Project

BCI controlled FES system for complete neurorehabilitation of post-stroke patients

Publisher

Supervisor

Location

Greater Copenhagen area

Brain Computer Interface (BCI) systems directly uses the brain signals (EEG – electroencephalogram) to allow the users to operate the environment without any muscular activation [1]. They are interactive devices in order to communicate between the brain and an external device (computer/machine).

BCI translates the EEG signals into comprehensive commands which are necessary to run an external machine or video game interface. It is an assistive technology and has been used in a wide variety of physical and mental disorders. Due to the bidirectional interaction between the brain and the computer, BCI can also be used to alter the brain functions. This makes them suitable for neuro-rehabilitation applications since they exploit the neural plasticity in their functioning.

BCI technology has been used to help the stroke survivors basically in two different ways: (i) It is used to substitute for the loss of neuromuscular functions by using the brain signals of the stroke survivor to interact with the environment instead of using their impaired muscles (eg., controlling a computer cursor or a limb orthosis for word processing and accessing Internet etc.), and (ii) BCI as a method for stroke rehabilitation to restore the impaired motor functions. Functional electric stimulator (FES) uses electrical currents to activate nerves innervating extremities affected by paralysis.

A BCI controlled FES system is proposed as a complete neuro-rehabilitation tool for post-stroke patients to regain fine motor skills in the fingers. An inexpensive portable neuro-rehabilitating training system is envisioned which can potentially cause neural plasticity and improvement in the motor skills. The method will be based on controlling a FES device attached on the affected arm, using the EEG signals of the patients.

The project includes understanding the different BCI systems, EEG signals and their characteristics, design of appropriate interface paradigms, choice of appropriate signal processing algorithms for the feature extraction and classification, getting acquainted with its implementation in Matlab and its performance evaluation.

Allowed no of students: 1-2

In collaboration with

Helle K. Iversen, M.D., DMSc, helle.klingenberg.iversen@regionh.dk

Search in postings
Contact

Company / Organization

DTU Sundhedsteknologi

Name

Sadasivan Puthusserypady

Position

Gruppeleder, Lektor

Mail

sapu@dtu.dk

Supervisor info

BSc in Electrical Engineering

Supervisor

Sadasivan Puthusserypady

Type

BSc project, MSc thesis

BSc in Biomedical Engineering

Supervisor

Sadasivan Puthusserypady

Type

BSc project, MSc thesis

MSc in Electrical Engineering

Supervisor

Sadasivan Puthusserypady

Type

BSc project, MSc thesis

MSc in Biomedical Engineering

Supervisor

Sadasivan Puthusserypady

Type

BSc project, MSc thesis

Technical University of Denmark

For almost two centuries DTU, Technical University of Denmark, has been dedicated to fulfilling the vision of H.C. Ørsted – the father of electromagnetism – who founded the university in 1829 to develop and create value using the natural sciences and the technical sciences to benefit society.


Today, DTU is ranked as one of the foremost technical universities in Europe, continues to set new records in the number of publications, and persistently increases and develops our partnerships with industry, and assignments accomplished by DTU’s public sector consultancy.

Find us here

Anker Engelunds Vej 1
Bygning 101A
2800 Kgs. Lyngby

Denmark



Tlf. (+45) 45 25 25 25

CVR-nr. 30 06 09 46

All vacant positions
 

loading..