A biometric-authenticated wearable
system for remote monitoring,
chronic disease management,
elderly care,
occupational therapy, and
mental health rehabilitation is disclosed. The
system uses
fingerprint, facial, and voice recognition to securely associate physiological data with individual users. It monitors
vital signs including
heart rate,
oxygen saturation, movement, and stress indicators, and transmits data to EMR / EHR systems in real time with privacy compliance.
Machine learning modules assess
disease risk, detect mobility decline, and perform sentiment-based analysis of speech and behavior. The
system supports therapy compliance tracking across wellness programs and
daily living tasks. The system may optionally employ large language models (LLMs) to enhance contextual understanding and sentiment interpretation from unstructured speech or text inputs. Real-time alerts are generated for health anomalies or non-compliance, enhancing clinical interventions. This integrated platform advances personalized and secure care through biometric
authentication,
predictive analytics, and seamless EMR / EHR integration.