Dataset Information

Quantification of movement in normal and parkinsonian macaques using video analysis.

ABSTRACT: BACKGROUND:Quantification of spontaneous animal movement can be achieved using analysis of video recordings of the animals. Previous reports of video-based methods are based on outdated computer platforms or require the use of specialized equipment. NEW METHOD:We developed a video analysis algorithm to quantify movement based on the commonly used MATLAB programming language. The algorithm is based on pixel differences between frames of video footage acquired with a standard video camera. RESULTS:The new algorithm was validated, analyzing the amount of movements made by monkeys undergoing treatment with the dopaminergic neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) to induce parkinsonism. We compared the movement quantification generated by the new system of analysis with results obtained with a conventional infrared beam break counting system, a parkinsonism rating scale, and accelerometry-based motion quantification in three rhesus macaques. The information provided by our video analysis method was consistent with that obtained with the first two methods, and more detailed than the third. COMPARISON WITH EXISTING METHODS:The new method can replace other methods to quantify movement. Although other video analysis methods have been described, some have since been deprecated, or involve the use of specialized hardware. The new method provides a straightforward and fast approach of analyzing the amount of movement in caged experimental animals, using conventional off-the-shelf equipment and moderate computing resources. CONCLUSIONS:This video analysis method provides an affordable, open access platform to quantify animal movement.

SUBMITTER: Caiola M

PROVIDER: S-EPMC6726117 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Publications

Quantification of movement in normal and parkinsonian macaques using video analysis.

Caiola Michael M Pittard Damien D Wichmann Thomas T Galvan Adriana A

Journal of neuroscience methods 20190502

<h4>Background</h4>Quantification of spontaneous animal movement can be achieved using analysis of video recordings of the animals. Previous reports of video-based methods are based on outdated computer platforms or require the use of specialized equipment.<h4>New method</h4>We developed a video analysis algorithm to quantify movement based on the commonly used MATLAB programming language. The algorithm is based on pixel differences between frames of video footage acquired with a standard video ...[more]

PMID: 31055027

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Project description:Positional preferences, asymmetry of body position and movements potentially indicate abnormal clinical conditions in infants. However, a lack of standardized nomenclature hinders accurate assessment and documentation of these preferences over time. Video tools offer a safe and reproducible method to analyze and describe infant movement patterns, aiding in physiotherapy management and goal planning. The study aimed to develop an objective classification system for infant movement patterns with particular emphasis on the specific distribution of muscle tension, using methods of computer analysis of video recordings to enhance accuracy and reproducibility in assessments. The study involved the recording of videos of 51 infants between 6 and 15 weeks of age, born at term, with an Apgar score of at least 8 points. Based on observations of a recording of infant spontaneous movements in the supine position, experts identified postural-motor patterns: symmetry and typical asymmetry linked to the asymmetrical tonic neck reflex. Deviations from the typical postural-motor system were indicated, and subcategories of atypical patterns were distinguished. A computer-based inference system was developed to automatically classify individual patterns. The following division of motor patterns was used: (1) normal patterns, including (a) typical (symmetrical, asymmetrical: variants 1 and 2); and (b) atypical (variants: 1 to 4), (2) positional preference, and (3) abnormal patterns. The proposed automatic classification method achieved an expert decision mapping accuracy of 84%. For atypical patterns, the high reproducibility of the system's results was confirmed. Lower reproducibility, not exceeding 70%, was achieved with typical patterns. Based on the observation of infant spontaneous movements, it is possible to identify movement patterns divided into typical and atypical patterns. Computer-based analysis of infant movement patterns makes it possible to objectify and satisfactorily reproduce diagnostic decisions.

Dataset Information

Quantification of movement in normal and parkinsonian macaques using video analysis.

Publications

Quantification of movement in normal and parkinsonian macaques using video analysis.

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