[17] Gait Dynamics in Neuro-Degenerative Disease ... - Esiee

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15 Οκτ 2013 (πριν από 3 χρόνια και 7 μήνες)

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Gate Modelling for Parkinson's, Huntigton’s and

amyotrophic lateral sclerosis’s diseases.


Pro
jet Interne I4 (2008/2009)





Noisy
-
le
-
Grand 14 Octobre 08

Tarik AL
-
ANI










Falls are one of the most serious complications of the gait

disturbance in elderly persons
[1],
in Parkinson's

[2
-
9]

(*)
, in Huntigton
’s s disease
[10]

(**)

and amyotrophic lateral sclerosis
(ALS) [11]

(***)
. Beyond the

acute trauma that they may cause, falls may lead to fear of

falling, self
-
imposed restrictions

in activities of daily living,

and nursing home admission.


Gait model
l
ing may help for


1.
u
nderstand
ing

better the pathophysiology of these diseases and to improve

the clinician
's
ability to measure responses to therapeutic interventions, it may be hel
pful to quantify gait
dynamics accurately. Stride variability, for example, has been associated with an increased
fall risk in elderly adults in general
,

2. remote telemonitoring and fall prediction.


This aim of this project is to apply and
then
to
compare the abilities of two advanced machine
learning algorithms: Hidden Markov Models (HMMs) [12] and Support Vector Machines
(SVM)
[13
-
15] for Gait model
l
ing.


Softwars

used
for the p
roject deve
l
o
pment
: Scilab [16] and Matlab

Database used for the proj
ect development
: database from
Physi
onet [17]


(*) A disease of the nervous system caused by degeneration of a part of the brain called the
basal ganglia, and by low production of the neurotransmitter dopamine.

Symptoms include
muscle rigidity, tremors, and slow voluntary movement.


(**) A dominant genetic disorder in which a protein is produced abnormally, leading to the
breakdown in the parts of the brain (central nervous system) that produces progressive
dem
entia and involuntary movements.


(***) A rare, fatal, progressive degenerative disease of unknown cause characterized by
slowly progressive degeneration of pyramidal motor neurons in the upper (UMN) and lower
motor neurons (LMN).


Mots clés
:
Algorithmiqu
e,

Apprentissage artificiel (Machine learning), Intelligence
artificielle (artificial intelligence), classification (classification), Modèles de Markov cachés
(Hidden Markov Models (HMMs),
Support Vector Machines (SVM)
.


References

[1]

Tarik Al
-
ani,
Quynh Trang LE BA, Eric Monacelli, "On
-
Line Automatic Detection of
Human Activity in Home Using Wavelet and Hidden Markov Models", MCSC 2007,
October, 1
-
3, Singapore, 2007.

[2]

Ashburn A, Stack E, Pickering RM, Ward CD: A community
-
dwelling

sample of peopl
e
with Parkinson's disease: characteristics

of fallers and non
-
fallers. Age Ageing 2001, 30:47
-
52.

[3]

Ashburn A, Stack E, Pickering RM, Ward CD: Predicting fallers in

a community
-
based
sample of people with Parkinson's

disease. Gerontology 2001, 47:277
-
28
1.

[4]

Bloem BR, van Vugt JP, Beckley DJ: Postural instability and falls in

Parkinson's disease.
Adv Neurol 2001, 87:209
-
223.

[5]

Hely MA, Morris JG, Traficante R, Reid WG, O'Sullivan DJ, Williamson

PM: The sydney
multicentre study of Parkinson's disease:

progression and mortality at 10 years. J Neurol
Neurosurg

Psychiatry 1999, 67:300
-
307.

[6]

Koller WC, Glatt S, Vetere
-
Overfield B, Hassanein R: Falls and Parkinson's

disease. Clin
Neuropharmacol 1989, 12:98
-
105.

[7]

Bloem BR, Hausdorff JM, Visser JE, Gilad
i N: Falls and freezing of

gait in Parkinson's
disease: a review of two interconnected,

episodic phenomena. Mov Disord 2004, 19:871
-
884.

[8]

Balash Y, Peretz C, Herman T, Leibovich G, Hausdorff J, Giladi N:

Falls in outpatients
with Parkinson's disease:
frequency,

impact and identifying factors. J Neurol 2004 in press.

[
9]

http://www.parkinson.org/NETCOMMUNITY/Page.aspx?pid=201&srcid=
-
2


[10]

http://www.hdfoundation.org/home.php


[11]

http://www.alsa.org/


[12]

L. R. Rabiner, "A tutorial on hidden Markov models and selected

application in speech
recognition", Proc. IEEE, Vol. 77, No. 2,
February

1989, pp. 267
-
296.

http://www.cs.ubc.ca/~murphyk/Bayes/rabiner.pdf


[13]

CHRISTOPHER J.C. BURGES, "A Tutorial on Support Vector Machines for Pattern

Recognition", Data Mining and Know
ledge Discovery, 2, 121

167 (1998)

http://www.umiacs.umd.edu/~joseph/support
-
vector
-
machines4.pdf

[14]

Andrew W. Moore, "Support Vector Machines"

http://www.autonlab.org/tutorials/svm15.pdf


[15]

Pai
-
Hsuen Chen, Chih
-
Jen Lin, and Bernhard Sch¨olkopf, "A Tutorial on º
-
Support
Vector Machines"

http://www.csie.ntu.edu.tw/~cjlin/papers/nusvmtutorial.pdf


[16]

http://www.scilab.org/

[17]

Gait Dynamics in Neuro
-
Degenerative Disease Data Base

http://www.physionet.org/physiobank/database/gaitndd/



Contact:
T. AL
-
ANI

ESIEE
-
PARIS

Département Informatique

e
-
mail

: t.alani@esiee.fr