A novel approach for analysis of altered gait variability in amyotrophic lateral sclerosis.
Gait variability reflects important information for the maintenance of human beings' health. For pathological populations, changes in gait variability signal the presence of abnormal motor control strategies. Quantitative analysis of the altered gait variability in patients with amyotrophic lateral...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 54; no. 9; pp. 1399 - 1409 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Sep2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=117576405&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 117576405 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Sep2016 vid: 54 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 117576405 117576405 NLM26518306 10.1007/s11517-015-1413-5 NLM26518306 117576405 ppf: 1399 ppct: 10 formats: fmt: @attributes: type: P tig: atl: A novel approach for analysis of altered gait variability in amyotrophic lateral sclerosis. aug: au: Xia, Yi Gao, Qingwei Lu, Yixiang Ye, Qiang affil: School of Electrical Engineering and Automation , Anhui University , 111 JiuLong Road Hefei 230601 People's Republic of China sug: subj: Amyotrophic Lateral Sclerosis Physiopathology Gait Physiology Monitoring, Physiologic Methods Aged Female Case Control Studies Middle Age Gait Disorders, Neurologic Physiopathology ROC Curve Physics Male Adult Aged: 65+ years Middle Aged: 45-64 years Adult: 19-44 years Female Male ab: Gait variability reflects important information for the maintenance of human beings' health. For pathological populations, changes in gait variability signal the presence of abnormal motor control strategies. Quantitative analysis of the altered gait variability in patients with amyotrophic lateral sclerosis (ALS) will be helpful for either diagnosing or monitoring pathological progression of the disease. Thus, we applied Teager energy operator, an energy measure that can highlight the deviations from moment to moment of a time series, to produce an instantaneous energy time series. Then, two important features were extracted to assess the variability of the new time series. First, the standard deviation statistics were used to measure the magnitude of the variability. Second, to quantify the temporal structural characteristics of the variability, the permutation entropy was applied as a tool from the nonlinear dynamics. In the classification experiments, the two proposed features were input to the support vector machine classifier, and the dataset consists of 12 ALS patients and 16 healthy control subjects. The experimental results showed that an area of 0.9643 under the receiver operating characteristic curve was achieved, and the classification accuracy evaluated by leave-one-out cross-validation method could reach 92.86 %. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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