Remote Patient Monitoring

Remote patient monitoring (RPM) uses digital technologies to track patient health remotely, aiming to improve care efficiency and reduce healthcare costs. Current research emphasizes leveraging artificial intelligence, particularly deep learning models (like CNNs, BiLSTMs, and transformer-based architectures) and federated learning, to analyze data from wearable sensors and other sources for accurate vital sign prediction, activity classification, and early disease detection. This approach addresses challenges like alarm fatigue and data privacy while offering significant potential for personalized treatment, improved clinical decision-making, and enhanced patient outcomes across various health conditions.