Deep Learning-Enhanced Polymer-Based Wearable Biosensors for Continuous Health Tracking via IoT

Year : 2025 | Volume : 13 | Special Issue 06 | Page : 18 31
    By

    Manoj M.,

  • Remya M.,

  • Shady Gomaa Abdulaziz,

  • Wedad Obaidallah Alahamade,

  • Asmaa Hatem Rashid Abogamous,

  • Subarno Bhattacharyya,

  1. Assistant Professor, Department of Computer Science & Engineering, Jawaharlal College of Engineering & Technology, Palakkad district, Kerala, India
  2. Assistant Professor, Department of Computer Science & Engineering, Jawaharlal College of Engineering & Technology, Palakkad district, Kerala, India
  3. Assistant Professor, Department of Computer Science, University College of Umluj, University of Tabuk, Tabuk, Saudi Arabia
  4. Assistant Professor, Department of Computer Science and Systems, Applied College, Taibah University, Medina, Saudi Arabia
  5. Assistant Professor, Department of Computer Science and Systems, Applied College, Taibah University, Medina, Saudi Arabia
  6. Assistant Director, Office of Digital Learning and Online Education, O.P. Jindal Global University, Sonipat, Haryana, India

Abstract

The rapid proliferation of wearable biosensor technologies has transformed approaches to real-time health monitoring, yet challenges persist in achieving both mechanical robustness and reliable, continuous data analytics in dynamic environments. Conventional polymer-based sensing systems often fall short due to limited signal fidelity, inadequate adaptive analytics, or insufficient integration with secure, low-latency IoT frameworks. Addressing these deficiencies, this work introduces a flexible, deep learning-enhanced wearable biosensor platform that combines a nanostructured polymer composite sensor array, embedded hybrid CNN-LSTM analytics, and seamless IoT connectivity. The system is designed to autonomously capture and classify physiological events in real time, leveraging advanced signal conditioning and on-device neural inference for robust artifact rejection and precise event detection. A modular wireless interface supports both Bluetooth Low Energy and Wi-Fi transmission, enabling continuous, secure data flow to mobile and cloud endpoints. Experimental validation demonstrates that the proposed device sustains over 1,000 cycles of mechanical deformation with less than 3% resistance drift, while achieving a biosignal classification accuracy of 98.3% and average inference latency of 134 milliseconds on embedded hardware. Streaming trials show stable packet delivery with packet loss maintained below 1% across extended operation. By uniting advanced polymer engineering with explainable AI and resilient IoT design, this platform establishes a new standard for continuous, high-fidelity health monitoring in wearable formats, with significant implications for personalized medicine and smart healthcare infrastructure.

Keywords: flexible polymer biosensor, nanocomposite, deep learning analytics, IoT health monitoring, wearable sensor integration.

[This article belongs to Special Issue under section in Journal of Polymer and Composites (jopc)]

aWQ6MjMwNDIzfGZpbGVuYW1lOjM4ZmFhYjdiLWZpLmF2aWZ8c2l6ZTp0aHVtYm5haWw=
How to cite this article:
Manoj M., Remya M., Shady Gomaa Abdulaziz, Wedad Obaidallah Alahamade, Asmaa Hatem Rashid Abogamous, Subarno Bhattacharyya. Deep Learning-Enhanced Polymer-Based Wearable Biosensors for Continuous Health Tracking via IoT. Journal of Polymer and Composites. 2025; 13(06):18-31.
How to cite this URL:
Manoj M., Remya M., Shady Gomaa Abdulaziz, Wedad Obaidallah Alahamade, Asmaa Hatem Rashid Abogamous, Subarno Bhattacharyya. Deep Learning-Enhanced Polymer-Based Wearable Biosensors for Continuous Health Tracking via IoT. Journal of Polymer and Composites. 2025; 13(06):18-31. Available from: https://journals.stmjournals.com/jopc/article=2025/view=230426


