IoMT and Data Privacy in Alzheimer’s Care for Older Adults: A Systematic Review

Md Mehedi Hasan; Fahim Islam Anik; Juan Rodriguez-Cardenas; Richard Beiswanger; Masrura Tasnim; Mary Ramos; Nazmus Sakib

doi:10.4108/eetpht.11.6170

Authors

Md Mehedi Hasan Kennesaw State University
Fahim Islam Anik Khulna University
Juan Rodriguez-Cardenas Kennesaw State University
Richard Beiswanger Kennesaw State University
Masrura Tasnim Kennesaw State University
Mary Ramos Kennesaw State University
Nazmus Sakib Kennesaw State University

DOI:

https://doi.org/10.4108/eetpht.11.6170

Keywords:

Data Privacy, Smart Health, Alzhemier's , Older Adults, Internet of Medical Things (IoMT)

Abstract

INTRODUCTION: The use of medical Internet of Things (IoT) devices becomes essential in everyday healthcare routines as the older adults confront an increasing risk of cyber victimization because of Alzheimer's illness. Despite the myriad benefits of IoT devices, escalating concerns about data privacy and cybersecurity loom larger, given the cognitive and physical decline associated with Alzheimer's.
OBJECTIVES: Focusing on the challenges faced by older adults, especially those with Alzheimer's, this study aims to investigate the data privacy and security risks and advocates for specialized education and user-friendly interfaces to narrow the digital divide.
METHODS: Eighteen peer-reviewed articles were selected based on predefined inclusion criteria, focusing on older adults or Alzheimer's patients, IoMT in healthcare, and data privacy or security concerns. Searches were conducted in PubMed and IEEE Xplore, following PRISMA 2020 guidelines. A structured data extraction matrix informed by Grounded Theory was used to chart and analyze key themes across selected studies, including types of vulnerabilities, consequences, and proposed solutions.
RESULTS: Recurring vulnerabilities included social engineering, data breaches, weak authentication, and poor access control. Effective mitigation strategies identified include patient and caregiver education, improved informed consent procedures, robust encryption, and data governance reforms.
CONCLUSION: Smart home technology and the digitization of the healthcare field have shown great promise in caring for Alzheimer's patients, positively affecting their ability to live on their own safely. They also create new challenges with the need to protect the sensitive information they gather. Our research emphasizes developing strategies that can create awareness and educate patients and their caregivers to further reduce the risks related to data security.

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References

[1] Dementia n.d. https://www.who.int/news-room/fact-sheets/detail/dementia (accessed June 26, 2025).

[2] Rhea EM, Leclerc M, Yassine HN, Capuano AW, Tong H, Petyuk VA, et al. State of the Science on Brain Insulin Resistance and Cognitive Decline Due to Alzheimer’s Disease. Aging Dis 2024;15:1688. https://doi.org/10.14336/AD.2023.0814.

[3] Botto R, Callai N, Cermelli A, Causarano L, Rainero I. Anxiety and depression in Alzheimer’s disease: a systematic review of pathogenetic mechanisms and relation to cognitive decline. Neurological Sciences 2022;43:4107–24. https://doi.org/10.1007/S10072-022-06068-X/METRICS.

[4] Shen LX, Yang YX, Kuo K, Li HQ, Chen SD, Chen KL, et al. Social Isolation, Social Interaction, and Alzheimer’s Disease: A Mendelian Randomization Study. Journal of Alzheimer’s Disease 2021;80:665–72. https://doi.org/10.3233/JAD-201442/SUPPL_FILE/SJ-PDF-1-ALZ-10.3233_JAD-201442.PDF.

[5] Ienca M, Fabrice J, Elger B, Caon M, Pappagallo AS, Kressig RW, et al. Intelligent Assistive Technology for Alzheimer’s Disease and Other Dementias: A Systematic Review. Journal of Alzheimer’s Disease 2017;56:1301–40. https://doi.org/10.3233/JAD-161037;SUBPAGE:STRING:ABSTRACT;JOURNAL:JOURNAL:ALZA;WEBSITE:WEBSITE:SAGE;WGROUP:STRING:PUBLICATION.

