title: A PDF-based classification of gait cadence patterns in patients with amyotrophic lateral sclerosis.
abstract: Amyotrophic lateral sclerosis (ALS) is a type of neurological disease due to the degeneration of motor neurons. During the course of such a progressive disease, it would be difficult for ALS patients to regulate normal locomotion, so that the gait stability becomes perturbed. This paper presents a pilot statistical study on the gait cadence (or stride interval) in ALS, based on the statistical analysis method. The probability density functions (PDFs) of stride interval were first estimated with the nonparametric Parzen-window method. We computed the mean of the left-foot stride interval and the modified Kullback-Leibler divergence (MKLD) from the PDFs estimated. The analysis results suggested that both of these two statistical parameters were significantly altered in ALS, and the least-squares support vector machine (LS-SVM) may effectively distinguish the stride patterns between the ALS patients and healthy controls, with an accurate rate of 82.8% and an area of 0.87 under the receiver operating characteristic curve.
authors.affiliation: Department of Communication Engineering, School of Information Science and Technology, Xiamen University, 422 Si Ming South Road, Fujian, 361005, China. y.wu@ieee.org
authors.forename: Yunfeng
authors.initials: Y
authors.lastname: Wu
authors.forename: Sin Chun
authors.initials: SC
authors.lastname: Ng
mesh_terms: D000465:Algorithms; D000690:Amyotrophic Lateral Sclerosis / Q000150:complications / Q000175:diagnosis* / Q000503:physiopathology*; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D005684:Gait; D020233:Gait Disorders, Neurologic / Q000175:diagnosis* / Q000209:etiology / Q000503:physiopathology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016008:Statistical Distributions