Browse Figures

References

  1. Yoon, J., Kwon, N., Lee, Y., Kim, S., Lee, T., and Choi, J.-W., “Nanotechnology-Based Wearable Electrochemical Biosensor for Disease Diagnosis,” ACS Sensors, vol. 10, no. 3, pp. 1675–1689, Mar. 2025, doi: 10.1021/acssensors.4c03371.
  2. Murugesan Chandran, M., Veerapandian, M., Dhanasekaran, B., Govindaraju, S., and Yun, K., “Advanced nanomaterials for health monitoring and diagnostics in next-generation wearable sensors,” Mater. Sci. Eng. R Rep., vol. 165, p. 101015, 2025, doi: 10.1016/j.mser.2025.101015.
  3. Huang, R., Tian, S., Cai, H., Bao, Y., Zhang, D., Li, Q., and Lin, Z., “Microchannel-based portable sensor for p53 gene based on CRISPR/Cas12a using multimeter as readout,” Sens. Actuators B Chem., vol. 13, p. 138274, 2025, doi: 10.1016/j.snb.2025.138274.
  4. Abhinav, V., Basu, P., Verma, S. S., Verma, J., Das, A., Kumari, S., Yadav, P. R., and Kumar, V., “Advancements in Wearable and Implantable BioMEMS Devices: Transforming Healthcare Through Technology,” Micromachines, vol. 16, no. 5, p. 522, 2025, doi: 10.3390/mi16050522.
  5. Pereira, C. R., Pereira, A. M., Teixeira, J. S., Sousa, A. R., Queirós, G. P., Costa, R. S., and Nunes, M. S., “Advanced energy storage systems as power sources for biosensing technologies,” 2025, doi: 10.1016/bs.pmbts.2025.05.012.
  6. Cha, S., Choi, M. Y., Kim, M. J., Sim, S. B., Haizan, I., and Choi, J.-H., “Electrochemical Microneedles for Real-Time Monitoring in Interstitial Fluid: Emerging Technologies and Future Directions,” Biosensors, vol. 15, no. 6, p. 380, 2025, doi: 10.3390/bios15060380.
  7. Nguyen, T. K. A., Nguyen, V. T., Huynh, T. V., Yi-Hui, H., Doong, R.-A., and Hsieh, J. C.-H., “Constructing an ultrasensitive electrochemical sensor based on N, S-codoped graphene quantum dots decorated Au-nanostar for MCF-7 breast cancer diagnostic,” Chem. Eng. J., vol. 72, p. 165771, 2025, doi: 10.1016/j.cej.2025.165771.
  8. Mu, G., et al., “Recent advancements in wearable sensors: integration with machine learning for human–machine interaction,” RSC Adv., vol. 15, pp. 7844–7854, Mar. 2025, doi: 10.1039/D5RA00167F.
  9. Hussain, S., Ramadan, Q., and Zourob, M., “Smart wearable photonic array biosensor for human sweat analysis,” Soft Sci., vol. 5, p. 21, Apr. 2025, doi: 10.20517/ss.2025.02.
  10. Laochai, T., et al., “Touch–based potentiometric sensors for simultaneous detection of urea and ammonium from fingertip sweat,” Sens. Actuators B Chem., p. 135898, 2024, doi: 10.1016/j.snb.2024.135898.
  11. Duan, H., Peng, S., He, S., Tang, S.-Y., Wang, C. H., and Li, M., “Wearable Electrochemical Biosensors for Advanced Healthcare Monitoring,” Adv. Sci., vol. 12, no. 2, p. 2411433, Nov. 2024, doi: 10.1002/advs.202411433.
  12. Jiao, Y., and Yu, X., “Recent advances in wearable electrochemical sensors for in situ detection of biochemical markers,” Sci. China Mater., vol. 68, pp. 755–774, Feb. 2025, doi: 10.1007/s40843-024-2960-1.
  13. Dervisevic, M., Esser, L., Chen, Y., Alba, M., Prieto-Simon, B., and Voelcker, N. H., “High-density microneedle array-based wearable electrochemical biosensor for detection of insulin in interstitial fluid,” Biosens. Bioelectron., p. 116995, 2024, doi: 10.1016/j.bios.2024.116995.
  14. Dervisevic, M., Alba, M., Yan, L., Senel, M., Gengenbach, T. R., Prieto-Simon, B., and Voelcker, N. H., “Transdermal electrochemical monitoring of glucose via high-density silicon microneedle array patch,” Adv. Funct. Mater., vol. 32, no. 3, Art. no. 2009850, 2022.
