Centre for Affective and Neurocomputing (CAN)


The Centre for Affective and Neurocomputing (CAN) is an initiative for conducting advanced research in the areas of Affective computing, Neurocomputing and Biomedical devices. Affective computing is a modern interdisciplinary branch of computer science that refers to the study and development of systems that can recognize, process and simulate emotions. Neurocomputing (also known as computational neuroscience) is a field that uses mathematical and computational methods to gain a greater understanding of the normal and abnormal functioning of different brain regions. Medical devices help in the diagnosis, treatment and management of various diseases, in preventing injuries during medical procedures and in improving the quality of life of those afflicted with incurable medical conditions. Specifically, CAN is focused on four areas (i) Computer-based brain research to assist the treatment of addiction and related mental disorders (ii) Computer-based emotion research to assist mental healthcare specialists (iii) Development of computational emotion models for use in affectively intelligent systems (iv) Development of medical/assistive devices to prevent and manage medical conditions, with special focus on those arising from neurological deficits.

Computer-based brain research to assist the treatment of addiction and related mental disorders

Alcoholism is a rampant social evil, with women often being the worst sufferers. Post-traumatic stress disorder (PTSD) is a psychological illness affecting up to 70% of population affected by natural disasters. Nucleus accumbens (NAc) is a brain structure that is closely associated with both alcoholism and PTSD. It is also involved in other addictions like drug abuse and smoking as well as common and severe psychiatric disorders, such as depression, schizophrenia, obsessive-compulsive disorder, bipolar disorder, attention deficit/ hyperactivity disorder and anxiety disorders. Computer-based research can give insights into the normal and abnormal functioning of NAc that can lead to the better treatment of the disorders associated with it. CAN studies the normal and abnormal functioning of NAc by developing computational models and running simulations so as to gain an improved understanding of its functioning and suggest methods and techniques for more effective treatment of addiction and the mental disorders associated with Nac.

Computer-based emotion research to assist mental healthcare specialists

Globally, over 10% of the population are affected by mental disorders of which a major component is made up of affective disorders. Affective disorders such as depression, bipolar disorder, and emotion dysregulation disorder and women-specific disorders like post-partum depression and premenstrual dysphoric disorder lead to several lost work days and increase the suicide-risk of the sufferers, greatly affecting families and the society as a whole emotionally and economically. Further, pandemics like COVID-19 and disasters like floods, cyclones and landslides take a great toll on emotional health. A greater understanding of the functioning of the human emotion system is necessary to tackle the problems that arise when it functions abnormally or when it is put under severe stress. Computer-based human emotion research is a useful tool to achieve this. CAN employs computational methods and techniques, supported by experiments, to study the emotion system and contribute towards a better understanding of emotional disorders and thus assist mental health specialists in treating and managing them optimally.

Development of computational emotion models for use in affectively intelligent systems

The research at CAN also focuses on the clarification of concepts related to emotion, mood, personality, and attitude in ways that facilitate their use in computing, and the design and development of systems that can model and simulate human emotions. There is increasing realization that artificial systems need to be also emotionally intelligent if they have to interpret human emotions, empathize with them, understand their thinking and decision making, interact effectively with them, predict their actions and also make judgments and decisions like them. This requires the development of computational models of human emotion processes and systems that can simulate and predict human emotional state. Such models and systems are needed to impart synthetic emotions to artificial agents, as well as to deduce and estimate the types, intensities and time course of emotions in humans whom they monitor or interact with. CAN is involved in developing computational emotion models and emotion dynamics simulators that have potential applications in surveillance systems, human-computer interaction, robotics, games, virtual reality training and anywhere affectively intelligent systems are required.

