research group fke, uitmpp
DESCRIPTION
RESEARCH GROUP FKE, UiTMPP. Advance Control System & Computing Research Group (ACSCRG). Background of ACSCRG. - PowerPoint PPT PresentationTRANSCRIPT
RESEARCH GROUPFKE, UiTMPP
Advance Control System & Computing Research Group
(ACSCRG)
Background of ACSCRG
The Advance Control System & Computing Research Group (ACSCRG), Faculty of Electrical Engineering, UiTM Pulau Pinang was formally established in December 2010 to spearhead research and consultancy in Intelligent Control Technique and Computing that related to Advanced Rehabilitation Engineering and Medical Imaging.
The research group is actively running the research work especially on the FES-Assisted Movement and Exercises, Hybrid Orthosis, Brainwave Signal Using EEG, Medical Image Segmentation, Noise Filtering, Artificial Intelligent and many more.
Team Member of ACSCRG
Research Team Member:
Chair : Dr Zakaria Hussain
Vice Chair : Dr Siti Noraini Sulaiman
Secretary 1 : Iza Sazanita Isa
Secretary 2 : Saiful Zaimy Yahaya
Treasurer : Abdul Rahim Ahmad
Active Member: Dr. Muhammad Khusairi Osman
Rozan Boudville
Mohd Faizal Abdul Rahman
Fadhil Dato’ Ahmad
Norhazimi Hamzah
Adi Izhar Che Ani
Khairul Azman Ahmad
Mohd Halim Mohd Noor
Current Research Area
Current Research Work includes :-- FES-Assisted Movement
-Knee Swinging Exercise -Elliptical Stepping Exercise -Rowing exercise-Body Supported Walking-Abdominal Stimulation
- Hybrid Orthosis and Prosthesis - Brain Signal and Images
- EEG- MRI and fMRI
- Medical Imaging- Noise filtering- Image segmentation
- Artificial Intelligent- ANN-GA- PSO
Research Collaboration under ACSCRG
Research Collaboration:
NORESEARCHER
(MAIN) YEARS
1Department of Family Medicine, Medical Faculty, UKM Medical Centre Cheras, Kuala Lumpur. 2011
2Rehabilitation Department, Medical Faculty, Universiti Malaya, Kuala Lumpur. 2012
3Department Of Neurosciences, The School of Medical Sciences of Universiti Sains Malaysia (USM), Kelantan 2014
Research Grant Secured by ACSCRG
Research Grant:
NORESEARCHER
(MAIN) PROJECT NAME
COMPLETION DATE
CATEGORYAMOUNT
(RM)
1Siti Noraini Sulaiman
A Novel Random-valued Impulse Noise Removal Based on Adaptive Switching Filter and Local-preserving Scheme
1-Jul-17 FRGS 67,700
2 Rozan BoudvilleA Novel Neuroprostheses Control Algorithm For Stroke Patients Lower Extremities Rehabilitation
1-Jul-15 ERGS 100,000
3 Zakaria HussainA Novel Hybrid Orthosis: Assisted Lower Extremities Movement
15-Apr-15 FRGS 86,760
4 Iza Sazanita Isa
An Alpha-Beta Steady-State Correlation Of Electroencephalographic (EEG) Power Spectral Density (PSD) Brain Balancing
15-Oct-14 FRGS 69,000
Research Grant Secured by ACSCRG
Research Grant:
NORESEARCHER
(MAIN) PROJECT NAME
COMPLETION DATE
CATEGORYAMOUNT
(RM)
5Saiful Zaimy Yahaya
A Novel Dynamic Algorithm for Functional Electrical Abdominal Stimulation
1-Jan-14 FRGS 64,000
6Norhazimi Hamzah
Robust Dynamic Control Allocation Algorithm of Yaw Dynamic Stability
1-Jul-13 FRGS 78,000
Postgraduate Students under ACSCRG
Postgraduate students:
NO STUDENT NAME PROJECT TITLE SUPERVISOR LEVEL
1 Rozan BoudvilleIntelligent Control Technique for FES-Assisted Knee Swing in Stroke Rehabilitation
Dr Zakaria Hussain
PhD
2Saiful Zaimy Yahaya
Intelligent Control Technique for FES-Assisted Elliptical Stepping in Stroke Rehabilitation
Dr Zakaria Hussain
PhD
3Mohd Aswad Amat Mushim
Intelligent Control Technique For FES-Assisted Indoor Rowing Exercise in Stroke Rehabilitation
Dr Zakaria Hussain
PhD
4 Adi Izhar Che AniIntelligent Control Technique For FES-Assisted Hybrid Orthosis Body Supported Walking in Stroke Rehabilitation
Dr Zakaria Hussain
PhD
5 Iza Sazanita Isa
New Features Extraction Analysis of Small Vessel Stroke Predisposition Based on White Matter Correlation for Image processing
Dr Siti Noraini PhD
Postgraduate Students under ACSCRG
Postgraduate students:
NO STUDENT NAME PROJECT TITLE SUPERVISOR LEVEL
6 Pais SaidinIntelligent Classification of Transmission Line Fault Location For Global Sensitivity Power Protection Digital Relay
Dr Zakaria Hussain
PhD
7Abdul Rahim Ahmad
Nature Based Gel Electroforesis Image Segmenattion
Dr Zakaria Hussain
MSc
