This study collected literature from major databases and revealed that all researchers addressed security aspects, such as basic authentication and privacy, but they neglected cryptographic measures, which remain the weakest point of execution in Arduino-based medical systems.
Abstract
Arduino is a popular choice for healthcare technology due to its open-source platform and low cost, making it ideal for developing intelligent medical solutions without the high costs of conventional systems. The current studies have largely assessed Arduino capabilities based on specific features rather than thoroughly testing the system's security, technical, and operational aspects. To address these issues, this study uses a Population, Intervention, Comparison, and Outcome (PICO)-based SLR that adheres to PRISMA guidelines and the Joanna Briggs Institute tool to critically evaluate the study's findings. This study collected literature from major databases, including Web of Science, Google Scholar, and ScienceDirect, covering the period from 2020 to 2024. It identified 216 papers, and only 8 met the PICOS eligibility criteria. The findings reveal that all researchers addressed security aspects, such as basic authentication and privacy, but they neglected cryptographic measures, which remain the weakest point of execution. Encryption, auditability, accountability, and freshness were implemented only once. Integrity, authorization, and third-party protection were rarely applied, and non-repudiation evaluation was minimal. Technical aspects such as accuracy and validation were satisfactory. However, reliability was tested in limited environments, and fault tolerance and robustness were poorly implemented. Operational aspects like cost and sustainability were widely addressed, whereas resilience, availability, and reliability received little attention. Arduino-based medical systems show strong technical promise but remain constrained by major security and operational gaps, limiting their readiness for real-world health settings.
The increasing adoption of Internet of Medical Things (IoMT) technologies within healthcare systems has significantly improved real-time patient monitoring, clinical decision-making, and health information exchange. However, the integration of interconnected medical devices has simultaneously expanded the cybersecurity threat landscape, particularly within resource-constrained healthcare environments characterized by limited technical capacity, inadequate governance mechanisms, and insufficient cybersecurity expertise. This study critically evaluated existing cybersecurity frameworks for Information Sharing-Enabled IoMT systems, including the National Institute of Standards and Technology (NIST) Cybersecurity Framework, COBIT, Critical Information Infrastructure Protection (CIIP), and the IoT Security Foundation (IoTSF) Security Compliance Framework. The study employed a mixed-method exploratory research design combining systematic literature review, comparative framework analysis, and descriptive quantitative assessment conducted at St. Francis Hospital Nsambya and Uganda Martyrs Hospital Lubaga. Quantitative findings were analyzed using descriptive statistics, while qualitative findings were synthesized thematically. The findings revealed that existing frameworks provide fragmented security solutions that inadequately integrate technical security controls, governance mechanisms, healthcare operational requirements, and socio-behavioral determinants necessary for secure IoMT implementation in low-resource healthcare contexts. Based on the identified gaps, the study proposes an integrated healthcare-oriented IoMT cybersecurity framework that combines governance, technical safeguards, compliance mechanisms, and socio-behavioral dimensions to strengthen secure information sharing and cybersecurity resilience within resource-constrained healthcare institutions. The study concludes that context-specific and integrated cybersecurity frameworks are essential for enhancing secure information sharing and sustainable IoMT adoption in developing healthcare systems.
W. Arinaitwe, K. Margaret, Olusegun Ganiyu· Journal of Technology Inform...· 0 citations
The convergence of Large Language Models (LLMs) with the Internet of Things (IoT) is driving a transformative shift toward a continuous, context-aware smart healthcare ecosystem. Due to its novelty, existing research in this domain remains fragmented, leaving a critical gap in unified frameworks that synthesize domain applications, functional AI deployment roles, network architectures, and security boundaries. Following PRISMA 2020 guidelines, this paper presents a systematic literature review and quantitative analysis evaluating a selected corpus of 61 peer-reviewed and 14 preprint papers in this domain. Methodologically, we assess a novel hybrid article discovery strategy, finding that an AI-powered prompt-based literature search strategy achieves higher precision than traditional keyword-based Boolean queries (86% vs. 42%) on the evaluated search sample, which may reduce screening workloads. We found that the major limitation of AI-based literature search is non-determinism, which is also an inherent property of LLM-powered applications. To address this, we propose methodological guidelines for using an AI-assisted hybrid literature search strategy. Based on the selected literature, we establish a multi-layer taxonomy organizing the IoT-LLM advances in the healthcare domain across four pillars: application domain, LLM role, IoT device type, and architectural deployment pattern. Quantitative synthesis reveals a heavy research concentration in remote patient monitoring and personal health management (representing 59% of the corpus combined), primarily driven by the data accessibility of wearable sensors (64%). Cross-tabulation uncovers a distinct capability–constraint spectrum: cloud-based deployments lean on heavyweight state-of-the-art models (mainly GPT-family models) for complex semantic reasoning, whereas edge, federated, and blockchain-based hybrid systems leverage localized models (BERT and LLaMA families). Patient data privacy and reduced communication overhead were among the main reasons for choosing localized models. Crucially, our assessment reveals a pervasive neglect of LLM-specific vulnerabilities such as prompt injection and jailbreak attacks and a tendency to treat regulatory frameworks (e.g., HIPAA, GDPR) as design features rather than empirically validated compliance metrics. Finally, we propose an actionable future research agenda prioritizing multi-device system orchestration, emergency care integration, privacy-preserving LLMs, and deployment-scale clinical validation.
