Biomedical Signal Processing & AI

CVD Risk Assessment

Enter your vitals below. Our CNN model — trained on clinical PPG-BP datasets — detects cardiovascular disease risk in seconds with 95% accuracy.

⚠️ For educational purposes only. Always consult a doctor for medical decisions.

1. Vitals

2. Health History

3. Processing

4. Results

Basic Vitals

Enter your personal measurements. BMI will be automatically calculated from your height and weight.

Age 18–100 years

Sex

Height cm

Weight kg

BMI auto-calculated

Blood Pressure & Health History

Enter your latest blood pressure and heart rate readings. These are the core signals from your PPG dataset used for CVD detection.

Systolic BP mmHg — upper number

Diastolic BP mmHg — lower number

Heart Rate beats per minute

Medical Conditions

Select Yes / No for each. These are direct risk factors used in the CVD scoring model.

Hypertension (High Blood Pressure)

Diabetes

Cerebral Infarction (Stroke)

Cerebrovascular Disease

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Analysing Your Data

Running your inputs through the CVD detection pipeline...

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Loading patient vitals

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Signal preprocessing (PMA + Notch + Savitzky-Golay)

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Feature extraction (time + frequency domain)

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BP classification (AHA guidelines)

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CVD risk scoring (CNN model — 95% accuracy)

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Generating personalised precautions