ReviewSensors for internet of medical things: State-of-the-art, security and privacy issues, challenges and future directions
Introduction
Recent developments in micro MEMS technology, large scale integration, and high-speed, low-latency pervasive communication have helped the Internet of Things (IoT) to emerge as a key enabler of heterogeneous application deployments. Almost all sectors of applications, including transportation, smart home automation, industrial automation, smart agriculture, smart city are getting benefits from IoT-based services [1]. Health being the wealth of a man, is simultaneously given equal preference and importance to come up as latest innovative business model. Different types of millions e-health sensors i.e. biosensors are getting connected with the IoT-enabled e-healthcare domain to serve heterogeneous applications that includes, clinical diagnostics, cardiac activity monitoring, sleep monitoring, woman health monitoring, infant monitoring, continuous glucose monitoring, fitness tracking, predictive medication, and smart home care.
A large number of sensors and their sub-systems are helping out people of multitude of range, such as, common healthy men/women, pregnant women, baby, infant, child, elderly, construction worker, and military. The aim of IoT-based sensor integration-facility is to pave smarter and pervasive e-healthcare services to the society [2], [3].
Problems:
Although, IoT is heavily populated with huge number of healthcare applications, it lacks a comprehensive understanding of how the biosensors are being utilized, applied, categorized or marketed. Various academic reviews have summarized IoT as main component of healthcare domain [4]. However, due to the constant upgradation of technology and simultaneous change of taste of our society, the gap of sensor-centric intervention is gradually taking a shape. For this reason, regular adoption and upgradation of current scenario in e-healthcare is warranted [5].
Inclusion–Exclusion criteria:
In this systematic review, we categorize, discuss and evaluate existing IoT-based sensors that may be of potential benefit for dedicated sector of beneficiaries [6], [7], [8], [9]. To undertake this task, we compiled a list of known sensors for monitoring physiology, health status, cognitive and affective aspects of people. Sensors and IoT-based market cap originated sensors-system for inclusion in the review were identified by searching the internet and scientific databases (e.g., PubMed, IEEE Xplore, ScienceDirect, Springer DL) by using following key terms, such as “IoT AND sensor AND review”, “Sensor”, “e-healthcare sensor”, “pervasive health sensor”, “sensor AND IoT”, “biofeedback sensor”, “respiration sensor”, “muscle oxygenation sensor”, “sleep sensor”, “blood pressure sensor”, “cancer AND sensor”, “blood clot sensor”, “brain sensor”, “ECG sensor”, “skin pressure sensor”, “urinal sensor”, “pancreas sensor”, “ingestible sensor”, “non-invasive sensor”, “invasive sensor”, “eye sensor”, “cognitive function sensor”, and “concussion”.
Contributions:
We further examined the websites for learning about existing commercial sensor technologies for links to IoT-based research, and where applicable, we sourced the online and published research paper. We broadly divided the IoT-based e-health sensor technologies into the following categories (Fig. 1):
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disposable health sensors (temperature, pressure, accelerator, biosensors, wearable, implementable, ingestible, invasive, strip, diagnostic, therapeutic and monitoring)
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connected health sensors (consumer, wearable, embedded sensors, flow sensor, level sensor, connectivity, application integration)
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IoT-supported sensors (patient monitoring, therapy administration, diagnostics, treatment, healthcare provider, patients, hardware, and software)
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IoT-market cap sensors (clinical efficient sensor, clinical-grade biometric sensor, consumer/home monitoring sensor, brain sensor, fitness wearable, sleep monitoring, and infant monitoring).
Major contributions:
Our systematic review investigates the key aspects of: (RQ1) what is the taxonomy of existing IoT-based sensors, (RQ2) what IoT-based sensors are claimed to do, (RQ3) what are the major types of IoT-sensors available in market, (RQ4) is the IoT-sensor technology reliable enough or any calibration needed, (RQ5) how IoT-market cap is leveraging e-healthcare domain, (RQ6) security and privacy issues associated with the surveyed sensors, and (RQ7) what should be the future directions for practitioners. Based on this information, we have proposed a taxonomy of IoT-based sensors for e-healthcare and provided details about the same using some unbiased critical way. The list of IoT-sensors, sensor products, and sensor caps in this review is not exhaustive; we intended to provide a cross-sectional systematic summary of what is available in different healthcare categories.
This review is organized as follows. Section 2 presents the novel taxonomy of IoT-sensors for healthcare. Section 3 discusses about futuristic IoT-based e-healthcare scenario with advanced sensor integration, while commenting on various advantages, prospects of using IoT-sensors. We also depicted a list of open challenges for possible development in the same domain. Section 4 presents related work and perform comparison between the existing literature to establish TABLE I. Comparisons of IoT-based Clinical Efficient Sensors the novelty and uniqueness of this paper. Section 5 paves the lessons learned from the study and provides future direction as well as recommendations for the practitioners. Section 6 presents key issues in security and privacy in surveyed IoMT sensor systems and their way out. Section 7 discusses citizen centric as well as paradigm shift oriented approaches in current IoMT domain. Section 8 concludes the review.
Section snippets
Taxonomy of IoT sensors for e-healthcare
This section proposes a novel taxonomy that illustrates the IoT-based sensors which are used in e-healthcare domain. The taxonomy is primarily divided into four segments, such as, (A) disposable e-health sensors, (B) connected e-health sensors, (C) IoT-based sensors for e-healthcare, and (D) IoT-based market capitalization (market cap) of recently deployed sensors that represent the market value of a company’s shares in global market [10]. Fig. 1. presents the taxonomy showing various
Discussions on IoT sensors for healthcare
This section discusses on futuristic IoT-based use cases for improvement of e-healthcare scenario, advantages and challenges of existing IoT-based sensor for e-healthcare.
Related work
This review included total 13 survey articles based on following selection metrics, such as, (i) healthcare-IoT based survey or review, (ii) studies on e-healthcare and sensor using IoT, (iii) sensor inclusion, and (iv) contribution including issues and future directions. Table 6 presents the comparative study between all the included survey/review articles against this article. Gholamhosseini et al. [24] surveyed on Health IoT, security threats, complexity, and weakness of existing health
Lessons learned
From the comparison between the related works as presented in Table 6, we learned following lessons, such as, (i) minimal percentage of overall studies investigated the sensor for healthcare. However, we found that those studies only involved some generic health sensors for example, respiratory sensor, temperature sensor, SPO2 sensor, ECG sensor, and light sensors. No explicit study was formulated neither investigated that showed what type of health-sensors exist in market domain and how they
Security and privacy issues of IoMT sensors
This review presents a detailed discussion on various types of sensors available and being popularly used in many aspects of IoT-base healthcare [67]. A major research gap that we found while study these sensors is no article has discussed how such sensors face security and privacy issues. In this section we illustrate this major concern by providing some key aspects.
Key aspects on citizen centric approach
IoMT is a latest inclusion into the healthcare industry. There seems to prevail a generic form of societal inertia against using and get habituated with these new inclusions [100], [101]. We discuss how citizens could benefited from IoMT sensors while residing in urban or rural regions of any country [102]. Major concerns in such societal inertia occur due to the lack of awareness among the citizen about latest trend and invasion of IoMT into the healthcare domain [103]. We found that citizen
Conclusion
IoT-based solutions like IoT-sensor enabled IoMT and e-healthcare and connected medical solution are proving to be a game changer in the IoT oriented healthcare industry. With the enormous growth of related applications, IoT has been gradually facilitating the healthcare providers including medical practitioners, care givers, hospitals, and clinics to nurture the patients with most effective, predictive and accurate medication services and strategies. Integrating IoT-based sensors into
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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