Cerebral Palsy EEG Signals Classification: Facial Expressions and Thoughts for Driving an Intelligent Wheelchair

2012 ◽  
Author(s):  
Brigida Monica Faria ◽  
Luis Paulo Reis ◽  
Nuno Lau
Keyword(s):  
Cerebral Palsy ◽  
Facial Expressions ◽  
Eeg Signals ◽  
Intelligent Wheelchair

Knowledge Discovery and Multimodal Inputs for Driving an Intelligent Wheelchair

2011 ◽  
Vol 2 (4) ◽  
pp. 18-34 ◽  
Author(s):  
Brígida Mónica Faria ◽  
Luís Paulo Reis ◽  
Nuno Lau
Keyword(s):  
Cerebral Palsy ◽  
Facial Expressions ◽  
Head Movements ◽  
Computer Interface ◽  
Selection Methods ◽  
Input Devices ◽  
Recognition Of Facial Expressions ◽  
Intelligent Wheelchair ◽  
Computer Interfaces ◽  
Simulated Environment

Cerebral Palsy is defined as a group of permanent disorders in the development of movement and posture. The motor disorders in cerebral palsy are associated with deficits of perception, cognition, communication, and behaviour, which can affect autonomy and independence. The interface between the user and an intelligent wheelchair can be done with several input devices such as joysticks, microphones, and brain computer interfaces (BCI). BCI enables interaction between users and hardware systems through the recognition of brainwave activity. The current BCI systems have very low accuracy on the recognition of facial expressions and thoughts, making it difficult to use these devices to enable safe and robust commands of complex devices like an Intelligent Wheelchair. This paper presents an approach to expand the use of a brain computer interface for driving an intelligent wheelchair by patients suffering from cerebral palsy. The ability with the joystick, head movements, and voice inputs were tested, and the best possibility for driving the wheelchair is given to a specific user. Experiments were performed using 30 individuals suffering from IV and V degrees of cerebral palsy on the Gross Motor Function (GMF) measure. The results show that the pre-processing and variable selection methods are effective to improve the results of a commercial BCI product by 57%. With the developed system, it is also possible for users to perform a circuit in a simulated environment using just facial expressions and thoughts.

scholarly journals Adapted Control Methods for Cerebral Palsy Users of an Intelligent Wheelchair

2014 ◽  
Vol 77 (2) ◽  
pp. 299-312 ◽  
Author(s):  
Brígida Mónica Faria ◽  
Luis Paulo Reis ◽  
Nuno Lau
Keyword(s):  
Cerebral Palsy ◽  
Control Methods ◽  
Intelligent Wheelchair

scholarly journals Context-Based Filtering for Assisted Brain-Actuated Wheelchair Driving

2007 ◽  
Vol 2007 ◽  
pp. 1-12 ◽  
Author(s):  
Gerolf Vanacker ◽  
José del R. Millán ◽  
Eileen Lew ◽  
Pierre W. Ferrez ◽  
Ferran Galán Moles ◽  
...  
Keyword(s):  
Control System ◽  
Shared Control ◽  
Eeg Signals ◽  
Intelligent Processing ◽  
Intelligent Wheelchair ◽  
Brain Signals ◽  
Brain Interface ◽  
The Subject ◽  
Electroencephalogram Eeg ◽  
The Brain

Controlling a robotic device by using human brain signals is an interesting and challenging task. The device may be complicated to control and the nonstationary nature of the brain signals provides for a rather unstable input. With the use of intelligent processing algorithms adapted to the task at hand, however, the performance can be increased. This paper introduces a shared control system that helps the subject in driving an intelligent wheelchair with a noninvasive brain interface. The subject's steering intentions are estimated from electroencephalogram (EEG) signals and passed through to the shared control system before being sent to the wheelchair motors. Experimental results show a possibility for significant improvement in the overall driving performance when using the shared control system compared to driving without it. These results have been obtained with 2 healthy subjects during their first day of training with the brain-actuated wheelchair.