[6] Syed L, Jabeen S, S. M, Alsaeedi A. Smart healthcare framework for ambient assisted living using IoMT and big data analytics techniques. Future Generation Computer Systems 2019;101:136–51. https://doi.org/10.1016/J.FUTURE.2019.06.004.

[7] Khan MF, Ghazal TM, Said RA, Fatima A, Abbas S, Khan MA, et al. An IoMT-Enabled Smart Healthcare Model to Monitor Elderly People Using Machine Learning Technique. Comput Intell Neurosci 2021;2021:2487759. https://doi.org/10.1155/2021/2487759.

[8] Awotunde JB, Ogundokun RO, Adeniyi AE, Abiodun MK, Ayo FE, Ajamu GJ, et al. Cloud-IoMT-based wearable body sensors network for monitoring elderly patients during the COVID-19 pandemic. Biomedical Engineering Applications for People with Disabilities and the Elderly in the COVID-19 Pandemic and Beyond 2022:33–48. https://doi.org/10.1016/B978-0-323-85174-9.00028-5.

[9] Jones D, Ghasemi S, Gračanin D, Azab M. Privacy, Safety, and Security in Extended Reality: User Experience Challenges for Neurodiverse Users. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2023;14045 LNCS:511–28. https://doi.org/10.1007/978-3-031-35822-7_33.

[10] Berridge C, Demiris G, Kaye J. Domain Experts on Dementia-Care Technologies: Mitigating Risk in Design and Implementation. Sci Eng Ethics 2021;27:1–24. https://doi.org/10.1007/S11948-021-00286-W/TABLES/5.

[11] Mishra PK, Iaboni A, Ye B, Newman K, Mihailidis A, Khan SS. Privacy-protecting behaviours of risk detection in people with dementia using videos. Biomed Eng Online 2023;22:1–17. https://doi.org/10.1186/S12938-023-01065-3/FIGURES/5.

[12] Rosenfeld L, Torous J, Vahia I V. Data Security and Privacy in Apps for Dementia: An Analysis of Existing Privacy Policies. The American Journal of Geriatric Psychiatry 2017;25:873–7. https://doi.org/10.1016/J.JAGP.2017.04.009.

[13] Gupta S, Kapoor M, Debnath SK. Cybersecurity Risks and Threats in Healthcare. Artificial Intelligence-Enabled Security for Healthcare Systems 2025:39–64. https://doi.org/10.1007/978-3-031-82810-2_3.

[14] Luna R, Rhine E, Myhra M, Sullivan R, Kruse CS. Cyber threats to health information systems: A systematic review. Technology and Health Care 2016;24:1–9. https://doi.org/10.3233/THC-151102.

[15] Khatun MA, Memon SF, Eising C, Dhirani LL. Machine Learning for Healthcare-IoT Security: A Review and Risk Mitigation. IEEE Access 2023;11:145869–96. https://doi.org/10.1109/ACCESS.2023.3346320.

[16] Madanian S, Chinbat T, Subasinghage M, Airehrour D, Hassandoust F, Yongchareon S. Health IoT Threats: Survey of Risks and Vulnerabilities. Future Internet 2024, Vol 16, Page 389 2024;16:389. https://doi.org/10.3390/FI16110389.

[17] Roobini S, Kavitha M, Sujaritha M, Rajesh Kumar D. Cyber-Security Threats to IoMT-Enabled Healthcare Systems. Cognitive Computing for Internet of Medical Things 2022:105–30. https://doi.org/10.1201/9781003256243-6.

[18] Chakraborty N, Iqbal S, Zulkernine M. Risk Assessment in Smart Aging Care Systems: An Elderly-Centered Perspective. Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023 2023:1–12. https://doi.org/10.1109/ICDH60066.2023.00012.

[19] Shaik MA, Anik FI, Hasan MM, Chakravarty S, Ramos MD, Rahman MA, et al. Advancing Remote Monitoring for Patients With Alzheimer Disease and Related Dementias: Systematic Review. JMIR Aging 2025;8:e69175. https://doi.org/10.2196/69175.

