Computational Methods for Gait Analysis in Rodents
Gait analysis is important for the investigation of gait progression and the development of therapies in disorders characterized by gait impairments, such as Parkinson's disease (PD), Huntington disease (HD), and Spinal Cord Injury (SCI). Describing gait quantitatively helps researchers to analyze g...
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| Формат: | Online |
| Мова: | Англійська |
| Опубліковано: |
FAU University Press
2025
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| Предмети: | |
| Онлайн доступ: | ONIX_20251215T160010_9783961473212_49 |
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| _version_ | 1869528043362451456 |
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| author | Timotius, Ivanna Kristianti |
| author_browse | Timotius, Ivanna Kristianti |
| author_facet | Timotius, Ivanna Kristianti |
| author_sort | Timotius, Ivanna Kristianti |
| collection | Directory of Open Access Books |
| description | Gait analysis is important for the investigation of gait progression and the development of therapies in disorders characterized by gait impairments, such as Parkinson's disease (PD), Huntington disease (HD), and Spinal Cord Injury (SCI). Describing gait quantitatively helps researchers to analyze gait impairment in a more consistent, reliable, and precise manner compared to qualitative description. For this reason, apparatus and computation methods are continuously developed for both clinical and preclinical studies using animals. One of the gait analysis apparatus for rodents is called CatWalk. The system is equipped with a transparent glass floor walkway, where rodents can walk from one to the opposite end. Using a camera located under the walkway, the system records a video, which contains the information of the paw contact positions. Based on the recorded video, this CatWalk system computes several gait parameters. Here, several computational methods that enrich the information extracted from CatWalk data are presented. These methods improve the outcome of the current Catwalk data acquisition by providing methods in identifying gait patterns related to PD, providing a silhouette-length-based intra-assay scaling method, an initial data analysis method, and a parametric gait recovery progression score for rat SCI models. |
| format | Online |
| id | doab-20.500.12854ir-170231 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | FAU University Press |
| publisherStr | FAU University Press |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1702312025-12-16T05:30:21Z Computational Methods for Gait Analysis in Rodents Timotius, Ivanna Kristianti gait analysis Maschinelles Lernen CatWalk system Digitale Signalverarbeitung Animal behavior data visualization thema EDItEUR::U Computing and Information Technology::UX Applied computing::UXJ Computer applications in the social and behavioural sciences Gait analysis is important for the investigation of gait progression and the development of therapies in disorders characterized by gait impairments, such as Parkinson's disease (PD), Huntington disease (HD), and Spinal Cord Injury (SCI). Describing gait quantitatively helps researchers to analyze gait impairment in a more consistent, reliable, and precise manner compared to qualitative description. For this reason, apparatus and computation methods are continuously developed for both clinical and preclinical studies using animals. One of the gait analysis apparatus for rodents is called CatWalk. The system is equipped with a transparent glass floor walkway, where rodents can walk from one to the opposite end. Using a camera located under the walkway, the system records a video, which contains the information of the paw contact positions. Based on the recorded video, this CatWalk system computes several gait parameters. Here, several computational methods that enrich the information extracted from CatWalk data are presented. These methods improve the outcome of the current Catwalk data acquisition by providing methods in identifying gait patterns related to PD, providing a silhouette-length-based intra-assay scaling method, an initial data analysis method, and a parametric gait recovery progression score for rat SCI models. 2025-12-16T05:30:19Z 2025-12-16T05:30:19Z 2025-12-15T15:04:42Z 2020 book ONIX_20251215T160010_9783961473212_49 https://library.oapen.org/handle/20.500.12657/109169 9783961473212 9783961473205 https://directory.doabooks.org/handle/20.500.12854/170231 eng FAU Studien aus der Informatik open access image/jpeg Attribution 4.0 International https://library.oapen.org/bitstream/20.500.12657/109169/1/9783961473212.pdf FAU University Press 10.25593/978-3-96147-321-2 10.25593/978-3-96147-321-2 2c600dea-eece-4066-87be-da335e323fdb 9783961473212 9783961473205 217 Erlangen open access |
| spellingShingle | gait analysis Maschinelles Lernen CatWalk system Digitale Signalverarbeitung Animal behavior data visualization thema EDItEUR::U Computing and Information Technology::UX Applied computing::UXJ Computer applications in the social and behavioural sciences Timotius, Ivanna Kristianti Computational Methods for Gait Analysis in Rodents |
| title | Computational Methods for Gait Analysis in Rodents |
| title_full | Computational Methods for Gait Analysis in Rodents |
| title_fullStr | Computational Methods for Gait Analysis in Rodents |
| title_full_unstemmed | Computational Methods for Gait Analysis in Rodents |
| title_short | Computational Methods for Gait Analysis in Rodents |
| title_sort | computational methods for gait analysis in rodents |
| topic | gait analysis Maschinelles Lernen CatWalk system Digitale Signalverarbeitung Animal behavior data visualization thema EDItEUR::U Computing and Information Technology::UX Applied computing::UXJ Computer applications in the social and behavioural sciences |
| topic_facet | gait analysis Maschinelles Lernen CatWalk system Digitale Signalverarbeitung Animal behavior data visualization thema EDItEUR::U Computing and Information Technology::UX Applied computing::UXJ Computer applications in the social and behavioural sciences |
| url | ONIX_20251215T160010_9783961473212_49 |
| work_keys_str_mv | AT timotiusivannakristianti computationalmethodsforgaitanalysisinrodents |