Paper
21 December 2018 Parkinsonian hand tremor characterization from magnified video sequences
Sergio Contreras, Isail Salazar, Fabio Martínez
Author Affiliations +
Proceedings Volume 10975, 14th International Symposium on Medical Information Processing and Analysis; 1097503 (2018) https://doi.org/10.1117/12.2512109
Event: 14th International Symposium on Medical Information Processing and Analysis, 2018, Mazatlán, Mexico
Abstract
Resting hand tremor is one of the most important biomarkers in Parkinson’s disease (PD). This indicator is mainly described as periodic oscillatory movements when hands are completely supported, i.e., without voluntary muscle contraction. Such characterization is however very difficult to observe in standard clinical analysis, due to the imperceptible low tremor amplitude. Furthermore, in early stages of PD those motions are commonly misclassified as control patterns. Common clinical practice often suggests a physical tremor magnification by forcing postural hand configurations, dealing with natural strain motions that might disturb tremor behavior. In this work was introduced a video characterization that highlights hand tremor patterns from resting and postural setups. Initially, each of videos are represented as a bank of spatial and temporal filters. Then, specific spatio-temporal bands are amplified to stand out tremor patterns. A set of anatomical points of interest was fixed to be quantitatively assessed along the magnified sequence. Temporal variance of these points were associated with tremor recorded in videos. The proposed approach was evaluated in a total of 80 videos recording hands in resting and postural configurations. Variance analysis was performed to measure temporal amplitude differences of tremor in PD and control videos. In resting validation, a gain of 7.76 dB was achieved in parkinsonian and control comparison by using amplified videos. While physical magnification obtains a F-test of 5.19, the proposed optical magnification yields a F-test of 8.19, allowing a better quantification of the disease.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sergio Contreras, Isail Salazar, and Fabio Martínez "Parkinsonian hand tremor characterization from magnified video sequences", Proc. SPIE 10975, 14th International Symposium on Medical Information Processing and Analysis, 1097503 (21 December 2018); https://doi.org/10.1117/12.2512109
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KEYWORDS
Video

Statistical analysis

Motion analysis

Cameras

Spatial frequencies

Electromyography

Motion models

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