[20] Sun F, Jiang L, Chen XS, Feng Y. Interactive AI Technology for Dementia Caregivers: Needs and Implementation Evidence. J Technol Hum Serv 2025. https://doi.org/10.1080/15228835.2025.2460156;JOURNAL:JOURNAL:WZCH20;CSUBTYPE:STRING:SPECIAL;PAGE:STRING:ARTICLE/CHAPTER.

[21] Arthanat S, Wilcox J, LaRoche D. Smart home automation technology to support caring of individuals with Alzheimer’s disease and related dementia: an early intervention framework. Disabil Rehabil Assist Technol 2024;19:779–89. https://doi.org/10.1080/17483107.2022.2125088;PAGE:STRING:ARTICLE/CHAPTER.

[22] Addae S, Kim J, Smith A, Rajana P, Kang M. Smart Solutions for Detecting, Predicting, Monitoring, and Managing Dementia in the Elderly: A Survey. IEEE Access 2024;12:100026–56. https://doi.org/10.1109/ACCESS.2024.3421966.

[23] Bajpayi P, Sharma S, Gaur MS. AI Driven IoT Healthcare Devices Security Vulnerability Management. 2024 2nd International Conference on Disruptive Technologies, ICDT 2024 2024:366–73. https://doi.org/10.1109/ICDT61202.2024.10488939.

[24] Mejía-Granda CM, Fernández-Alemán JL, Carrillo-de-Gea JM, García-Berná JA. Security vulnerabilities in healthcare: an analysis of medical devices and software. Med Biol Eng Comput 2024;62:257–73. https://doi.org/10.1007/S11517-023-02912-0/TABLES/9.

[25] Tsantikidou K, Sklavos N. Vulnerabilities of Internet of Things, for Healthcare Devices and Applications. Proceedings - 2021 8th NAFOSTED Conference on Information and Computer Science, NICS 2021 2021:498–503. https://doi.org/10.1109/NICS54270.2021.9701497.

[26] Keshta I, Odeh A. Security and privacy of electronic health records: Concerns and challenges. Egyptian Informatics Journal 2021;22:177–83. https://doi.org/10.1016/J.EIJ.2020.07.003.

[27] Ilori O, Nwosu NT, Nwapali H, Naiho N. Third-party vendor risks in IT security: A comprehensive audit review and mitigation strategies. Https://WjarrCo.in/Sites/Default/Files/WJARR-2024-1727Pdf 2024;22:213–24. https://doi.org/10.30574/WJARR.2024.22.3.1727.

[28] Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. The BMJ 2021;372. https://doi.org/10.1136/BMJ.N71.

[29] Dwivedi R, Mehrotra D, Chandra S. Potential of Internet of Medical Things (IoMT) applications in building a smart healthcare system: A systematic review. J Oral Biol Craniofac Res 2022;12:302–18. https://doi.org/https://doi.org/10.1016/j.jobcr.2021.11.010.

[30] Litmaps | Your Literature Review Assistant n.d. https://www.litmaps.com/ (accessed June 26, 2025).

[31] Jaigirdar FT, Rudolph C, Bain C. Risk and Compliance in IoT- Health Data Propagation: A Security-Aware Provenance based Approach. Proceedings - 2021 IEEE International Conference on Digital Health, ICDH 2021 2021:27–37. https://doi.org/10.1109/ICDH52753.2021.00015.

[32] Chatzisofroniou G, Markellos C, Kotzanikolaou P. Assessing the Security Risks of Medical Mobile Applications. Proc IEEE Symp Comput Commun 2023;2023-July. https://doi.org/10.1109/ISCC58397.2023.10217984.

[33] Martinez CJ, Galmes S. Analysis of the primary attacks on IoMT Internet of Medical Things communications protocols. 2022 IEEE World AI IoT Congress (AIIoT) 2022:708–14. https://doi.org/10.1109/AIIOT54504.2022.9817252.

[34] Soundari D V., Kavya R, Monika P, Pooja S. IOT Based Surveillance and Health Monitoring System for Elderly and Physically Challenged People. Proceedings of the 6th International Conference on Communication and Electronics Systems, ICCES 2021 2021:702–6. https://doi.org/10.1109/ICCES51350.2021.9489185.

