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Unsupervised Selection of Mother Wavelets
and Parameter Optimization for Artifact
Removal in Neural Recordings
By
Md Kafiul Islam
Translational System and Signal Processing Group
National University of Singapore
Sequence of Optimization
1) Optimization of Parameter Alpha for Best
Mother Wavelet
2) Optimization of Parameter kA
3) Optimization of Parameter kD
Motivation to Choose Best Wavelet
 To achieve best performance both in terms of artifact removal and signal distortion
2 4 6 8 10
65
70
75
80
85
90
lamda
db2
Best
2 4 6 8 10
12
14
16
18
delSNR
db2
Best
2 4 6 8 10
0.006
0.008
0.01
0.012
0.014
RMSE
db2
Best
2 4 6 8 10
0.5
1
1.5
2
2.5
No. of Trials
PSDDistortion
db2
Best
Comparison of Artifact Removal Performance between Best Mother Wavelet and
Daubechies Wavelet (Filter Length = 4)
2 4 6 8 10
60
70
80
90
lamda
Sym2
Best
2 4 6 8 10
12
14
16
18
20
delSNR
Sym2
Best
2 4 6 8 10
0.008
0.01
0.012
0.014
0.016
RMSE
Sym2
Best
2 4 6 8 10
0.5
1
1.5
2
2.5
3
No. of Trials
PSDDistortion
Sym2
Best
Comparison of Artifact Removal Performance between Best Mother Wavelet
and Symlet Wavelet (Filter Length = 4)
Purpose to Optimize Parameter kD and kA
 To make the selection unsupervised
 To achieve best performance both in terms of artifact removal and signal distortion
1 1.5 2 2.5 3 3.5 4 4.5 5
9
10
11
12
13
14
15 X: 3
Y: 14.5
Parameter k
D
Avg.SNDRImprove
The Maximum Value of Average SNDR Improvement Can be
Achieved Through an Optimized and Unsupervised Selection of
Parameter k_D
0 0.2 0.4 0.6 0.8 1
0
20
40
60
80
100 X: 0.6
Y: 80.97
lamda
0 0.2 0.4 0.6 0.8 1
10
12
14
16
18
X: 0.6
Y: 16.32
delSNR
0 0.2 0.4 0.6 0.8 1
0
1
2
3
X: 0.6
Y: 1.187
PSDDistortion
0 0.2 0.4 0.6 0.8 1
0.005
0.01
0.015
0.02
X: 0.6
Y: 0.009534
RMSE
Parameter k
A
The Best Performance Metrics Can be Achieved Through an Optimized
and Unsupervised Selection of Parameter k_A
Optimization of Parameter α for Best Wavelet
 Wavelet Filter Design (Length = 4)
Low Pass Filter
High Pass Filter
 Criteria for Optimal ‘α’: Options
 Maximize Correlation between Artifactual
Signal and Reconstructed Signal in non-
artifactual regions (i.e. IDi is not artifact index)
 Minimize Correlation between Artifactual
Signal and Reconstructed Signal in artifactual
regions (i.e. IDi is artifact index)
Optimization of Parameter α
• Steps for Optimization Procedure
1) Parameterize the wavelet filters w. r. t. α
2) Sweep α from –π to +π with increment of π/6
3) Compute the filter coef., hα & gα for each α
4) Perform proposed artifact removal process with the
wavelet filters, hα & gα
5) Minimize Correlation between r(n) and r’(n) only in
the artifact-index regions to find optimal alpha,
α_opt1
Or
6) Maximize Correlation between r(n) and r’(n) only in
the non-artifact-index regions to find optimal alpha,
α_opt2
Correlation Value Vs Alpha
-4 -3 -2 -1 0 1 2 3 4
0.35
0.4
