Centre for Excellence in
Real Time Human Brain-Computer Interface
Brain-computer interface (BCI) is a direct communication between the brain and an external device, bypassing the traditional pathway of peripheral nerves and muscles. The aim of BCI is to supplement human capabilities by enabling people (particularly disabled) to communicate/control devices by simply “imagining”. Only a very limited number of clinical studies with neurological patients are available, most of them are single case studies. Over the last one year, a team of 15 students along with faculty members in the R&D centre have started working on brain signals such as EEG signals. Different types of EEG signals and their classifications are understood and software reference models based on Matlab is developed. Discrete wavelet transforms for signal classification and Denoising are developed for analysis of EEG signals. Various EEG signals from known data base are classified using novel algorithm and the developed algorithm is implemented on FPGA platform.
Currently, there are faculty members those who have registered for PhD and are working on the following problem statements in BCI:
- Design, Modeling and Performance Analysis of Novel Algorithms for EEG based Brain Control Interface for Paralytic Patients
- Design, Modeling and Validation of Novel Algorithms for Emotion Detection and Classification using EEG signals in Normal and Abnormal Patients
- Design, Modeling and Validation of BCI for non medical application areas such as driving and traffic monitoring
- Design of low cost embedded systems for BCI module for elderly persons
The goal of Centre for Excellence is to develop BCI system that is robust and portable enough to meet the daily communication and social interaction needs of severely disabled individuals and elderly persons. The centre aims to develop signatures of brain signals, prepare database of brain signatures, develop data acquisition modules for experimentation, develop algorithms for segmentation, classification and analysis of EEG signals, design and prototype development of electronic gadgets with user friendly interface for differently able persons and elderly citizens. The centre will promote research and development activities in BCI and will be able to create aniche for itself in the country as a nodal centre for BCI research. The primary objectives of CFE in Real Time Human Brain-Computer Interface are:
- Create state-of-the-art lab facility for brain signal acquisition, analysis and classification
- Creation of database for brain signals from Indian population of locked-in patients and elderly persons
- Development of new brain-computer interface technology for real time monitoring of locked-in patients
- Development of consumer-ready products with hardware platforms for locked-in patients and elderly persons
- Impart training and consultancy services to NGOs, medical research services, academic institutions and will collaborative with international organisations for advanced research in BCI
- Develop new products with low cost solutions that are of social relevance
Need and Relevance:
Stroke is the leading cause of long-term disability in adults and affects approximately 20 million people per year worldwide. Five millions remain severely handicapped and dependent on assistance in daily life. Nearly 30% of all stroke patients are under the age of 65. Other diseases resulting in paralysis at such early age include Multiple Sclerosis (MS), affecting more than 2.5 million people worldwide, or spinal cord injury (SCI) with 12.1 to 57.8 cases per million. BPI, the disruption of the upper limb nerves leading to a flaccid paralysis of the arm, affects thousands of people every year. Paralytic patients are also called as “locked-in” patients. Because of a stroke, traumatic brain injury, cerebral palsy or a degenerative neurological disease such as amyotrophic lateral sclerosis, their entire motor system is paralyzed.
The population of disabled in India is estimated to be 90 million and 30 million are children below the age of 14 years. One in every 10 children is born with or acquires a physical, mental or sensory disability. India has approximately 450 million child populations and the prevalence rate mental retardation is 0.5 to 1% (Planning commission of India). In every one lakh persons in our total population, 94 are persons with mental retardation. On the other hand neurological disorders such as dementia mainly affect older people: only 2% of cases start before the age of 65 years. After this the prevalence doubles with every ﬁve year increment in age. Dementia is one of the major causes of disability in later life. The prevalence of dementia in India is 1.9% over the age of 60 years.
The only ray of hope is currently the development of brain-computer interfaces (BCI), a direct communication pathway between the brain and an external device that records neural processes. To a certain extent, BCI can be created with non-invasive techniques. EEG recordings are the most thoroughly studied potential interface and have the advantage of excellent temporal resolution, ease of use and portability.
