Comparison among probabilistic neural network, support vector machine and logistic regression for evaluating the effect of subthalamic stimulation in Parkinson disease on ground reaction force during gait.
J Biomech
; 43(4): 720-6, 2010 Mar 03.
Article
en En
| MEDLINE
| ID: mdl-19914622
Deep brain stimulation of the subthalamic nucleus (DBS-STN) is an approved treatment for advanced Parkinson disease (PD) patients; however, there is a need to further evaluate its effect on gait. This study compares logistic regression (LR), probabilistic neural network (PNN) and support vector machine (SVM) classifiers for discriminating between normal and PD subjects in assessing the effects of DBS-STN on ground reaction force (GRF) with and without medication. Gait analysis of 45 subjects (30 normal and 15 PD subjects who underwent bilateral DBS-STN) was performed. PD subjects were assessed under four test conditions: without treatment (mof-sof), with stimulation alone (mof-son), with medication alone (mon-sof), and with medication and stimulation (mon-son). Principal component (PC) analysis was applied to the three components of GRF separately, where six PC scores from vertical, one from anterior-posterior and one from medial-lateral were chosen by the broken stick test. Stepwise LR analysis employed the first two and fifth vertical PC scores as input variables. Using the bootstrap approach to compare model performances for classifying GRF patterns from normal and untreated PD subjects, the first three and the fifth vertical PCs were attained as SVM input variables, while the same ones plus the first anterior-posterior were selected as PNN input variables. PNN performed better than LR and SVM according to area under the receiver operating characteristic curve and the negative likelihood ratio. When evaluating treatment effects, the classifiers indicated that DBS-STN alone was more effective than medication alone, but the greatest improvements occurred with both treatments together.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Enfermedad de Parkinson
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Terapia Asistida por Computador
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Inteligencia Artificial
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Terapia por Estimulación Eléctrica
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Interpretación Estadística de Datos
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Redes Neurales de la Computación
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Trastornos Neurológicos de la Marcha
Tipo de estudio:
Diagnostic_studies
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Etiology_studies
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Evaluation_studies
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Prognostic_studies
/
Risk_factors_studies
Aspecto:
Determinantes_sociais_saude
Límite:
Female
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Humans
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Male
/
Middle aged
Idioma:
En
Revista:
J Biomech
Año:
2010
Tipo del documento:
Article
País de afiliación:
Brasil
Pais de publicación:
Estados Unidos