8Balkis Solehah Binti Zainuddin
EEG-Based Intelligent Classification of Stroke Patient Imaginary Movement Using Alpha Beta Steady State Correlation
Dr Zakaria Hussain
MSc
Current Research Area
FES-Assisted Knee Swinging Exercise- Utilize the flexed non-paretic knee to assist extension of the paretic knee. - Optimize functional electrical stimulation- Allow patient to perform repetitive FES-assisted knee swinging exercise
Left Knee Extension
Right Knee Extension
Rest Position
Figure 1 Setup of the FES-assisted knee ergometer model
Current Research Area
FES-Assisted Knee Swinging Exercise
Current Research Area
FES-Assisted Knee Swinging Exercise
3
Non-par Angle
2
Par Ang Vel
1
Par AnglePID
PID Paretic
PID
PID Non-paretic
d
q_k
dq_k/dt
TotalMoment
Muscle Model
vNPlant
Knee Ergometer
2
Ref Non-paretic
1
Ref Paretic
Time (sec)
0 1 2 3 4 5
Angle
(degre
e)
100
120
140
160
180
200
220Left Ref Knee TrajRight Ref Knee Traj Left Act Knee TrajRight Act Knee Traj
Time (second)
0 1 2 3 4 5
Err
or
(de
gre
e)
-4
-2
0
2
4 Paretic legNon-paretic leg
(a) Actual and reference knee trajectories
(b)Knee error
Figure 3. Knee trajectories and error obtained from PID controller
Current Research Area
FES-Assisted Elliptical Stepping Exercise- Utilize control technique to produce smooth movement of elliptical stepping exercise.
To implement the technique of optimizing the control parameter to enhance the accuracy of the movement
Current Research Area
FES-Assisted Elliptical Stepping Exercise
Figure 6 Cadence speed at control gain setting of 0.5 and 1
Figure 7 Produced knee joint torque for control gain setting of 0.5
Figure 8 Produced knee joint torque for control gain setting of 1
Current Research Area
Brainwave Signal using EEG- Established the Brainwave signal - Stroke Rehabilitation
- Stroke patient psychology – Mentally unstable.- Determine Brainwave signal for stroke patient - Encourage for physiotherapy/rehabilitation
Current Research Area
EEG Brainwave Sample
Brainwave Frequency State of
Beta13–30 Hz
Fully Awake and Alert Concentration Associated with left-brain thinking
activity-conscious mind
Alpha7-12 Hz
Relaxed, daydreaming Creativity, visualization Generally associated with right-brain
thinking activity
Theta 3-7 Hz
Deeply relaxed, dreaming Meditation, intuition, memory Generally associated with right-brain
thinking activity – deeper subconscious to super conscious
Delta 0.1-3 Hz
Sleep, dreamless Detached awareness, healing Generally associated with no thinking
Current Research Area
A Novel Random-valued Impulse Noise Removal Based on Adaptive Switching Filter and Local-preserving SchemeThe aim of this research is to establish the fundamental technique for Random-Valued Impulse Noise removal. Hence, the objectives are as follows:•To investigate the characteristics or the behavior of RVIN in terms of noise occurrence on the image histogram.•To formulate a two phase iterative method (detect then preserve) for detecting and removing RVIN by incorporating intelligent principles for adaptive noise filtering and a local preserving scheme that able to suppress high density of noise in digital images.•To evaluate the performance of the proposed method in terms of its efficiency to detect the noise and preserving the fine details of the original image.
Current Research Area
A Novel Random-valued Impulse Noise Removal Based on Adaptive Switching Filter and Local-preserving Scheme
Original Image Noisy image Corrupted with
50% RVIN Restored image by MED
Figure 1: Result of conventional MED filter in restoring 50% corrupted Lena image.
Current Research Area
A Novel Random-valued Impulse Noise Removal Based on Adaptive Switching Filter and Local-preserving Scheme
Original Image Noisy image Corrupted with
50% RVIN Restored image by MED
Figure 2: Result of conventional MED filter in restoring 50% corrupted MRI image.
Current Research Area
A Novel Random-valued Impulse Noise Removal Based on Adaptive Switching Filter and Local-preserving Scheme
Original Image Noisy image Corrupted with
50% RVIN Restored image by MED
Figure 3: Result of conventional MED filter in restoring 50% corrupted Satellite image.
Q & A……………………………….
Thank you