DL-Based Secure Wearable Scheme for Remote Patient Data Monitoring in Healthcare 4.0
Fenil Ramoliya, Krisha Darji, Rajesh Gupta, Riya Kakkar, Sudeep Tanwar, Aparna Kumari · 2023
The paper articulates an exploration into the integration of wearable devices for remote patient data monitoring, which marks a transformative shift in healthcare practices. This transition is underscored by user-centric interfaces and applications, enabling convenient remote monitoring. However, the escalating concern of patient data vulnerability to network breaches presents a substantial impediment. In response, we introduce the proposed scheme that harnesses Machine Learning (ML) and Deep Learning (DL) techniques. The main objective of the proposed scheme is to meet the exacting requirements of healthcare systems, aiming to fortify data integrity and confidentiality. Within this context, the proposed scheme unveils a sophisticated DL-driven detection model, adeptly tailored for discerning and countering data manipulation endeavors through a nuanced multi-label classification paradigm. Notably, the emphasis lies on safeguarding patient data privacy and security, which is paramount in today's information-rich landscape. The narrative seamlessly interweaves elements of wearable technology, sensor networks, advanced DL capabilities, and robust security measures, resulting in an innovative scheme. Finally, the proposed scheme is evaluated against various metrics such as accuracy and loss curve and F1, recall, and precision comparison.