[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121735-en":3,"doc-seo-121735-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},121735,34359740700684,"Finn","https://ap-avatar.wpscdn.com/avatar/1f400023980c374ae676?_k=1777273430885731487",7,"Healthcare","Development of a Pain Signaling System Using Machine Learning","A wearable pain signaling system is presented for daily care of people with severe and profound intellectual disabilities, who often cannot reliably express or communicate acute and chronic pain. The solution combines a smart sock with fabric sensors, a sensor unit delivering a 6A current and capturing electrodermal responses, and a mobile application with a machine learning algorithm to translate signals into pain predictions. A random-forest model classifies pain moments using one to five stimuli from 28 healthy participants, with accuracy improved via an ensemble of five models and voting.","VU Research Portal  \nDevelopment of a Pain Signaling System Using Machine Learning  \nKorving, Helen; Li, Sheng; Zhou, Di; Sterkenburg, Paula; Markopoulos, Panos; Barakova, Emilia  \npublished in  \n2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)  \n2023  \nDOI (link to publisher)  \n10.1109/ICASSPW59220.2023.10193643  \ndocument version  \nPublisher's PDF, also known as Version of record  \ndocument license  \nArticle 25fa Dutch Copyright Act  \nLink to publication in VU Research Portal  \ncitation for published version (APA)  \nKorving, H. , Li, S. , Zhou, D. , Sterkenburg, P. , Markopoulos, P. , & Barakova, E. (2023) . Development of a Pain Signaling System Using Machine Learning. In 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW): [Proceedings] Institute of Electrical and Electronics Engineers Inc..  \n[https://doi.org/10.1109/ICASSPW59220.2023.10193643](https://doi.org/10.1109/ICASSPW59220.2023.10193643)  \nGeneral rights  \nCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.  \n• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.  \n• You may not further distribute the material or use it for any profit-making activity or commercial gain  \n• You may freely distribute the URL identifying the publication in the public portal  \nTake down policy  \nIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.  \nE-mail address:  \n[vuresearchportal.ub@vu.nl](vuresearchportal.ub@vu.nl)  \n[Download date: 04](Download date: 04) . Nov. 2024  \n2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW) | 979-8-3503-026 1-5/23/$31.00 ©2023 IEEE | DOI: 10. 1 109/ICASSPW59220.2023. 10193643  \nDEVELOPMENT OF A PAIN SIGNALING SYSTEM USING MACHINE LEARNING  \nHelen Korving 1 ,2 ,∗ , Sheng Li3, Di Zhou4, Paula Sterkenburg2 ,5 , Panos Markopoulos 1, Emilia Barakova 1  \n1Eindhoven University of Technology, Department of Industrial Design, the Netherlands  \n2Vrije Universiteit Amsterdam, Department of Child and Family Studies, the Netherlands  \n3IEEE  \n4 School of Design Arts and Media, Nanjing University of Science and Technology, PRC  \n5Bartimus, Doorn, the Netherlands  \nABSTRACT  \nA wearable pain signaling system is introduced, to be used in the daily care for people with severe and profound intellectual disabilities. Due to several medical disorders, this group of people can experience daily acute pain and chronic pain, which they have trouble expressing and communicating to caregivers. The system consists of a smart sock with fabric sensors, a sensor unit sending a 6A current through the smart sock receiving electrodermal response and a mobile application containing a machine learning algorithm translating the signal. The pain signaling algorithm uses data of one to five painful stimuli from 28 healthy participants. Random forest modeling was used to classify moments of pain and train a model to predict pain from new data. The algorithm’s accuracy could be improved by an ensemble of five models and voting, so this groundbreaking system can become a much-wanted attribution to daily caregiving of people with disabilities.  \nIndex Terms: Pain signaling, electrodermal activity, wearable sensor, smart sock, algorithm development  \n1. INTRODUCTION  \nIn the realm of healthcare, the use of wearables has become more and more common. As early as 1956, wearable biosensors could provide information on a patient’s health status and risks of certain diseases [1] . Development and enhancement have navigated the wearables from one-time","cbCaiuKINbeYBpCT","https://ap.wps.com/l/cbCaiuKINbeYBpCT","pdf",351642,1,6,"English","en",105,"# Abstract\n# 1. Introduction\n## Wearables in healthcare and beyond\n## Wearables for non-verbal caregivers\n## Target group: severe and profound intellectual disability","[{\"question\":\"What problem does the proposed system address?\",\"answer\":\"It targets daily acute and chronic pain in people with severe and profound intellectual disabilities who have difficulty expressing and communicating pain to caregivers.\"},{\"question\":\"How does the wearable system work?\",\"answer\":\"It uses a smart sock with fabric sensors connected to a sensor unit that sends a 6A current and measures electrodermal response, while a mobile application applies a machine learning algorithm to translate the signal into pain predictions.\"},{\"question\":\"Which machine learning approach is used to detect pain?\",\"answer\":\"Random forest modeling is used to classify pain moments and train a model from data representing one to five painful stimuli from 28 healthy participants.\"}]","Development of a Pain Signaling System Using Machine Learning | PDF",1785806566,15,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"development-of-a-pain-signaling-system-using-machine-learning","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/healthcare/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/development-of-a-pain-signaling-system-using-machine-learning/121735/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the proposed system address?","Question",{"text":75,"@type":76},"It targets daily acute and chronic pain in people with severe and profound intellectual disabilities who have difficulty expressing and communicating pain to caregivers.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the wearable system work?",{"text":80,"@type":76},"It uses a smart sock with fabric sensors connected to a sensor unit that sends a 6A current and measures electrodermal response, while a mobile application applies a machine learning algorithm to translate the signal into pain predictions.",{"name":82,"@type":73,"acceptedAnswer":83},"Which machine learning approach is used to detect pain?",{"text":84,"@type":76},"Random forest modeling is used to classify pain moments and train a model from data representing one to five painful stimuli from 28 healthy participants.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,114,117,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},"Technology",50,"technology",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":115,"slug":116},40,"healthcare",{"id":118,"doc_module":4,"doc_module_name":46,"category_name":119,"show_sort_weight":120,"slug":121},8,"Research & Report",30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]