Biomedical Instrumentation and Signal Processing

Biomedical signal processing involves acquiring and preprocessing physiological signals and extracting meaningful information to identify patterns and trends within the signals. Sources of biomedical signals include neural activity, cardiac rhythm, muscle movement, and other physiological activities. Biomedical instrumentation is an application of biomedical engineering, which focuses on the devices and mechanics used to measure, evaluate, and treat biological systems. It focuses on the use of multiple sensors to monitor physiological characteristics of a human or animal.

Sub-Topics

  • Medical Devices

Biomedical Instrumentation is a broad area of research that basically deals with the measurement and analysis/ control of bio-parameters/ signals, from an engineering perspective. Clinically these could be termed diagnosis and therapy. 

The devices which assist clinicians in the diagnosis and treatment of diseases are called Medical Devices. Medical devices are not only confined to diagnosis and treatment but also extend their boundary to the rehabilitation/ assistive devices domain. The type of diagnostic, treatment and assistive devices varies from (i) simple thermometers to sophisticated imaging systems, (ii) simple scissors/ knives of Operation Theatres to diathermy units and further to life-saving devices like pacemakers and defibrillators (iii) simple to complex such as walking sticks to high-end wheelchairs respectively. 

The research groups in our department work on developing medical devices on different scales of dimension from nano to macro by drawing the benefits of different present-day technologies such as sensors, materials, electronics, communication, IoT, etc.

  • Cognitive Neuroscience

Cognitive neuroscience is the field of study focusing on the neural substrates of mental processes. It is at the intersection of psychology and neuroscience, but also overlaps with physiological psychology, cognitive psychology and neuropsychology. It combines the theories of cognitive psychology and computational modelling with experimental data about the brain. Some sub-topics/fields are given below:

  • Subcortical neurotransmitter systems of arousal.
  • Neural basis of sign language.
  • Neural basis of working memory in monkeys and humans.
  • Role of the cerebellum in cognition.
  • Neural substrates for implicit memory.
  • Sleep and dreaming.
  • Mechanisms of attention.
  • Effects of stress on the brain.
  • Hemispheric specialization for language.
  • Hemispheric specialization in animals.
  • William’s syndrome and its implications for cognitive architecture
  • Genetic studies of language
  • Perception of emotion
  • Role of the cerebellum in timing.
  • Movement parameters coded by individual neurons in cortex.
  • Neuroimaging

Neuroimaging is a discipline that studies the structure and function of the nervous system by means of imaging technology, and where the images of the brain can be obtained in a non-invasive way. It explores a series of mechanisms such as cognition, information processing, and brain changes in the pathological state. In recent years, the neuroimaging has developed rapidly and become a powerful tool for medical research and diagnosis. With the increasing prevalence of neurological diseases, higher requirements have been put forward for neuroimaging technology and subsequent data analysis, and many advances have been made in this field. Some related sub-topics:

  • Baby Brain Research
  • Biomagnetic Imaging
  • Brain Arteriovenous Malformations
  • BrainChange Study
  • Cancer Metabolic Imaging and Therapy    
  • Study for Imaging of Neurodegenerative Diseases
  • Imaging Research for Neurodevelopment
  • Multimodal Metabolic Brain
  • Neural Connectivity
  • Brain Imaging and EEG 
  • Measurement & Simulation in Biological Systems

Many biological phenomena of interest, such as the intracellular localization of molecules, morphogenesis, growth, and forest distribution dynamics involve a spatial component that calls for a spatiotemporal systems understanding. 

The term “Systems Biology” has been used to designate a number of different things. This ranges from biological applications of systems theory to automated high-throughput experiments followed by statistical data mining to computational modeling and simulation of biological processes. The common theme that seems to emerge in systems biology is a focus on dynamics and interactions, which are believed to cause the apparent “complexity” of life. Often, the goal is to formulate predictive models of these interactions from systematically collected quantitative data.

  • Medical Imaging

Medical imaging is the technique and process of imaging the interior of a body for clinical analysis and medical intervention, as well as visual representation of the function of some organs or tissues (physiology). Medical imaging seeks to reveal internal structures hidden by the skin and bones, as well as to diagnose and treat disease. Medical imaging also establishes a database of normal anatomy and physiology to make it possible to identify abnormalities. Although imaging of removed organs and tissues can be performed for medical reasons, such procedures are usually considered part of pathology instead of medical imaging.

Measurement and recording techniques that are not primarily designed to produce images, such as electroencephalography (EEG), magnetoencephalography (MEG), electrocardiography (ECG), and others, represent other technologies that produce data susceptible to representation as a parameter graph versus time or maps that contain data about the measurement locations. In a limited comparison, these technologies can be considered forms of medical imaging in another discipline.

  • Drug delivery

Transdermal drug delivery is a non-invasive method of drug administration. However, to achieve this, the drug has to pass through the complicated structure of the skin. The complex structure of skin can be modelled by an electrical equivalent circuit to calculate its impedance. This developed model can be used to predict transdermal drug delivery dosage. This is primarily an essential tool for the development of electrically controlled transdermal drug delivery techniques like Iontophoresis, Electroporation etc. Also, skin impedance models can be used for the study of various clinical conditions of the skin, health monitoring technologies, and other electrochemical impedance studies.

