review and analysis of ethical issues associated with the artificial pancreas

The artificial pancreas combines a hormone infusion pump with a continuous glucose monitoring device, supported by a dosing algorithm currently installed on the pump. It allows for dynamic infusions of insulin (and possibly other hormones such as glucagon) tailored to patient needs. For patients with type 1 diabetes the artificial pancreas has been shown to prevent more effectively hypoglycaemic events and hyperglycaemia than insulin pump therapy and has the potential to simplify care. However, the potential ethical issues associated with the upcoming integration of the artificial pancreas into clinical practice have not yet been discussed. Our objective was to identify and articulate ethical issues associated with artificial pancreas use for patients, healthcare professionals, industry and policymakers. We performed a literature review to identify clinical, psychosocial and technical issues raised by the artificial pancreas and subsequently analysed them through a common bioethics framework. We identified five sensitive domains of ethical issues. Patient confidentiality and safety can be jeopardized by the artificial pancreas' vulnerability to security breaches or unauthorized data sharing. Public and private coverage of the artificial pancreas could be cost-effective and warranted. Patient selection criteria need to ensure equitable access and sensitivity to patient-reported outcomes. Patient coaching and support by healthcare professionals or industry representatives could help foster realistic expectations in patients. Finally, the artificial pancreas increases the visibility of diabetes and could generate issues related to personal identity and patient agency. The timely consideration of these issues will optimize the technological development and clinical uptake of the artificial pancreas.

A Novel Authentication and Key Agreement Scheme for Implantable Medical Devices Deployment

Implantable medical devices (IMDs) are man-made devices, which can be implanted in the human body to improve the functioning of various organs. The IMDs monitor and treat physiological condition of the human being (for example, monitoring of blood glucose level by insulin pump). The advancement of information and communication technology enhances the communication capabilities of IMDs. In healthcare applications, after mutual authentication, a user (for example, doctor) can access the health data from the IMDs implanted in a patient's body. However, in this kind of communication environment, there are always security and privacy issues, such as leakage of health data and malfunctioning of IMDs by an unauthorized access. To mitigate these issues, in this paper, we propose a new secure remote user authentication scheme for IMDs communication environment to overcome security and privacy issues in existing schemes. We provide the formal security verification using the widely accepted Automated Validation of Internet Security Protocols and Applications tool. We also provide the informal security analysis of the proposed scheme. The formal security verification and informal security analysis prove that the proposed scheme is secure against known attacks. The practical demonstration of the proposed scheme is performed using the broadly accepted NS2 simulation tool. The computation and communication costs of the proposed scheme are also comparable with the existing schemes. Moreover, the scheme provides additional functionality features, such as anonymity, untraceability, and dynamic implantable medical device addition.