Paper
22 December 2015 A characterization of Parkinson's disease by describing the visual field motion during gait
David Trujillo, Fabio Martínez, Angélica Atehortúa, Charlens Alvarez, Eduardo Romero
Author Affiliations +
Proceedings Volume 9681, 11th International Symposium on Medical Information Processing and Analysis; 96810K (2015) https://doi.org/10.1117/12.2211438
Event: 11th International Symposium on Medical Information Processing and Analysis (SIPAIM 2015), 2015, Cuenca, Ecuador
Abstract
An early diagnosis of Parkinson’s Disease (PD) is crucial towards devising successful rehabilitation programs. Typically, the PD diagnosis is performed by characterizing typical symptoms, namely bradykinesia, rigidity, tremor, postural instability or freezing gait. However, traditional examination tests are usually incapable of detecting slight motor changes, specially for early stages of the pathology. Recently, eye movement abnormalities have correlated with early onset of some neurodegenerative disorders. This work introduces a new characterization of the Parkinson disease by describing the ocular motion during a common daily activity as the gait. This paper proposes a fully automatic eye motion analysis using a dense optical flow that tracks the ocular direction. The eye motion is then summarized using orientation histograms constructed during a whole gait cycle. The proposed approach was evaluated by measuring the χ2 distance between the orientation histograms, showing substantial differences between control and PD patients.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David Trujillo, Fabio Martínez, Angélica Atehortúa, Charlens Alvarez, and Eduardo Romero "A characterization of Parkinson's disease by describing the visual field motion during gait", Proc. SPIE 9681, 11th International Symposium on Medical Information Processing and Analysis, 96810K (22 December 2015); https://doi.org/10.1117/12.2211438
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Cited by 1 scholarly publication.
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KEYWORDS
Eye

Gait analysis

Parkinson's disease

Visualization

Motion analysis

Motion controllers

Optical flow

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