Advanced Wearable Health Monitoring System with Multi-Sensor Data and Secure Data Management with Blockchain Technology

Authors

  • S. Aarthee Assistant Professor, School of Computing, SASTRA Deemed University, Thanjavur, Tamil Nadu 613401, India.
  • R. Ramya Department of Computer science and engineering, Bannari Amman Institute of Technology, Sathyamangalam, Tamil Nadu 638401, India
  • R. Priyanka Pramila Assistant Professor, Department of Artificial Intelligence and Data Science, R.M.K. Engineering College, Kavaraipettai, Tamil Nadu 601206, India.
  • M. R. Ezilarasan Department of Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai-600062, India
  • G. Merlin Suba Associate Professor, Department of Electrical and Electronics Engineering, Panimalar Engineering College, Chennai - 600123, India.

Keywords:

Healthcare, Accelerometer, Skin temperature sensor, Blood pressure monitor, Photoplethysmogram, Electrothermal activity

Abstract

Health data management is crucial for informed healthcare decisions. It centralizes real-time information from wearable devices, enabling early detection of issues, personalized recommendations, and comprehensive patient profiles. This organized data aids healthcare professionals in delivering tailored care, improving diagnostics, and enhancing overall patient well-being. Additionally, robust data management ensures security and integrity, instilling patient trust and providing a foundation for impactful research and advancements in healthcare practices. This healthcare data management system utilizes a smartwatch with advanced sensors, including a photo plethysmo gram (PPG) for continuous heart rate monitoring, an accelerometer for physical activity tracking, a skin temperature sensor, a blood pressure monitor, and an electrodermal activity (EDA) sensor for stress assessments. Real-time physiological data is collected, with the PPG sensor capturing blood volume changes, the accelerometer providing insights into physical activity, and the EDA sensor measuring skin conductance for stress levels. The data is transmitted to a centralized platform via IoT, where big data analytics process minute-to-minute variations in heart rate, step counts, sleep patterns, blood pressure, and stress levels. This dataset forms the basis for early health issue detection, personalized recommendations, and detailed patient profiles. The system incorporates blockchain for data security, encrypting and storing information in a decentralized ledger. Patients have control over their data through a user-friendly interface, managing access permissions and providing explicit consent for sharing health information with professionals.

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References

Bao, C., Singh, H., Meyer, B., Kirksey, K., & Bardhan, I. (2020). Patient-provider engagement and its impact on health outcomes: A longitudinal study of patient portal use. MIS quarterly, 44(2).

Harrison, M. I., & Shortell, S. M. (2021). Multi‐level analysis of the learning health system: integrating contributions from research on organizations and implementation. Learning health systems, 5(2), e10226.

World Health Organization. (2021). WHO guideline on self-care interventions for health and well-being. World Health Organization.

Banerjee, A., Chakraborty, C., Kumar, A., & Biswas, D. (2020). Emerging trends in IoT and big data analytics for biomedical and health care technologies. Handbook of data science approaches for biomedical engineering, 121-152.

Qin, H., Steenbergen, N., Glos, M., Wessel, N., Kraemer, J. F., Vaquerizo-Villar, F., & Penzel, T. (2021). The different facets of heart rate variability in obstructive sleep apnea. Frontiers in Psychiatry, 12, 642333.

Rehman, A., Naz, S., & Razzak, I. (2022). Leveraging big data analytics in healthcare enhancement: trends, challenges, and opportunities. Multimedia Systems, 28(4), 1339-1371.

Khanra, S., Dhir, A., Islam, A. N., & Mäntymäki, M. (2020). Big data analytics in healthcare: a systematic literature review. Enterprise Information Systems, 14(7), 878-912.

Chenthara, S., Ahmed, K., Wang, H., Whittaker, F., & Chen, Z. (2020). Healthchain: A novel framework on privacy preservation of electronic health records using blockchain technology. Plos one, 15(12), e0243043.

