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DECOMPOSITION OF SURFACE ELECTROMYOGRAMS:
PRACTICAL EXPERIENCES
DECOMPOSITION OF SURFACE ELECTROMYOGRAMS:
PRACTICAL EXPERIENCESA. Holobar1,2
[email protected] ( [email protected] )
1 FEECS, University of Maribor, Slovenia2 LISiN, Politecnico di Torino, Italy
Laboratorio di Ingegneria del Sistema Neuromuscolare
e della Riabilitazione Motoria
Politecnico di Torino, Italy
Faculty of Electrical Engineering and Computer Science
University of Maribor, Slovenia
Copyright Ales Holobar, 2007. Some rights reserved. Content in this presentation is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License. This license is more fully described at:http://creativecommons.org/licenses/by-nc-sa/3.0/.
LISiNPolitecnico di Torino
Surface EMG • acquisition systems
(16, 64, 128 chs)• HD electrode arrays• stimulators• EMG simulators• information extraction
techniques
Signal & image processing
• TF & TS analysis• HOS• Cepstral analysis• BSS/ICA• MIMO, MISO
identification
SSLUniversity of Maribor
Arrays of surface electrodes
Select time instant
with high MU activity
Step 2
Convolution Kernel Compensation (CKC)in
stan
tane
ous
disc
harg
e ra
te (
Hz)
time (s)
Compensate MUAPshapes
Step 1
Blindly reconstruct
MU dischargepattern
estimator
Step 3
Filter out single MU discharge patterns
Step 4
mul
ticha
nnel
su
rfac
e E
MG
CKC decomposition: MU discharge patterns (abductor pollicis, force ramp contractions 0 % - 10 % MVC)
CKC decomposition: MU discharge patterns(Biceps Brachii, constant isometric contraction at 10 % MVC)
A. Holobar, D. Zazula. Correlation-based decomposition of surface EMG signals at low contraction forces, Medical & Biological Engineering & Computing, 2004, 42 (4), 487-495.
[pp
s]
2 4 6 8 10 12Time [s]
Ch
ann
el
(4,3
)
2 2.2 2.4 2.6
0
Time [s]
Am
plitu
de
Reconstructed MUAP trainsacquired EMG signal
sum of reconstructedMUAP trains
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-60
-40
-20
0
20
40
60
Normalized Frequency [ π rad/sample]
Po
we
r S
pe
ctr
al D
en
sity (
dB
/ ra
d/sa
mp
le)
400 800 1200 1600 2000 2400 2800 3200 3600 4000
0
0.1
0.2
Time [ms]
Am
plit
ud
e
200 400 600 800 1000 1200 1400 1600 1800 2000-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
Time [ms]
Am
plit
ud
e [a
rbitr
ary
un
its]
0 10 0 10Time [ms]
0 100 10
MU
AP
am
plit
ud
e(P2
P 2
40 μV
)
0 10
Signal artefacts: line interference
1 2 3 4 5
13
12
11
10
9
8
7
6
5
4
3
2
1
Ele
ctro
de r
ows
Electrode columns
Signal artefacts: bad contact (biceps brachii, monopolar mode)
Internal array Central array External array
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
Ele
ctro
de r
ows
Movement artefetcs & saturations:(external sphincter, bipolar mode, 100% MVC)
1
2
3
4
5
6
7
MU
num
ber
0 1 2 3 4 5 6
10 - MU 1
10 - MU 2
10 - MU 3
10 - MU 4
10 - MU 5
10 - MU 6
10 - MU 7
Time [s]
inst
anta
neou
s di
scha
rge
rate
[H
z]
Decomposition & ground truth(external sphincter, bipolar mode)
Similar shapes of MUAPs: MU 1
2 3
Time41
-2500
250
-2500
250
-2500
250
-2500
250
-2500
250
-2500
250
-2500
250
-2500
250
-2500
250
-2500
250
-2500
250
-2500
250
MU
AP
s am
plitu
de [
V]
5
Similar shapes of MUAPs: MU 2
2 3
Time41
-880
88
-880
88
-880
88
-880
88
-880
88
-880
88
-880
88
-880
88
-880
88
-880
88
-880
88
-880
88
MU
AP
s am
plitu
de [
V]
5
Similar shapes of MUAPs: MU 1 & MU 2
Similar shapes of MUAPs and reconstruction of innervation pulse trains
2 3 4 5 6 7 8 9 10 11 12MU 1
MU 2
MU 1 & 2
Time [s]
Rec
onst
ruct
ed in
nerv
atio
n pu
lse
trai
ns
Case studies: ICA & image processing homepages
• ICA – http://www.tsi.enst.fr/icacentral
• Face recognition test databases– http://www.face-rec.org/databases/– http://vision.bc.edu/~dmartin/MidLevel/
• Middlebury stereo page:– http://cat.middlebury.edu/stereo/– test database, source codes & algorithm
benchmarking
ICA central: data collections
Face recognition test databases
Face recognition test databases
Middlebury stereo page
Middlebury stereo page
Middlebury stereo page
Acknowledgement
Progetto Lagrange
This research was supported by a Marie Curie Intra-European Fellowships within the 6th European Community Framework Programme, by CyberManS EU project, Slovenian Ministry of Higher Education, Science and Technology, Italian Ministry of Foreign Affairs, Slovenian Research Agency and Lagrange project.
