Continuously collects health data from wearable devices such as heart rate, blood pressure, and activity levels.
Uses machine learning algorithms to analyze trends, predict health events, and generate insights.
Provides encrypted data storage and transmission with compliance to healthcare regulations.
Seamlessly integrates with major electronic health record systems like Epic and Cerner.
Offers mobile apps and patient portals for data viewing, communication, and reminders.
Allows clinicians to set personalized thresholds and notifications for vital signs.
Supports deployments from small clinics to large hospital networks with flexible architecture.
Monitor patients with conditions like diabetes, hypertension, or COPD remotely to track vitals and adjust treatments.
Track recovery after surgeries to prevent complications and reduce hospital readmissions through continuous monitoring.
Ensure safety and health monitoring for aging populations at home, detecting falls or health declines early.
Collect real-time data from participants in research studies for accurate outcome measurements and compliance tracking.
Continue monitoring after discharge to support transition care and improve patient outcomes.
Use activity and sleep data to support mental health assessments and interventions for conditions like depression.
Remote monitoring for infectious diseases to limit exposure and manage symptoms in quarantine settings.
Implement corporate or community health initiatives using wearables to promote fitness and preventive care.
Monitor children with chronic illnesses under parental supervision, ensuring timely medical attention.
Track progress in physical therapy and recovery programs to optimize treatment plans and motivate patients.
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