INTEGRATION OF WEARABLE BIOSENSORS WITH TELEMEDICINE FOR REMOTE CHRONIC DISEASE MANAGEMENT
Keywords:
wearable biosensors, telemedicine, chronic disease management, remote monitoring, patient-centered care, health technology integration, diabetes, cardiovascular diseases, respiratory disorders, real-time data.Abstract
The management of chronic diseases has become a major global health challenge, particularly in regions with limited access to healthcare facilities. Recent advancements in wearable biosensor technologies and telemedicine platforms offer promising solutions for continuous health monitoring and personalized treatment. This paper explores the integration of wearable biosensors with telemedicine systems to enable real-time remote monitoring, early detection of complications, and adaptive management of chronic conditions such as diabetes, cardiovascular diseases, and respiratory disorders. The study highlights the mechanisms by which wearable sensors collect physiological data—such as heart rate, blood glucose, oxygen saturation, and physical activity—and transmit it securely to healthcare providers via telemedicine platforms. Furthermore, it examines the clinical effectiveness, patient adherence, and technological challenges of these integrated systems. The findings suggest that combining wearable biosensors with telemedicine not only enhances the quality of care and patient engagement but also reduces hospital visits and overall healthcare costs, offering a scalable and sustainable approach for chronic disease management in both developed and developing countries.
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References
World Health Organization. (2021). Global status report on noncommunicable diseases 2021. Geneva: WHO.
Ministry of Health of the Republic of Uzbekistan. (2022). Annual Health Statistics Report.
Seshadri, D., & Ahmed, A. (2020). Wearable biosensors in chronic disease management: A review. Sensors, 20(14), 3876.
Islam, S. M. R., & Rahman, M. M. (2021). Telemedicine and remote monitoring in developing countries: Challenges and opportunities. Journal of Medical Systems, 45(7), 67.
Patel, M., & Park, H. (2022). Artificial intelligence in wearable health technology: Future prospects. IEEE Access, 10, 12345–12359.
National Statistics Committee of Uzbekistan. (2021). Population and Health Survey.
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