Semester-wise syllabus for an M.Tech in Biomedical Engineering

Semester 1: Core Foundations 

Courses: 

1. Human Anatomy and Physiology

   - Systems physiology, cell biology, and biomechanics of tissues/organs. 

2. Biomedical Instrumentation 

   - Sensors, biosignal acquisition (ECG, EEG, EMG), and medical imaging basics (MRI, CT, ultrasound). 

3. Biomechanics 

   - Stress-strain analysis, gait analysis, prosthetics, and biomaterial mechanics. 

4. Medical Electronics 

   - Circuit design for medical devices, amplifiers, filters, and safety standards (IEC 60601). 

5. Research Methodology 

   - Technical writing, statistical tools (Python/MATLAB), and ethics in biomedical research. 

Labs: 

- Biomechanics Lab (motion capture, force plate analysis) 

- Medical Device Prototyping Lab (Arduino/Raspberry Pi for biosignal acquisition) 

Semester 2: Advanced Topics & Electives 

Core Courses: 

1. Medical Imaging Systems 

   - Advanced MRI/CT physics, image reconstruction algorithms, and AI in diagnostics. 

2. Biomaterials and Tissue Engineering

   - Biocompatibility, scaffolds, 3D bioprinting, and regenerative medicine. 

Electives (Examples): 

- Bioinformatics and Genomics (NGS data analysis, personalized medicine) 

- Rehabilitation Engineering (exoskeletons, neuroprosthetics) 

- Healthcare Robotics (surgical robots, assistive devices) 

- Neural Engineering (brain-computer interfaces, neural implants) 

- Clinical Engineering (hospital equipment management, FDA regulations) 

Labs: 

- Medical Imaging Lab (MATLAB/Python for image processing) 

- Biomaterials Testing Lab (tensile testing, cell culture techniques) 

Semester 3: Specialization & Project Work 

Electives (Examples): 

- AI/ML in Healthcare (predictive diagnostics, radiomics) 

- Nanomedicine (drug delivery, nanorobots) 

- Wearable Health Tech (smart sensors, IoT-enabled devices) 

- Cardiovascular Engineering (stents, pacemakers, hemodynamics) 

- Telemedicine and Digital Health (remote monitoring, EHR systems) 

Project/Dissertation: 

- Phase 1: Topic selection (e.g., AI-based cancer detection, low-cost prosthetic design, wearable glucose monitors), literature review, and proposal. 

- Seminars: Presentations on trends like neural implants, CRISPR-based therapies, or AI-driven drug discovery. 

Semester 4: Thesis/Project Completion 

Thesis/Project: 

- Full-time focus on prototyping (e.g., medical device development), clinical simulations, or data-driven research (e.g., genomic analysis). 

- Final documentation, viva voce defense, and collaboration with hospitals/research institutes (e.g., AIIMS, ICMR). 

Additional Components:

- Industrial Internship (optional, with firms like Siemens Healthineers, GE Healthcare, or startups). 

- Workshops: Training in 3D bioprinting, FDA compliance, or AI tools (TensorFlow for medical imaging). 

Elective Tracks (Specializations): 

1. Medical Devices and Diagnostics

   - Wearables, point-of-care devices, and imaging systems. 

2. Biomaterials and Tissue Engineering

   - Smart biomaterials, organ-on-a-chip, and regenerative therapies. 

3. AI and Data Science in Healthcare

   - Predictive analytics, radiomics, and personalized medicine. 

4. Rehabilitation and Assistive Technologies

   - Prosthetics, exoskeletons, and assistive robotics.