P. Mekala, Yonas Kassa, Sushma Mishra· IoT· 0 citations
This paper provides a detailed discussion on how cryptography techniques have been essential in changing the healthcare sector. Because of the emergence of various healthcare applications and the increase in the amount of data in the healthcare sector, there is a need for ensuring that the data are protected. In this paper, we will be looking at the capabilities of cryptography, which can help in solving problems and ensuring security in future healthcare systems. This paper focuses on cryptography in healthcare systems, which is made up of practices and methods that ensure that sensitive healthcare information is encrypted, authenticated, hashed and keys are managed securely. This paper provides an overview of cryptographic evolution and concepts. It also looks at some of the challenges that may affect the use of cryptography in practice. Overcoming such issues will require a pragmatic and structured strategy. The paper offers pragmatic suggestions that will help in utilizing cryptography in an efficient manner within real-world systems hence, the paper proposed an implementation framework integrating encryption, authentication, key management and auditing. These findings offer a way forward for policy-makers to increase the security and resilience of EHRs within the public health care system through empirical knowledge. The paper ends by making actionable suggestions for the health care organization and future research direction.
Theophilus Bamise Ajala, Adeniyi Akanni, Olajide Adegunwa et al.· International journal of res...· 0 citations
The healthcare sector increasingly relies on electronic systems to manage patient information,
improve service delivery, and enhance operational efficiency. However, the digitization of medical
records has introduced significant security and privacy concerns, including unauthorized access,
data breaches, and identity misuse. The aim of this study is to design and implement a secured
electronic health system using Personal Identification Number (PIN) and barcode technology.
This work was motivated on the basis of finding a solution to the security concerns of patients
about their Electronic Health Records (EHR). The replacement of paper processes in our hospitals
with Electronic Medical Record (EMR) system has neither ended the problem of continued manual
and repeated processes in gathering health history of patients, nor the security problem with the
patients’ health information, hence, the need for the research. The methodology used is the ObjectOriented Analysis and Design Methodology (OOADM). The expected result of this new system is
a two-level authentication security technique, as the hybrid model that will solve the bottlenecks
identified in this work. Some of the hardware, programming and scripting languages, and
application packages that were used for the development of this hybrid software are barcode
reader, php, java scripts, CSS, ajax, and Adobe Photoshop - CS6. Also, MySqlLite is used as the
database system for the program too, given its robustness. Therefore, with the aid of this research,
patient’s health data can now move with him through this new system, “Design and
Implementation Secured Electronic Health system (EHS) Using Pin and Barcode Technology”,
thereby eliminating repeated antiquated processes and interoperability issues.
Juliet Nkechi Iherinwa· INTERNATIONAL JOURNAL OF SOC...· 0 citations
This study examines the impact of data governance (DG), compliance (COM), and digital oversight (DO) on system performance (SP) and security within mobile biomedical systems in Indonesia’s healthcare sector. Employing Socio-Technical Systems Theory, the study investigates the role of regulations in enhancing operational efficiency and strengthening cybersecurity in digital healthcare. A quantitative cross-sectional design was utilised, with data collected from 200 healthcare and biomedical technology professionals through an online questionnaire. Relationships among variables were analysed using multiple linear regression. The results showed that DG had the greatest positive effect on both SP and security, followed by COM and DO. All these relationships were statistically significant (p < 0.001). This study shows that adopting integrated governance frameworks, complying with regulations and maintaining ongoing monitoring are important for making mobile biomedical technologies more reliable and secure. It also adds new evidence by examining operational performance and system security (SS) as distinct outcomes in mobile biomedical systems.
Ade Ikhlas Amal Alam, Khairunnisa Azrin, Fakhrul Indra Hermansyah et al.· International Journal of Onl...· 0 citations
This work expands upon the privacy threat assessment model to quantitatively evaluate the risks of data likability, identifiability, non-repudiation, detectability, unintended disclosure, indulgence, and policy & consent noncompliance, and constructs a framework aimed at mitigating these identified risks.
Jamila Alsayed Kassem, Tim Müller, Christopher A. Esterhuyse et al.· 0 citations
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