Medical and assistive device development

Disorders, diseases and injuries to the nervous system can lead to a wide range of medical conditions from blindness to underactive urinary bladder, severely impacting the quality of life of the affected. Such conditions arise due to a variety of reasons including various diseases, personal injuries and traffic accidents. Also, some medical procedures, if done incorrectly, can cause long lasting damage to certain nerves. CAN is involved in the research and development of simple medical and assistive devices with an objective to prevent and manage various medical conditions, with special focus on those that arise from the diseases, disorders or injuries of the nervous system. These include medical devices to prevent nerve damage during certain medical procedures, assistive devices to improve the quality of life of the affected, as well as training devices to help the affected to get back to as normal a life as possible.


Contact person: Dr. John Eric Steephen, School of Digital Sciences.

e-mail: john.steephen@duk.ac.in

  • John Eric Steephen, B.Tech, M.Tech-Ph.D (IIT Bombay)
  • Mithun Padmakumar, B.Tech, M.Tech-Ph.D (IIT Bombay)
  • Joseph Tharion, MBBS, M.Tech-Ph.D (IIT Bombay)
  • Divya Rajan, B.Sc, MCA
Selected Member Publications and Patents
Affective computing
  • Steephen, J. E., Obbineni, S. C., Kummetha, S., & Surampudi, B. R. (2020). HED-ID: An affective adaptation model explaining the intensity-duration relationship of emotion, IEEE Transactions on Affective Computing, 11(4), 736 – 750. [Link] [Author’s version] [Search]
  •  Steephen, J. E. (2013). HED: A computational model of affective adaptation and emotion dynamics. IEEE Transactions on Affective Computing, 4(2), 197-210. [Link] [Author’s version] [Search]
Computational Neuroscience
  • Padmakumar, M., Brain, K. L., Young, J. S., and Manchanda, R. (2018). A four-component model of the action potential in mouse detrusor smooth muscle cell. PloS One, 13(1), e0190016. [Link] [Search]
  • Appukuttan, S., Padmakumar, M., Young, J. S., Brain, K. L., and Manchanda, R. (2018). Investigation of the syncytial nature of detrusor smooth muscle as a determinant of action potential shape. Frontiers in Physiology, 9, 1300. [Link] [Search]
  • Appukuttan, S., Padmakumar, M., Brain, K. L., and Manchanda, R. (2017). A method for the analysis of AP foot convexity: insights into smooth muscle biophysics. Frontiers in Bioengineering and Biotechnology, 5, 64. [Link] [Search]
  • Steephen, J. E. (2011). Excitability range of medium spiny neurons widens through the combined effects of inward rectifying potassium current inactivation and dopaminergic modulation. Neurocomputing, 74, 3884-3897. [Link] [Search]
  • Steephen, J. E., & Manchanda, R. (2009). Differences in biophysical properties of nucleus accumbens medium spiny neurons emerging from inactivation of inward rectifying potassium currents. Journal of Computational Neuroscience, 27, 453–470. [Link] [Search]
Cognitive Science
  • Steephen, J. E., Kummetha, S., Obbineni, S. C., & Surampudi, B. R. (2021). Mood-congruent biases in facial emotion perception and their gender dependence, International Journal of Psychology, 56(3), 378-386. [Link] [Search]
  • Steephen, J. E., Mehta, S. R., & Surampudi, B. R. (2018). Do we expect women to look happier than they are?: A test of gender-dependent perceptual correction, Perception, 47(2), 232-235. [Link] [Author’s version] [Search]
Medical and Assistive Devices
  • Jhunjhunwala, S., Tharion, J., Kapil, S., & Muthu, N. (2020). A portable mechanical ventilator for respiratory emergencies (Patent filed).
  • Tharion, J., Rao, Y. P. C., Muthu, N., & Kanagaraj, S. (2020). Vacuum assisted technique for in situ manufacturing of composite prosthetic socket on the residual stump of upper and lower limbs (Patent under filing process).
  • Tharion, J., Kapil, S., Muthu, N., & Kanagaraj, S. (2020). Rapid manufacturable ventilator for respiratory emergencies of COVID-19 disease. Trans Indian Natl. Acad. Eng. 5, 373–378. [Full paper]