AI-powered Home Healthcare Assistant

Inspiration

Millions of homebound patients, like John, receive lab reports but struggle to interpret them without immediate access to a doctor. Many also rely on wearable devices for health tracking but lack a system to analyze trends, generate actionable insights, and send alerts in case of emergencies. Our goal was to bridge this gap with an AI-powered home healthcare assistant that provides structured health guidance and real-time monitoring, ensuring proactive and accessible care.

What it does

Our AI-powered home healthcare assistant helps patients understand their lab reports, monitor their vitals in real-time, and receive emergency alerts when necessary. The system:

• Accepts patient lab report inputs and generates a structured six-section healthcare plan with personalized recommendations.
• Uses a machine learning model to classify cardiovascular risk and refine health recommendations accordingly.
• Connects with wearable devices to track vitals like heart rate and oxygen levels, storing this data in AWS and visualizing it through Grafana.
• Triggers automatic alerts to emergency contacts and healthcare providers when critical health thresholds are breached.

How we built it

• Machine Learning Model: Trained to classify cardiovascular risk based on patient data.
• Streamlit Frontend: Developed an interactive and user-friendly interface for patients to input their lab report details.
• AWS & Grafana: Built a backend system to store and visualize wearable health data, allowing real-time monitoring.
• Automated Alert System: Implemented a mechanism that notifies emergency contacts and healthcare providers when vital signs exceed safe thresholds.

Challenges we ran into

• Data Accessibility: Finding publicly available datasets that accurately reflect real-world patient conditions was challenging.
• Wearable Device Integration: Ensuring seamless synchronization between wearable devices and our backend system required significant optimization.
• Threshold Sensitivity: Balancing the alert system to avoid false positives while ensuring critical issues are detected reliably.

Accomplishments that we're proud of

• Successfully built a machine learning-powered healthcare assistant that provides both proactive and reactive healthcare support.
• Integrated real-time health monitoring with AWS and Grafana for continuous patient tracking.
• Developed a user-friendly Streamlit application designed for accessibility, even for non-technical users.
• Implemented a fully functional emergency alert system to notify caregivers and healthcare providers in case of medical emergencies.

What we learned

• Healthcare AI Applications: Gained deeper insights into how AI can be used to enhance home healthcare and bridge gaps in medical accessibility.
• Cloud-Based Health Monitoring: Learned to build scalable and real-time data processing systems using AWS and Grafana.
• User Experience in Healthcare: Understood the importance of designing an intuitive, easy-to-use interface for patients and caregivers.

What's next for AI-powered Home Healthcare Assistant

• Expanding ML Capabilities: Improve the predictive model to assess risks for a broader range of diseases.
• Wearable Device Integration: Expand compatibility to include more health-tracking devices.
• Multilingual Support: Develop support for multiple languages to enhance accessibility for diverse communities.
• Doctor & Caregiver Portal: Introduce a dedicated portal for doctors and caregivers to monitor patient data and intervene when necessary.

Healthcare should be proactive, not reactive. Our AI-powered assistant ensures that every second counts.

Built With

• amazon-web-services
• grafana
• python
• streamlit