From Movement to Action

2017 ◽  
Author(s):  
Peggy Mason
Keyword(s):  
Cerebral Palsy ◽  
Motor Control ◽  
Facial Expression ◽  
Postural Control ◽  
Facial Expressions ◽  
Body Mass ◽  
Emotional Facial Expressions ◽  
Cortical Regions ◽  
Self Motion

Tracts descending from motor control centers in the brainstem and cortex target motor interneurons and in select cases motoneurons. The mechanisms and constraints of postural control are elaborated and the effect of body mass on posture discussed. Feed-forward reflexes that maintain posture during standing and other conditions of self-motion are described. The role of descending tracts in postural control and the pathological posturing is described. Pyramidal (corticospinal and corticobulbar) and extrapyramidal control of body and face movements is contrasted. Special emphasis is placed on cortical regions and tracts involved in deliberate control of facial expression; these pathways are contrasted with mechanisms for generating emotional facial expressions. The signs associated with lesions of either motoneurons or motor control centers are clearly detailed. The mechanisms and presentation of cerebral palsy are described. Finally, understanding how pre-motor cortical regions generate actions is used to introduce apraxia, a disorder of action.

scholarly journals Towards an Intelligent Wheelchair System for Users With Cerebral Palsy

2010 ◽  
Vol 18 (2) ◽  
pp. 193-202 ◽  
Author(s):  
Luis Montesano ◽  
Marta Diaz ◽  
Sonu Bhaskar ◽  
Javier Minguez
Keyword(s):  
Cerebral Palsy ◽  
Intelligent Wheelchair

scholarly journals Biological Computation Indexes of Brain Oscillations in Unattended Facial Expression Processing Based on Event-Related Synchronization/Desynchronization

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Bo Yu ◽  
Lin Ma ◽  
Haifeng Li ◽  
Lun Zhao ◽  
Hongjian Bo ◽  
...  
Keyword(s):  
Facial Expressions ◽  
Emotional Experience ◽  
Vital Role ◽  
Brain Oscillations ◽  
Eeg Signals ◽  
Frequency Bands ◽  
Set Up ◽  
Biological Computation ◽  
Expression Processing ◽  
Electroencephalogram Eeg

Estimation of human emotions from Electroencephalogram (EEG) signals plays a vital role in affective Brain Computer Interface (BCI). The present study investigated the different event-related synchronization (ERS) and event-related desynchronization (ERD) of typical brain oscillations in processing Facial Expressions under nonattentional condition. The results show that the lower-frequency bands are mainly used to update Facial Expressions and distinguish the deviant stimuli from the standard ones, whereas the higher-frequency bands are relevant to automatically processing different Facial Expressions. Accordingly, we set up the relations between each brain oscillation and processing unattended Facial Expressions by the measures of ERD and ERS. This research first reveals the contributions of each frequency band for comprehension of Facial Expressions in preattentive stage. It also evidences that participants have emotional experience under nonattentional condition. Therefore, the user’s emotional state under nonattentional condition can be recognized in real time by the ERD/ERS computation indexes of different frequency bands of brain oscillations, which can be used in affective BCI to provide the user with more natural and friendly ways.

scholarly journals Design and Simulation of Brain Controlled Electronic Wheelchair for Physically Challenged Person

2020 ◽  
Vol 9 (1) ◽  
pp. 1166-1171
Keyword(s):  
Disabled Persons ◽  
Motor Drives ◽  
Eeg Signals ◽  
Intelligent Wheelchair ◽  
Independent Life ◽  
Human Effort ◽  
Left And Right ◽  
Solid Works ◽  
The Right ◽  
Physically Challenged

Improving the quality for the life of elders and disabled person and giving proper care at the right time is one of the most important role to be performed as a responsible citizen in the society. This paper is describing about the integration of hardware, software and sensors with the help of Brain Computer Interface (BCI) to develop best generation wheelchair for physical challenged persons. Electronic wheelchair is one of the easiest way for disabled persons to lead an independent life. This smart wheelchair is totally controlled by brain, and here mechatronics plays an important role in safety recovery. By developing these types of wheelchairs it can reduce the usage of human effort and force to drive the wheels of wheelchair. It also provides a better opportunity for physically handicap person to move from one place to another. One of the best method to record brain activities can be done with the help of electroencephalography (EEG) this is also known as brain waves signal, through these EEG signals the BCI interface encode and decode the signals and transfers to ATMEGA 328 microcontroller. This wheelchair with the support of motor drives the movement is designed in such a way to control the commands like moving forward and backward, stop, turn left and right. Intelligent Wheelchair is designed using solid works and implementing into MATLAB using simmechanics is simulated using simscape multibody and the resulting torque is obtained. The aim of this paper is implement mind controlled movements for disabled persons.Keywords: Orthosis, Paraplegia, Rehabilitation, Simulation, Under limb.

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