0.45
0.5
Minimize ArtifactsCorrelationValue
-4 -3 -2 -1 0 1 2 3 4
0.94
0.96
0.98
1
alpha
Maximize Non-Artifacts
α_opt2 = - 2.618
α_opt1 = - 2.094
Performance Metrics Vs Alpha
-4 -3 -2 -1 0 1 2 3 4
86
87
88
89
lamda
-4 -3 -2 -1 0 1 2 3 4
17.5
18
18.5
19
delSNR
alpha
-4 -3 -2 -1 0 1 2 3 4
1.1
1.15
1.2
1.25
PSDDistortion
-4 -3 -2 -1 0 1 2 3 4
7.6
7.8
8
8.2
8.4
x 10
-3
alpha
RMSE
Optimization of Parameter kA
0.2 0.4 0.6 0.8 1
0
20
40
60
80
100
lamda
0.2 0.4 0.6 0.8 1
8
10
12
14
16
delSNR
Parameter k
A
0.2 0.4 0.6 0.8 1
0
2
4
6
PSDDistortion
0.2 0.4 0.6 0.8 1
0.005
0.01
0.015
0.02
RMSE
Parameter kA
0.2 0.4 0.6 0.8 1
-0.4
-0.2
0
0.2
0.4
Minimize Artifacts
CorrelationValue
0.2 0.4 0.6 0.8 1
0.8
0.85
0.9
0.95
1
Maximize Non-Artifacts
Parameter k
A
kA_opt1 = 1
kA_opt2 = 0.7
Optimization of Parameter kD
1 1.5 2 2.5 3 3.5 4 4.5 5
0.461
0.462
0.463
0.464
Minimize Artifacts
1 1.5 2 2.5 3 3.5 4 4.5 5
0.9934
0.9934
0.9934
0.9934
k
D
Maximize Non-Artifacts
1 2 3 4 5 6
11
12
13
14
15
16
17
k
D
Avg.SNDRImprovement
kD_opt1 = 2.5
kD_opt2 = 5
17 dB SNDR
@ kD_opt1 = 2.5
15.94 dB SNDR
@ kD_opt2 = 5
1 1.5 2 2.5 3 3.5 4 4.5 5
0.8482
0.8482
0.8482
0.8482
PSD dis aft
1 1.5 2 2.5 3 3.5 4 4.5 5
9.9945
9.995
9.9955
x 10
-3
k2
RMSE aft
1 1.5 2 2.5 3 3.5 4 4.5 5
79.687
79.688
79.689
79.69
79.691
79.692
lamda
1 1.5 2 2.5 3 3.5 4 4.5 5
13.4296
13.4298
13.43
13.4302
13.4304
delSNR
k2

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Unsupervised selection of mother wavelets and parameter optimization

  • 1. Unsupervised Selection of Mother Wavelets and Parameter Optimization for Artifact Removal in Neural Recordings By Md Kafiul Islam Translational System and Signal Processing Group National University of Singapore
  • 2. Sequence of Optimization 1) Optimization of Parameter Alpha for Best Mother Wavelet 2) Optimization of Parameter kA 3) Optimization of Parameter kD
  • 3. Motivation to Choose Best Wavelet  To achieve best performance both in terms of artifact removal and signal distortion 2 4 6 8 10 65 70 75 80 85 90 lamda db2 Best 2 4 6 8 10 12 14 16 18 delSNR db2 Best 2 4 6 8 10 0.006 0.008 0.01 0.012 0.014 RMSE db2 Best 2 4 6 8 10 0.5 1 1.5 2 2.5 No. of Trials PSDDistortion db2 Best Comparison of Artifact Removal Performance between Best Mother Wavelet and Daubechies Wavelet (Filter Length = 4) 2 4 6 8 10 60 70 80 90 lamda Sym2 Best 2 4 6 8 10 12 14 16 18 20 delSNR Sym2 Best 2 4 6 8 10 0.008 0.01 0.012 0.014 0.016 RMSE Sym2 Best 2 4 6 8 10 0.5 1 1.5 2 2.5 3 No. of Trials PSDDistortion Sym2 Best Comparison of Artifact Removal Performance between Best Mother Wavelet and Symlet Wavelet (Filter Length = 4)
