Master of Technology (M.Tech) in Biomedical Signal Processing and Instrumentation

M.Tech in Biomedical Signal Processing and Instrumentation Course Details

Biomedical Signal Processing and Instrumentation is a discipline where principles of biomedical engineering, electronics, and medical instrumentation are used to analyze biological signals. This two-year postgraduate degree is aimed at engineers and scientists who want to develop, analyse, and improve on existing technologies related to medical devices like diagnostic systems, imagining modalities etc. that are based on biological signals such as ECG, EEG, EMG, MRI signals, CT signals, or else ultrasound signals commonly used in hospitals.

Biomedical signal processing and instrumentation are crucial in early detection of diseases, patient care, disease management, and medical science research in the current technology-enabled system of health care. With the rapid advancements in digital healthcare, AI-assisted diagnosticians, wearable medical devices, telemedicine, and smart hospitals, there will be more opportunities for versatile BMEs who have strengths in signal processing and instrumentation around the world.

M.Tech Biomedical Signal Processing and Instrumentation is advanced in the subjects of digital signal processing, medical image processing, bio sensor technology, biomedical instrumentation design, physiological signal analysis, embedded systems for healthcare health care. The programme places a strong emphasis on theoretical foundations and practical experience through labs, projects, internships, careers support, and a research-based dissertation.

Graduates from this programme are prepared to work at technology and medicine interface, working with doctors, researchers, and healthcare organisations in the creation of state-of-the-art diagnostic and therapeutic tools. It is second to none for candidates seeking careers in R&D institutions, research labs, medical device industries, hospitals, and academia.

Key Areas of Study

• Biomedical Signal Processing

• Medical Image Processing

• Biomedical Instrumentation

• Biosensors and Transducers

• Digital Signal Processing

• Embedded Systems in Medical Devices

• Radiological Imaging Systems (MRI, CT, and Ultrasound)

• Healthcare Informatics

• Artificial Intelligence and Machine Learning in Biomedical Applications