Centre for Excellence in Real Time Human Brain Computer Interface will currently work on
four major projects which would be carried out in parallel in the following phases:
Phase I: Year 1
- Literature review on BCI signal acquisition, classification and segmentation algorithms will be carried out by referring to journals and various data base
- Collection of data sets from known patients and analysis of data sets for data interpretation
- Development of experimental setup for BCI with sensors, head cap, signal conditioners, data converters and software modules
- Design, modelling and validation of algorithms for BCI analysis using DWT, Neural Networks and SVMs
Phase II: Year II
- Development of novel algorithms for brain signal interpretation in locked-in patients and elderly persons
- Collaborative research with national and international universities and research organisations
- Interpretation of brain signals from locked-in patients and elderly persons and identify brain signal signatures for various thoughts
- Design and development of hardware modules based on embedded systems for providing assistance to locked-in patients and elderly persons
Phase III: Year III
- Development of novel embedded system modules for realtime interface of BCI and prototype development of embedded systems with novel logic
- Integration of BCI with sensor modules for complete system development
- Develop novel BCI systems for non medical applications
- Impart training and provide consultant services for generating revenue for self sustainment
CFE in BCI will initially be able to carry out the following:
- Signal acquisition, the recording of the brain signal. This signal is then digitized for analysis.
- Signal processing, the conversion of the raw signal into a useful device command. This involves both feature extraction, the identification of meaningful changes in the signal, and feature translation, the conversion of those signal changes into a device command.
- Device output, the overt command or control functions that are administered by the BCI system.
Most of the research devoted to BCI development consists of methodological studies comparing different online mathematical algorithms, ranging from simple linear discriminant analysis (LDA) to nonlinear artiﬁcial neural networks (ANNs) or support vector machine (SVM) classiﬁcation. The CFE will be involved in design and development of novel algorithms using various techniques for BCI system.
R&D centre will create state-of-the-art facility with sophisticated hardware and software resources to carry out research activities in BCI. The centre will be headed by eminent professor with experience in BCI, doctors will be hired on consultancy basis as advisory committee members, and research scholars will be hired as interns for two years and will form the core team in BCI research. The centre will hire talented and experience engineers and also groom young scholars, undergraduates to actively pursue the set objectives and demonstrate significant progress in BCI.
The Centre will collaborate with DRDO organization (DEBEL), Nimhans (Bangalore) and MS Ramaiah Memorial Hospital (Neuro Science Department) for joint research activities. The centre will also collaborative with Berlin Institute of Technology, Charité - University Medicine Berlin, Fraunhofer, Germany, Weldon School of Biomedical Engineering, Purdue University, US and University of Toronto, Canada for collaborative research in BCI.
MSEC will provide space of 4000 sq. ft., for setup of software computing facility, hardware based experimental facility, discussion room and staff room.
The hardware and software resources required for CFE:
- Matlab/Simulink/Real-Time Workshop, MS Visual C++ and MS Office on Unix and Windows platforms.
- An ElectroCap™ electrode cap connected to a custom SA Instruments BIOAMP signal amplifier
- MCSCap electrodes systems
- Bridge electrodes and cap electrodes
- Photo stimulator and acoustic stimulator
- EEG machine
- USB Interface
- LED impedance indicators
- Digital video electroencephalograph
- Portable digital electroencephalograph (with EEG mapping system)
- Programmable SOC from Cypress
- DSP processor kits from Texas Instruments (Medical applications)
- FPGA development kits Computing Facility (5 Nos.):
- Processor - Quad-processor Pentium® IV PC 3.00 GHz
- RAM - 8 GB RAM
- Serial Port - RS 232 Serial port for EEG amplifier and USB port for external interface
- Hard Disk - 300 GB HDD
The centre for excellence in Real Time Human Brain Computer Interface will be able to deliver the following every academic year:
- Execution of four major projects that focuses on development of novel algorithms for BCI system for differently able persons and elderly persons
- Development of prototype modules for differently able persons and elderly persons
- Development of software that are commercially viable for EEG signal analysis
- Publish 5 research papers every year that will be published in reputed journals and contribute for technological growth
- At least two patents every year in BCI and its applications
- Training and consultancy services that can generate revenue for BCI research at MSEC
- Detailed project reports will be delivered every academic year highlighting progress report of CFE in BCI
- Imparting training to UG and PG students, PhD scholars and faculties from various organisations
- Access to data base of brain signals for research activity and development of brain signal signatures for information extraction and interpretation
Asst Professor, DEPT of R&D (ECE) MS Engineering College
Mail ID: firstname.lastname@example.org