Associated Faculty Members

Significant Publications

  1. Jupitara Hazarika, Piyush Kant, Rajdeep Dasgupta, and Shahedul Haque Laskar, “Neural modulation in action video game players during inhibitory control function: an EEG study using discrete wavelet transform”, Biomedical Signal Processing and Control ,vol. 45, pp. 144-150, 2018.
  2. Jupitara Hazarika and Rajdeep Dasgupta, “Neural correlates of action video game experience in a visuospatial working memory task”, Neural Computing and Applications , vol. 32(8), pp. 3431-3440, 2020.
  3. Jupitara Hazarika, Piyush Kant, Rajdeep Dasgupta, and Shahedul H. Laskar, “EEG Wavelet Coherence Based Analysis of Neural Connectivity in Action Video Game Players in Attention Inhibition and Short-term Memory-retention Task”, Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering), vol. 12(4), pp. 324-338, 2018.
  4. Piyush Kant, Shahedul Haque Laskar, and Jupitara Hazarika, “Transfer learning-based EEG analysis of visual attention and working memory on motor cortex for BCI”, Neural Computing and Applications, pp. 1-12, 2022, Available Online.
  5. Piyush Kant, Shahedul Haque Laskar, Jupitara Hazarika, and Rupesh Mahamune, “CWT Based transfer learning for motor imagery classification for brain computer interfaces”, Journal of Neuroscience Methods, vol. 345, pp. 108886, 2020.
  6. Sudarsan Sahoo et. al., “A Device and A Method for Detecting Severe Acute Respiratory Syndrome (SARS) Coronavirus Based on Filtered Cough Sound Signals”, South African Patent No. 2022/01879, (Patent granted).
  7. Sudarsan Sahoo et. al., “A System for diagnosing the Cognitive Effect of Tele-series on the Human Brain using De-noised EEG Signals”, German Patent No. 202021106795.0, (Patent granted).
  8. Sudarsan Sahoo, Priyanuj Borthakur, Niharika Baruah and Bhaskar Pratim Chutia, “IoT and Machine Learning Based Health Monitoring and Heart Attack Prediction System”, Journal of Physics, vol. 1950(1), pp. 012056, 2021.
  9. Sudarsan Sahoo, J. K. Das, “Investigation of the Effect of Video Game Play on Cognitive Behaviour using Adaptive Noise Cancellation and Wavelet Transform”, Indian Journal of Science and Technology, vol. 10(27), 2017.
  10. S.H. Choudhury, A. Kumar, S. H. Laskar, “Biometric Authentication through Unification of Finger Dorsal Biometric Traits”, Information Science, Elsevier, vol. 497, pp. 202-218, 2019.
  11. Manas Kumar Bera, Pintu Kumar, Rajkumar Biswas, “Robust Control of HIV Infection by Antiretroviral Therapy: A Super-twisting Sliding Mode Control Approach”, IET Systems Biology, vol. 13(3), pp. 120-128, 2019.
  12. Bhabani Shankar Dey, Manas Kumar Bera, Binoy Krishna Roy, “Nonlinear active control of a cancerous tumour”, International J. Engineering and Technology, vol. 7(2.21), pp. 72-76, 2018.
  13. Dhruba Jyoti Bora, Rajdeep Dasgupta, “Numerical simulation of iontophoresis for in-silico prediction of transdermal drugs in the dermal layers using skin impedance values”, Computer Methods and Programs in Biomedicine, vol. 214, pp. 106551, 2022. 106551.
  14. Dhruba Jyoti Bora, Rajdeep Dasgupta, “Estimation of skin impedance models with experimental data and a proposed model for human skin impedance”, IET Systems Biology, vol. 14(5), pp. 230-240, 2020.
  15. Dhruba Jyoti Bora, Rajdeep Dasgupta, “Various skin impedance models based on physiological stratification”, IET Systems Biology, vol. 14(3), pp. 147-159, 2020.
  16. A. Sekhar, S. Biswas, R. Hazra, A. Sunaniya, A. Mukherjee and L. Yang, “Brain tumor classification using fine-tuned GoogLeNet features and machine learning algorithms: IoMT enabled CAD system”, IEEE Journal of Biomedical and Health Informatics, vol. 26(3), pp. 983-991, 2022.
  17. S. Biswas, R. Hazra and A. Sirvee, “A COVID-19 Detection System and Method using a CNN Model”, Patent Number: 2021105722, Australian Patent (Status: Granted on 27/10/21).
  18. E. Ramanujam, Thingaran Perumal, Shankar K., “Fall Detection Systems in Night”, IEEE Computer, 2021.
  19. Shankar. K. et al., “A DEVICE FOR ASSISTING RESPIRATION”, Indian Patent, Application No. 202231035556A (Status: Published and FER received)