{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/data-augmentation-of-wearable-sensor-data-for","title":"Data Augmentation of Wearable Sensor Data for Parkinson's Disease Monitoring using Convolutional Neural Networks","arxiv_id":"1706.00527","date":"2017-06-02","proceeding":null,"authors":["Terry Taewoong Um","Franz Michael Josef Pfister","Daniel Pichler","Satoshi Endo","Muriel Lang","Sandra Hirche","Urban Fietzek","Dana Kulić"],"abstract":"While convolutional neural networks (CNNs) have been successfully applied to\nmany challenging classification applications, they typically require large\ndatasets for training. When the availability of labeled data is limited, data\naugmentation is a critical preprocessing step for CNNs. However, data\naugmentation for wearable sensor data has not been deeply investigated yet.\n  In this paper, various data augmentation methods for wearable sensor data are\nproposed. The proposed methods and CNNs are applied to the classification of\nthe motor state of Parkinson's Disease patients, which is challenging due to\nsmall dataset size, noisy labels, and large intra-class variability.\nAppropriate augmentation improves the classification performance from 77.54\\%\nto 86.88\\%.","url_abs":"http://arxiv.org/abs/1706.00527v2","url_pdf":"http://arxiv.org/pdf/1706.00527v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"data-augmentation-of-wearable-sensor-data-for","repo_url":"https://github.com/terryum/Data-Augmentation-For-Wearable-Sensor-Data","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"data-augmentation-of-wearable-sensor-data-for","repo_url":"https://github.com/comp-well-org/Data_Augmentation_for_Biobehavioral_Time_Series_Data","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"data-augmentation","task_name":"Data Augmentation"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1706.00527","atlas_url":"https://app.syntology.ai/?focus=1706.00527","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}