Platform Overview
The ASTA Platform combines computer vision, AI pipelines, and scalable infrastructure to transform patient monitoring and care delivery.
How It Works
Our cutting-edge platform combines multi-parameter cameras, cloud computing, and AI to deliver unparalleled smart monitoring capabilities
Computer Vision AI Cameras
Advanced AI-powered cameras capture patient vitals through computer vision
Intelligent Processing
Real-time AI analysis processes visual data and extracts vital signs
Smart Dashboard
Processed data displayed on intuitive dashboards for medical professionals
Instant Alerts
Automated alerts sent to doctors and authorized medical staff
AI-Native Smart Ward Platform
Our Software as a Medical Service platform combines cloud-native microservices architecture with advanced AI algorithms trained on diverse healthcare datasets for clinical-grade accuracy.
Real-time Monitoring
Continuous patient surveillance with sub-second response times
Intelligent Alerts
AI-powered notifications that reduce false positives by 90%
Regulatory Compliance
HIPAA, and international healthcare standards compliant
Seamless Integration
Works with existing hospital infrastructure and EMR systems
Live Platform Status
AI Engine Performance
Advanced AI Engine Capabilities
Our proprietary AI algorithms continuously learn from real-world clinical environments to improve accuracy and reduce false positives.
Deep Learning Models
Advanced neural networks trained on millions of medical data points
Real-time Processing
Sub-second analysis and prediction with clinical-grade accuracy
Adaptive Learning
Continuously improves from new data while maintaining privacy
System Design
A modular AI-first pipeline that translates visual input from medical monitors into structured vitals in real time, without proprietary integrations.
Approach
In post-operative wards and critical care settings, continuous monitoring of patients is essential yet still largely dependent on manual observation by nursing staff. While clinicians strive to maintain close oversight, it’s not humanly feasible to monitor every patient continuously, especially in high-volume environments.
To address this gap, our platform introduces an AI-powered, camera-based vital sign monitoring system designed to operate continuously and autonomously. Unlike conventional systems that rely on proprietary integrations or hardware, our approach is completely vendor-agnostic, offering real-time performance with minimal latency.
The system architecture includes four core components:
- Screen Segmentation: Isolating monitor displays within the video stream
- Monitor Detection: Identifying relevant patient monitor areas in each frame
- Vitals Detection & OCR: Extracting numerical vital signs via robust optical character recognition
- Layout Classification: Using an encoder to generate embedding vectors for detecting and adapting to diverse monitor formats
To ensure reliable performance at scale, the system leverages message queues and parallelized processing pipelines — reducing computational load and enabling real-time throughput. This architecture supports both structured hospital environments and resource-constrained deployments like field clinics or temporary wards.
Overall, this solution offers a non-invasive, low-cost, and rapidly deployable alternative to traditional vitals monitoring, ideal for telemedicine, remote observation, and hybrid AI-assisted care models.
Behind the System: AI + Computer Vision in Practice
This section walks through the machine intelligence powering ASTA Health Tech’s real-time monitoring from detection pipelines to OCR, layout understanding, and performance optimization.
Abstract: Continuous patient monitoring is essential in modern healthcare but traditional systems are expensive, closed, and hardware-dependent. ASTA’s system introduces a lightweight, AI-powered visual pipeline that interprets real-time vitals from patient monitors using only camera input.
Designed to be infrastructure-agnostic, the system supports multiple device types, layouts, and conditions — no vendor lock-in, no need for direct integrations. The intelligent architecture uses layout classifiers, perspective correction, and optimized OCR to enable scalable deployment across both high-end hospitals and low-resource care environments.
Evaluation Metrics
We evaluate our system using standard metrics: Precision (P) reflects how many of the detected values were correct, Recall (R) indicates how many actual values were successfully detected, and F1 Score is the harmonic mean of precision and recall — balancing both. Intersection over Union (IoU) is used for segmentation to measure the overlap between predicted and actual regions.
| Overall Performance | ||
|---|---|---|
| Component | Metric | Score |
| Screen Segmentation | IoU | 92.3% |
| Vital Detection (OCR) | Precision, Recall, F1 | 1.000, 1.000, 1.000 |
| Layout Classification | Accuracy | 100% |
| Per-Label Scores | ||
| Label | GT, Pred | Precision, Recall, F1 |
| NBPMap | 75, 75 | 1.000, 1.000, 1.000 |
| NBPDiastolic | 71, 71 | 1.000, 1.000, 1.000 |
| NBPSystolic | 71, 71 | 1.000, 1.000, 1.000 |
| SpO2 | 64, 64 | 1.000, 1.000, 1.000 |
| Heart Rate | 84, 84 | 1.000, 1.000, 1.000 |
| Respiration Rate | 82, 82 | 1.000, 1.000, 1.000 |
| Pulse | 37, 37 | 1.000, 1.000, 1.000 |
ASTA Health Tech builds AI-native infrastructure for scalable, cost-effective care. This is one of many intelligence-first modules in our broader platform transforming medical vision into actionable data.