AI-Driven Brain–Computer Interface (BCI) Systems with Digital Twin for Advanced Medical Rehabilitation and Neurofeedback Training 2026

Topics to be covered
1)Introduction to BCI
2)Neural Signal Acquisition & Processing
3) AI Integration in BCI,Neuromorphic Computing
4)Cognitive computing
5)Digital Twin Creation using Machine Learning/Deep Learning Techniques
6) AR/VR Technology in Medical Rehabilitation and Neurofeedback Training
7) Applications,Challenges and Future Scope in Medical Rehabilitation

Brain–Computer Interface (BCI) systems are revolutionizing medical rehabilitation and cognitive training by enabling direct interaction between the human brain and external devices. The enhancement of BCI systems through the integration of Artificial Intelligence (AI), Digital Twin simulations, and AR/VR (Augmented/Virtual Reality) technologies results in systems that are adaptive, personalized, and highly efficient.
AI-driven BCIs interpret neural signals from EEG, fNIRS, or ECoG sensors in real time, converting brain activity into control signals for prosthetic limbs, robotic exoskeletons, or virtual therapy tasks. Digital Twins generate virtual representations of patients’ neural and motor systems, enabling therapists and AI algorithms to safely simulate therapy outcomes and refine interventions. Training sessions in AR/VR environments are immersive and gamified, which boosts motivation and engagement, leading to more effective neurorehabilitation and cognitive training.
The architecture, key technologies, and applications of AI-enabled BCI systems integrated with Digital Twin and AR/VR technologies will be examined in this seminar. It will demonstrate applications in stroke rehabilitation, recovery from spinal cord injuries, treatment of cerebral palsy, neuroprosthetic control, and neurofeedback aimed at enhancing mental wellness. We will talk about challenges like signal variability, device cost, data privacy, and computational requirements. Additionally, we will explore future directions such as edge AI, wearable BCI devices, haptic feedback, and home-based adaptive therapy systems

1) Dr. Ashwinth Janarthanan
Assistant Professor Grade II
Department of Computer Applications,
National Institute of Technology,
Thiruchirapalli

2) Dr. Shridevi S
Professor & Deputy Director
Centre for Neuroinformatics,
Vellore Institute of Technology, Chennai

3) Mr.D.Sainatarajan
Founder of Dura Infotech,
Coimbatore

4)Dr.C.S.Saravana Kumar
Senior Software Architect
Bosch Global Software Technologies,
Coimbatore

5)Dr.Senthil Kumar T
Professor,
Department of Computer Science and Engineering
School of Computing, Coimbatore

Rs.300

Account Details for Payment

Account Number : 44064398204

IFSC Code:

SBIN0012245

Bank:

State Bank of India, Kuniamuthur, Coimbatore.

Sri Krishna College of Technology
Kovaipudur,
Coimbatore – 641042,
Tamil Nadu

Available