An Intelligent Brain Computer Interfacing (BCI) based personalized healthcare system for neurorehabilitation

Project Title

An Intelligent Brain Computer Interfacing (BCI) based personalized healthcare system for neurorehabilitation

Project Area of Specialization Artificial IntelligenceProject Summary

Brain- Computer Interfaces (BCIs) is a rapidly evolving field that seeks direct interaction between the human brain and machines. In this project, we will develop An Intelligent BCI based Personalized Healthcare System for Neurorehabilitation for people living with
disabilities which can act as an auxiliary control to operate other devices to perform activities of daily livings (ADLs) e.g. robotic wheelchairs, tilt / recline hospital beds, remote controls for TV, keyboards for PCs, smartphone s/tablets, and videogame controllers.

A brain-computer interface (BCI) directly uses brain-activity signals to allow users to operate the environment without any muscular activation. Thanks to this feature, BCI systems can be employed not only as assistive devices, but also as neurorehabilitation tools in clinical settings. However, several critical issues need to be addressed before using BCI in neurorehabilitation, issues ranging from signal acquisition and selection of the proper BCI paradigm to the evaluation of the affective state, cognitive load and system acceptability of the users.  

Project Objectives

The objectives are as follows

understanding the problems

understanding the devices needed

design and implemenation of the project

Recommendations

Project Implementation Method

In principle, any type of brain signal could be used to control a BCI system. The most commonly studied signals are the electrical signals produced mainly by neuronal postsynaptic membrane polarity changes that occur because of activation of voltage-gated or ion-gated channels. The scalp EEG, first described by Hans Berger in 1929,14 is largely a measure of these signals. Most of the early BCI work used scalp-recorded EEG signals, which have the advantages of being easy, safe, and inexpensive to acquire. The main disadvantage of scalp recordings is that the electrical signals are significantly attenuated in the process of passing through the dura, skull, and scalp.Thus, important information may be lost. The problem is not simply theoretical: epileptologists have long known that some seizures that are clearly identifiable during intracranial recordings are not seen on scalp EEG. Given this possible limitation, recent BCI work has also explored ways of recording intracranially.

Benefits of the Project

As a communication channel, a BCI consists of input signals, output signals, an input into-output translator (i.e., a signal processing system), a protocol for timing and one for the switching on or off of the BCI communication-channel itself . At this level, a BCI can be depicted by the simple model. Though useful and correct, the model hides the critical issues characteristic of any BCI.

Technical Details of Final Deliverable

The interaction between man and machine does not require any muscular activation. This means that unlike classical human-computer interfaces, the user commands follow notnatural output pathways. We have shown that this peculiar feature makes BCI systems not only valuable assistive devices for people with severe motor disabilities, but also real rehabilitative tools. In fact, by stimulating patients to acquire new skills, and activating specific cortical areas, BCIs might also be used for innovative and effective neurorehabilition therapies. Indeed, 

Final Deliverable of the Project HW/SW integrated systemCore Industry MedicalOther Industries IT Core Technology Internet of Things (IoT)Other Technologies Augmented & Virtual RealitySustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	80000
Thesis and publication	Miscellaneous	2	5000	10000
Arduino Nano 33 IoT Headers	Equipment	4	2700	10800
MFP M130fn - LaserJet Pro	Equipment	1	39000	39000
Transisters	Equipment	50	30	1500
Miscellaneous wires	Equipment	1	1600	1600
capciters	Equipment	10	300	3000
EEG Sensors	Equipment	4	1200	4800
ECG sensor	Equipment	4	500	2000
1TB HDD for Data collectioon	Equipment	1	7300	7300