Healthcare systems around the world face a common challenge: what happens after a patient leaves the hospital?
Post-operative patients may experience complications hours or days after discharge, and early warning signs can easily go unnoticed until the condition becomes serious.
To address this challenge, we built SentinelOp, an AI-powered monitoring system that allows patients to report symptoms through voice, text, or wound image uploads, while intelligent analysis continuously evaluates recovery risk.
SentinelOp acts as a digital recovery assistant, helping patients communicate symptoms while enabling clinicians to detect complications earlier.
After surgery, patients are often discharged with instructions such as:
- Monitor pain levels
- Watch for swelling or redness
- Check for fever
- Report unusual symptoms
However, several problems occur in practice:
- Patients forget or misunderstand instructions
- Symptoms are reported too late
- Hospitals cannot continuously monitor patients at home
- Minor symptoms may escalate into serious complications
SentinelOp was designed to bridge this gap between discharge and recovery.
SentinelOp is a conversational AI platform that performs automated post-operative check-ins with patients.
Patients can interact with the system in three different ways:
- Voice conversation
- Text input
- Image upload of surgical wounds
This multi-modal approach ensures that patients can communicate with the system in the way that is most comfortable for them.
SentinelOp supports three different input methods, making it flexible for different patient situations.
Patients can simply talk to the system.
Example conversation:
AI: “Hello Sarah, I’m checking on your recovery today. On a scale of 1 to 10, how would you rate your pain?”
Patient: “It’s around a 6 today, and the wound looks a bit swollen.”
The system converts speech into text and analyzes symptoms in real time.
Voice interaction is particularly useful for:
- elderly patients
- patients experiencing discomfort
- users who prefer speaking instead of typing
Not all patients want to speak aloud. SentinelOp also provides a text input field where patients can type their symptoms.
Example:
Patient message:
Pain around incision is about 7 today.
There is some redness near the stitches.
The AI processes the typed message in the same way it processes voice responses.
This option helps patients who:
- are in noisy environments
- prefer typing
- have limited microphone access
SentinelOp also allows patients to upload images of their surgical wound.
Patients may take a photo and upload it if they notice:
- redness
- swelling
- unusual discharge
- slow healing
The image can then be:
- reviewed by clinicians
- analyzed by AI models
- stored as part of the recovery record
This feature adds an important visual dimension to post-operative monitoring.
SentinelOp maintains a conversation history for each patient session.
This allows the system to ask contextual follow-up questions like:
- “You mentioned swelling yesterday. Has it improved today?”
- “Earlier you rated your pain as 8. Has the medication helped?”
This memory allows the interaction to feel more like a natural medical conversation rather than a static questionnaire.
As patients speak, type, or upload updates, the system analyzes the information to detect clinical warning signs.
Examples include:
- severe pain
- breathing difficulty
- heavy bleeding
- fever symptoms
When such symptoms appear, the system automatically raises the patient’s risk level.
SentinelOp continuously evaluates recovery risk using an internal risk model.
Risk levels include:
Low Risk
- symptoms consistent with normal recovery
Medium Risk
- symptoms requiring closer monitoring
High Risk
- possible complications needing urgent attention
Risk levels are updated dynamically throughout the conversation.
If high-risk symptoms are detected, SentinelOp generates alerts for healthcare providers.
Example triggers include:
- chest pain
- breathing difficulty
- heavy bleeding
- severe swelling or infection indicators
This allows clinicians to intervene early, potentially preventing serious complications.
SentinelOp integrates a conversational interface with backend clinical analysis.
Patient
│
├── Voice Input
├── Text Input
└── Image Upload
│
▼
Web Interface
│
▼
Backend API
│
▼
Conversation Processing
│
├── Symptom Detection
├── Risk Analysis
└── Image Review Pipeline
│
▼
Clinical Dashboard
This architecture enables real-time analysis and continuous monitoring.
Healthcare providers can monitor patient recovery through a dashboard that displays:
- patient information
- surgery type
- recovery timeline
- AI conversation transcript
- reported symptoms
- uploaded wound images
- current risk level
This gives clinicians a complete view of the patient’s recovery progress.
- easy voice or text interaction
- ability to upload wound images
- continuous monitoring after discharge
- automated daily check-ins
- earlier detection of complications
- better patient follow-up
- reduced readmission rates
- improved recovery monitoring
- scalable patient care systems
cd backend
python -m venv venv && venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env # fill in AWS credentials + DB details
uvicorn main:app --reload --port 8000cd frontend
npm install
npm run devSentinelOp can be extended with additional capabilities such as:
- automated wound image analysis
- wearable device integration
- medication reminders
- predictive complication models
These additions could further strengthen post-operative monitoring.
Recovery after surgery should not rely solely on occasional hospital visits.
SentinelOp demonstrates how AI-powered conversations, text reporting, and wound image uploads can provide continuous post-operative monitoring.
By combining voice interaction, text communication, visual reporting, and intelligent risk detection, SentinelOp offers a smarter and more proactive approach to patient recovery.
As digital healthcare continues to evolve, systems like SentinelOp may become essential tools for ensuring safer and more connected post-operative care.
SentinelOp — Intelligent Monitoring for Safer Recovery