EP 52. PREGAIT study – Pattern recognition and differential diagnosis of neurological gait disorders in instrumental and clinical gait analysis. Issue 9 (September 2016)

• Record Type: Journal Article
• Authors: Möhwald, K.; Pradhan, C.; Wuehr, M.; Dieterich, M.; Brandt, T.; Jahn, K.; Schniepp, R.
• Is Part Of: Clinical neurophysiology. Volume 127:Issue 9(2016:Sep.)
• Page Start: e260
• Publication Date: 2016-09
• Subjects: Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2016.05.106
• Languages: English
• ISSNs: 1388-2457

Abstract

Abstract : Background: Gait disturbances are a common symptom in neurological disorders. About 70% of neurological inpatients show an abnormal gait. This results in decreased mobility, an increased risk for falls and therefore, a decrement in health-related quality of life. Instrumental gait analysis is used to characterize gait disturbances analyzing spatio-temporal parameters and video data. The aim of the study is to compare the clinical gait analysis with the standardized instrumental gait analysis. Methods/design: Clinically confirmed cases of hypokinetic, atactic, phobic, paretic, antalgic, spastic, hyperkinetic and bizarre gait disturbances will be recruited for this prospective study. The patients will undergo 8 different gait measurements walking across a GAITRite® sensor carpet, while standardized gait parameters and video data are being collected. For analysis clinicians will be divided into 4 groups, each group will analyze the gait data of different packages with a limited data set (package 1: "video preferred walking speed", package 2: "videos of all gait conditions", package 3: "spatio-temporal gait parameters", package 4: "all available data"). Sensitivity and specificity of the clinician's diagnoses will be compared among the 4 groups. Furthermore, an automated pattern recognition system for gait pattern classification will be used to compare the computed results with the clinician's results. Discussion: This study investigates the use of different gait analysis methods and the automated pattern recognition procedures within neurological gait disorders. The comparison will determine the advantages and disadvantages of each method, which will further help to improve the instrumental and clinical gait analysis in the clinical routine.