  15. Dervisevic, M., Dervisevic, E., Esser, L., Easton, C. D., Cadarso, V. J., and Voelcker, N. H., “Wearable microneedle array-based sensor for transdermal monitoring of pH levels in interstitial fluid,” Biosens. Bioelectron., vol. 222, Art. no. 114955, 2023.
  16. Dervisevic, M., Jara Fornerod, M. J., Harberts, J., Zangabad, P. S., and Voelcker, N. H., “Wearable microneedle patch for transdermal electrochemical monitoring of urea in interstitial fluid,” ACS Sensors, vol. 9, no. 2, pp. 932–941, 2024.
  17. Flynn, C. D., Chang, D., Mahmud, A., Yousefi, H., Das, J., Riordan, K. T., Sargent, E. H., and Kelley, S. O., “Nanobiosensors for precision medicine,” Nat. Rev. Bioeng., vol. 1, pp. 560–577, 2023.
  18. Wu, J., Liu, H., Chen, W., Ma, B., and Ju, H., “Next-generation biosensing technologies,” Nat. Rev. Bioeng., vol. 1, pp. 346–361, 2023.
  19. Kitahama, Y., Egawa, M., Dwivedi, P. K., Yang, W., and Goda, K., “Next-gen biosensor platforms using photonics,” J. Phys. Photonics, vol. 6, no. 2, p. 021001, 2024.
  20. Saha, T., Del Caño, R., Mahato, K., De la Paz, E., Chen, C., Ding, S., Yin, L., and Wang, J., “Advances in wearable biosensor interfaces,” Chem. Rev., vol. 123, pp. 7854–7876, 2023.
  21. Li, S., Zhang, H., Zhu, M., Kuang, Z., Li, X., Miao, S., Zhang, Z., Lou, X., Li, H., and Xia, F., “Functional nanomaterials for wearable biosensors,” Chem. Rev., vol. 123, pp. 7953–7982, 2023.
  22. Dezhakam, E., Khalilzadeh, B., Mahdipour, M., Isildak, I., Yousefi, H., Ahmadi, M., Naseri, A., and Rahbarghazi, R., “Wearable biosensors for continuous health monitoring,” Biosens. Bioelectron., vol. 222, p. 114980, 2023.
  23. Ye, C., Lukas, H., Wang, M., Lee, Y., and Gao, W., “Molecularly imprinted polymer-based wearable biosensors,” Chem. Soc. Rev., vol. 53, pp. 7960–7982, 2024.
  24. Bai, J., Liu, D., Tian, X., Wang, Y., Cui, B., Yang, Y., Dai, S., Lin, W., Zhu, J., Wang, J., Xu, A., Gu, Z., and Zhang, S., “Wearable biosensors based on fiber-integrated electrodes for multiplexed sweat analysis,” Sci. Adv., vol. 10, p. eadl1856, 2024.
  25. Wang, X., Zhou, J., and Wang, H., “Flexible Electrochemical Biosensors for In Vivo Real-Time Monitoring,” Cell Rep. Phys. Sci., vol. 5, p. 101801, 2024.
  26. Wang, Y., Duan, H., Yalikun, Y., Cheng, S., and Li, M., “Smart wearable platforms for noninvasive health monitoring,” Talanta, vol. 266, p. 125026, 2024.
  27. Duan, H., Tang, S.-Y., Goda, K., and Li, M., “Electrochemical sensing technologies for wearable biosensor systems,” Biosens. Bioelectron., vol. 246, p. 115918, 2024.
  28. Ayankojo, J. Reut, and V. Syritski, “Aptamer-based electrochemical biosensors for wearable applications,” Biosensors, vol. 14, no. 1, p. 71, 2024.
  29. Nordin and A. A. Manaf, “Microfluidic biosensors: design and fabrication strategies,” in Microfluidic Biosensors, W. C. Mak and A. H. P. Ho, Eds. Academic Press, 2023, pp. 41–85.
  30. A. I. Azizan, S. Taufik, M. N. Norizan, and J. I. A. Rashid, “Flexible and transparent wearable electrochemical sensors,” Biosens. Bioelectron.: X, vol. 13, p. 100291, 2023.
Special Issue Subscription Original Research
Volume 13
Special Issue 06
Received 21/07/2025
Accepted 12/08/2025
Published 22/08/2025
Publication Time 32 Days
15


My IP

PlumX Metrics