  • 4. Purpose to Optimize Parameter kD and kA  To make the selection unsupervised  To achieve best performance both in terms of artifact removal and signal distortion 1 1.5 2 2.5 3 3.5 4 4.5 5 9 10 11 12 13 14 15 X: 3 Y: 14.5 Parameter k D Avg.SNDRImprove The Maximum Value of Average SNDR Improvement Can be Achieved Through an Optimized and Unsupervised Selection of Parameter k_D 0 0.2 0.4 0.6 0.8 1 0 20 40 60 80 100 X: 0.6 Y: 80.97 lamda 0 0.2 0.4 0.6 0.8 1 10 12 14 16 18 X: 0.6 Y: 16.32 delSNR 0 0.2 0.4 0.6 0.8 1 0 1 2 3 X: 0.6 Y: 1.187 PSDDistortion 0 0.2 0.4 0.6 0.8 1 0.005 0.01 0.015 0.02 X: 0.6 Y: 0.009534 RMSE Parameter k A The Best Performance Metrics Can be Achieved Through an Optimized and Unsupervised Selection of Parameter k_A
  • 5. Optimization of Parameter α for Best Wavelet  Wavelet Filter Design (Length = 4) Low Pass Filter High Pass Filter  Criteria for Optimal ‘α’: Options  Maximize Correlation between Artifactual Signal and Reconstructed Signal in non- artifactual regions (i.e. IDi is not artifact index)  Minimize Correlation between Artifactual Signal and Reconstructed Signal in artifactual regions (i.e. IDi is artifact index)
  • 6. Optimization of Parameter α • Steps for Optimization Procedure 1) Parameterize the wavelet filters w. r. t. α 2) Sweep α from –π to +π with increment of π/6 3) Compute the filter coef., hα & gα for each α 4) Perform proposed artifact removal process with the wavelet filters, hα & gα 5) Minimize Correlation between r(n) and r’(n) only in the artifact-index regions to find optimal alpha, α_opt1 Or 6) Maximize Correlation between r(n) and r’(n) only in the non-artifact-index regions to find optimal alpha, α_opt2
  • 7. Correlation Value Vs Alpha -4 -3 -2 -1 0 1 2 3 4 0.35 0.4 0.45 0.5 Minimize ArtifactsCorrelationValue -4 -3 -2 -1 0 1 2 3 4 0.94 0.96 0.98 1 alpha Maximize Non-Artifacts α_opt2 = - 2.618 α_opt1 = - 2.094
  • 8. Performance Metrics Vs Alpha -4 -3 -2 -1 0 1 2 3 4 86 87 88 89 lamda -4 -3 -2 -1 0 1 2 3 4 17.5 18 18.5 19 delSNR alpha -4 -3 -2 -1 0 1 2 3 4 1.1 1.15 1.2 1.25 PSDDistortion -4 -3 -2 -1 0 1 2 3 4 7.6 7.8 8 8.2 8.4 x 10 -3 alpha RMSE
  • 9. Optimization of Parameter kA 0.2 0.4 0.6 0.8 1 0 20 40 60 80 100 lamda 0.2 0.4 0.6 0.8 1 8 10 12 14 16 delSNR Parameter k A 0.2 0.4 0.6 0.8 1 0 2 4 6 PSDDistortion 0.2 0.4 0.6 0.8 1 0.005 0.01 0.015 0.02 RMSE Parameter kA 0.2 0.4 0.6 0.8 1 -0.4 -0.2 0 0.2 0.4 Minimize Artifacts CorrelationValue 0.2 0.4 0.6 0.8 1 0.8 0.85 0.9 0.95 1 Maximize Non-Artifacts Parameter k A kA_opt1 = 1 kA_opt2 = 0.7
  • 10. Optimization of Parameter kD 1 1.5 2 2.5 3 3.5 4 4.5 5 0.461 0.462 0.463 0.464 Minimize Artifacts 1 1.5 2 2.5 3 3.5 4 4.5 5 0.9934 0.9934 0.9934 0.9934 k D Maximize Non-Artifacts 1 2 3 4 5 6 11 12 13 14 15 16 17 k D Avg.SNDRImprovement kD_opt1 = 2.5 kD_opt2 = 5 17 dB SNDR @ kD_opt1 = 2.5 15.94 dB SNDR @ kD_opt2 = 5 1 1.5 2 2.5 3 3.5 4 4.5 5 0.8482 0.8482 0.8482 0.8482 PSD dis aft 1 1.5 2 2.5 3 3.5 4 4.5 5 9.9945 9.995 9.9955 x 10 -3 k2 RMSE aft 1 1.5 2 2.5 3 3.5 4 4.5 5 79.687 79.688 79.689 79.69 79.691 79.692 lamda 1 1.5 2 2.5 3 3.5 4 4.5 5 13.4296 13.4298 13.43 13.4302 13.4304 delSNR k2