Manu, S. R., & Bhaskar, G. (2020, June). Securing sensitive data in body area sensor network using blockchain technique. In 2020 5th International Conference on Communication and Electronics Systems (ICCES) (pp. 1-5). IEEE.

Perumal, G., Subburayalu, G., Abbas, Q., Naqi, S. M., & Qureshi, I. (2023). VBQ-Net: A Novel Vectorization-Based Boost Quantized Network Model for Maximizing the Security Level of IoT System to Prevent Intrusions. Systems, 11(8), 436.

Satyanarayana, P., Diwakar, G., Subbayamma, B. V., Kumar, N. P. S., Arun, M., & Gopalakrishnan, S. (2023). Comparative analysis of new meta-heuristic-variants for privacy preservation in wireless mobile adhoc networks for IoT applications. Computer Communications, 198, 262-281.

Esmaeilzadeh, P., & Mirzaei, T. (2019). The potential of blockchain technology for health information exchange: experimental study from patients’ perspectives. Journal of medical Internet research, 21(6), e14184.

Girardi, F., De Gennaro, G., Colizzi, L., & Convertini, N. (2020). Improving the healthcare effectiveness: The possible role of EHR, IoMT and blockchain. Electronics, 9(6), 884.

Teixeira, E., Fonseca, H., Diniz-Sousa, F., Veras, L., Boppre, G., Oliveira, J., ... & Marques-Aleixo, I. (2021). Wearable devices for physical activity and healthcare monitoring in elderly people: A critical review. Geriatrics, 6(2), 38.

Paganelli, A. I., Mondéjar, A. G., da Silva, A. C., Silva-Calpa, G., Teixeira, M. F., Carvalho, F., ... & Endler, M. (2022). Real-time data analysis in health monitoring systems: A comprehensive systematic literature review. Journal of Biomedical Informatics, 127, 104009.

Jacob Rodrigues, M., Postolache, O., & Cercas, F. (2020). Physiological and behavior monitoring systems for smart healthcare environments: A review. Sensors, 20(8), 2186.

Vimalachandran, P. (2019). Privacy and Security of Storing Patients’ Data in the Cloud (Doctoral dissertation, Victoria University).

Wylde, V., Rawindaran, N., Lawrence, J., Balasubramanian, R., Prakash, E., Jayal, A., ... & Platts, J. (2022). Cybersecurity, data privacy and blockchain: a review. SN Computer Science, 3(2), 127.

Somasekhar, G., Patra, R.K., Srujan Raju, K. (2021). The Research Importance and Possible Problem Domains for NoSQL Databases in Big Data Analysis. In: Jyothi, S., Mamatha, D.M., Zhang, YD., Raju, K.S. (eds) Proceedings of the 2nd International Conference on Computational and Bio Engineering . Lecture Notes in Networks and Systems, vol 215. Springer, Singapore. https://doi.org/10.1007/978-981-16-1941-0_43

Joshi, A., Choudhury, T., Sai Sabitha, A., Srujan Raju, K. (2020). Data Mining in Healthcare and Predicting Obesity. In: Raju, K., Govardhan, A., Rani, B., Sridevi, R., Murty, M. (eds) Proceedings of the Third International Conference on Computational Intelligence and Informatics . Advances in Intelligent Systems and Computing, vol 1090. Springer, Singapore. https://doi.org/10.1007/978-981-15-1480-7_82

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Published

24.03.2024

How to Cite

Aarthee, S. ., Ramya, R. ., Pramila, R. P. ., Ezilarasan, M. R. ., & Suba, G. M. . (2024). Advanced Wearable Health Monitoring System with Multi-Sensor Data and Secure Data Management with Blockchain Technology. International Journal of Intelligent Systems and Applications in Engineering, 12(20s), 808–813. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5305

Issue

Vol. 12 No. 20s (2024)

Section

Research Article

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