Development of solar powered smart telehealth system for conditioning monitoring in IMC

Devesh Raj. Mani

doi:10.31893/multiscience.2025391

Keywords:

Abstract

This paper introduces an innovative electronic model of the human respiratory system aimed at diagnosing common respiratory disorders such as bronchitis, emphysema, chronic obstructive pulmonary disease (COPD), and pleural effusion. Additionally, it proposes designing hardware capable of automatically controlling oxygen levels. The primary objective is to facilitate the solar powered automatic regulation of patient oxygen flow without the need for constant human supervision. The developed electrical model closely mimics the physiological structure of the human respiratory system, utilizing passive electrical components including resistors (R), inductors (L), and capacitors (C). The input impedance of this model is derived, and various time- domain responses are analyzed to evaluate airway and alveolar conditions. This assessment provides a qualitative evaluation of bronchitis, typically characterized by narrowed bronchi, and emphysema, often associated with air pollution and smoking. This study delves into different disease stages or levels, encompassing average, good, and affected conditions, to offer a comprehensive analysis. To ensure the stability and clinical relevance of the proposed model, a root localization technique is employed for real-time monitoring of the affected respiratory system. Root locus diagrams derived from this technique correspond to expected clinical phenomena in both healthy individuals and COPD patients. As such, this paper presents simulations to demonstrate various respiratory conditions and proposes the development of hardware for controlling oxygen levels.
References
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2. Carnì, D. L., et al. (2007). Blood oxygenation measurement by smartphone. IEEE Instrumentation & Measurement Magazine.
3. Devesh Raj, M., et al. (2020). Electrical modeling and analysis of human respiratory system. Bulletin of Scientific Research, 43–48. https://doi.org/10.34256/bsr2017
4. Fernandez de Canete, J., et al. (2021). Physical modelling and computer simulation of the cardiorespiratory system based on the use of a combined electrical analogy. Mathematical and Computer Modelling of Dynamical Systems, 27(1), 453–488. https://doi.org/10.1080/13873954.2021.1977335
5. Ghafarian, P., et al. (2016). A review on human respiratory modeling. Tanaffos, 15(2), 61–69.
6. Jaya Lakshmi, G., Ghonge, M., & Obaid, A. J. (2021). Cloud-based IoT smart healthcare system for remote patient monitoring. EAI Endorsed Transactions on Pervasive Health and Technology, 7(28), 1–11. https://doi.org/10.4108/eai.15-7-2021.170296
7. Neelakantan, S., et al. (2022). Computational lung modelling in respiratory medicine. Journal of the Royal Society Interface, 19(191), 20220062. https://doi.org/10.1098/rsif.2022.0062
8. Shaik, T., et al. (2023). Remote patient monitoring using artificial intelligence: Current state, applications, and challenges. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 13(2), 1–31. https://doi.org/10.1002/widm.1485
9. Tehrani, F. T. (2020). Mathematical model of the human respiratory system in chronic obstructive pulmonary disease. Healthcare Technology Letters, 7(6), 139–145. https://doi.org/10.1049/htl.2020.0060
10. Tran, A. S., H. Q., et al. (2021). Design, control, modeling, and simulation of mechanical ventilator for respiratory support. Mathematical Problems in Engineering, 2021, 1–15. https://doi.org/10.1155/2021/2499804

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to cite

Mani, D. R. (2025). Development of solar powered smart telehealth system for conditioning monitoring in IMC. Multidisciplinary Science Journal, 7(8), 2025391. https://doi.org/10.31893/multiscience.2025391

[1] Biswas, A. T., et al. (2012). An electrical model for bronchitis and emphysema of human respiratory system. International Journal of Modern Engineering Research (IJMER, 2, 3956–3961.

[2] Carnì, D. L., et al. (2007). Blood oxygenation measurement by smartphone. IEEE Instrumentation & Measurement Magazine.

[3] Devesh Raj, M., et al. (2020). Electrical modeling and analysis of human respiratory system. Bulletin of Scientific Research, 43–48. https://doi.org/10.34256/bsr2017

[4] Fernandez de Canete, J., et al. (2021). Physical modelling and computer simulation of the cardiorespiratory system based on the use of a combined electrical analogy. Mathematical and Computer Modelling of Dynamical Systems, 27(1), 453–488. https://doi.org/10.1080/13873954.2021.1977335

[5] Ghafarian, P., et al. (2016). A review on human respiratory modeling. Tanaffos, 15(2), 61–69.

[6] Jaya Lakshmi, G., Ghonge, M., & Obaid, A. J. (2021). Cloud-based IoT smart healthcare system for remote patient monitoring. EAI Endorsed Transactions on Pervasive Health and Technology, 7(28), 1–11. https://doi.org/10.4108/eai.15-7-2021.170296

[7] Neelakantan, S., et al. (2022). Computational lung modelling in respiratory medicine. Journal of the Royal Society Interface, 19(191), 20220062. https://doi.org/10.1098/rsif.2022.0062

[8] Shaik, T., et al. (2023). Remote patient monitoring using artificial intelligence: Current state, applications, and challenges. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 13(2), 1–31. https://doi.org/10.1002/widm.1485

[9] Tehrani, F. T. (2020). Mathematical model of the human respiratory system in chronic obstructive pulmonary disease. Healthcare Technology Letters, 7(6), 139–145. https://doi.org/10.1049/htl.2020.0060

[10] Tran, A. S., H. Q., et al. (2021). Design, control, modeling, and simulation of mechanical ventilator for respiratory support. Mathematical Problems in Engineering, 2021, 1–15. https://doi.org/10.1155/2021/2499804

Abstract

References

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