[35] Hassan MM, Gumaei A, Huda S, Almogren A. Increasing the Trustworthiness in the Industrial IoT Networks through a Reliable Cyberattack Detection Model. IEEE Trans Industr Inform 2020;16:6154–62. https://doi.org/10.1109/TII.2020.2970074.

[36] Frank F, Bjerregaard F, Bengel J, Bitzer EM, Heimbach B, Kaier K, et al. Local, collaborative, stepped and personalised care management for older people with chronic diseases (LoChro): study protocol of a randomised comparative effectiveness trial. BMC Geriatr 2019;19:64. https://doi.org/10.1186/s12877-019-1088-0.

[37] Karssemeijer EGA, Aaronson JA, Bossers WJR, Donders R, Olde Rikkert MGM, Kessels RPC. The quest for synergy between physical exercise and cognitive stimulation via exergaming in people with dementia: a randomized controlled trial. Alzheimers Res Ther 2019;11:3. https://doi.org/10.1186/s13195-018-0454-z.

[38] Lee RZY, Yu J, Rawtaer I, Allen PF, Bao Z, Feng L, et al. CHI study: protocol for an observational cohort study on ageing and mental health in community-dwelling older adults. BMJ Open 2020;10:e035003. https://doi.org/10.1136/bmjopen-2019-035003.

[39] Bertini F, Beltrami D, Barakati P, Calza L, Ghidoni E, Montesi D. A Web-Based Application for Screening Alzheimer’s Disease in the Preclinical Phase. Proc IEEE Symp Comput Commun 2023;2023-July. https://doi.org/10.1109/ISCC58397.2023.10218229.

[40] Ali HY, El-Medany W. IoT security: A review of cybersecurity architecture and layers. 2nd Smart Cities Symposium (SCS 2019), 2019, p. 1–7. https://doi.org/10.1049/cp.2019.0191.

[41] Hatzivasilis G, Soultatos O, Ioannidis S, Verikoukis C, Demetriou G, Tsatsoulis C. Review of security and privacy for the internet of medical things (IoMT): Resolving the protection concerns for the novel circular economy bioinformatics. Proceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019 2019:457–64. https://doi.org/10.1109/DCOSS.2019.00091.

[42] Kaur A, Isha, Rai G, Malik A. Authentication and Context Awareness Access Control in Internet of Things: A Review. Proceedings of the 8th International Conference Confluence 2018 on Cloud Computing, Data Science and Engineering, Confluence 2018 2018:630–5. https://doi.org/10.1109/CONFLUENCE.2018.8443067.

[43] Gettel CJ, Chen K, Goldberg EM. Dementia Care, Fall Detection, and Ambient-Assisted Living Technologies Help Older Adults Age in Place: A Scoping Review. Journal of Applied Gerontology 2021;40:1893–902. https://doi.org/10.1177/07334648211005868.

[44] Sunny JS, Patro CPK, Karnani K, Pingle SC, Lin F, Anekoji M, et al. Anomaly Detection Framework for Wearables Data: A Perspective Review on Data Concepts, Data Analysis Algorithms and Prospects. Sensors 2022;22:756. https://doi.org/10.3390/s22030756.

[45] Capiau A, Foubert K, Van der Linden L, Walgraeve K, Hias J, Spinewine A, et al. Medication Counselling in Older Patients Prior to Hospital Discharge: A Systematic Review. Drugs Aging 2020;37:635–55. https://doi.org/10.1007/s40266-020-00780-z.

[46] Lovell J, Pham T, Noaman SQ, Davis M-C, Johnson M, Ibrahim JE. Self-management of heart failure in dementia and cognitive impairment: a systematic review. BMC Cardiovasc Disord 2019;19:99. https://doi.org/10.1186/s12872-019-1077-4.

[47] Malamas V, Chantzis F, Dasaklis TK, Stergiopoulos G, Kotzanikolaou P, Douligeris C. Risk Assessment Methodologies for the Internet of Medical Things: A Survey and Comparative Appraisal. IEEE Access 2021;9:40049–75. https://doi.org/10.1109/ACCESS.2021.3064682.