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AKTU AI in Bio-Medical Instrumentation Lab (BIC751) Syllabus PDF – B.Tech 4th Year
AI in Bio-Medical Instrumentation Lab BIC751
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- Semester 7
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Official AKTU syllabus of AI in Bio-Medical Instrumentation Lab (BIC751) for B.Tech 4th Year – 1 credits, L-T-P 0-0-2. Read the unit-wise course content, course outcomes, evaluation pattern and recommended books online, or download the PDF.
Syllabus — AI in Bio-Medical Instrumentation Lab
Download PDFBIC751 · 1 credits · L-T-P 0-0-2
List of Experiments
- ECG Signal Classification Using Machine Learning Objective: Record ECG signals and classify them as normal or abnormal using ECG sensor, DAQ module, MATLAB/Python.
- EEG-Based Brain State Detection Objective: Identify mental states like relaxed, focused, or drowsy using EEG headset (e.g., Emotiv, NeuroSky), PC with Python.
- Glucose Level Prediction from Physiological Parameters Objective: Predict glucose levels using non-invasive data (e.g., pulse, BP) using Pulse sensor & BP monitor.
- Heart Rate Monitoring & Arrhythmia Detection Objective: Detect arrhythmia from heart rate variability (HRV) using Pulse sensor or ECG module.
- Biomedical Image Segmentation (e.g., X-ray or MRI) Objective: Segment key organs or anomalies using AI. [Tool: Open-source datasets (e.g., NIH Chest X- ray), Python with Keras/TensorFlow]
- Oximeter Signal Analysis and SpO₂ Estimation Objective: Analyze photoplethysmogram (PPG) signals for oxygen saturation using Pulse oximeter module.
- AI-Based Gait Analysis Using Wearable Sensors Objective: Detect abnormal walking patterns for early disease detection using IMU sensors, Smartphone sensors.
- To study Auditory system check-up using Audiometer.
- To Measure Skin Conductance and Skin Potential using Galvanic Skin Response Module,
- Conduct Electromyogram test using EMG biofeedback Trainer.
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