Marlène Gilles , Mireille Gagnon-Roy , Carolina Bottari , Hubert Kenfack Ngankam , Eric Maisel , Sylvain Giroux , Gireg Desmeulles , Hélène Pigot , Pierre De Loor
{"title":"定义一个推荐系统,为因创伤性脑损伤而导致认知障碍的个体配置个性化的帮助","authors":"Marlène Gilles , Mireille Gagnon-Roy , Carolina Bottari , Hubert Kenfack Ngankam , Eric Maisel , Sylvain Giroux , Gireg Desmeulles , Hélène Pigot , Pierre De Loor","doi":"10.1016/j.ijhcs.2025.103624","DOIUrl":null,"url":null,"abstract":"<div><div>Smart assistive technologies are increasingly being used to support independent living. Occupational therapists perceive such technologies as useful to helping their clients become more independent in their everyday activities, particularly individuals having sustained a traumatic brain injury. However, adapting and configuring these technologies to meet each person’s individual needs remain challenging. In this study, occupational therapists and computer scientists collaborate to develop a recommendation system designed to assist in configuring a smart assistive technology that helps people having sustained a traumatic brain injury cook safely. The relevance of the recommendations made by this case-based recommendation system was first evaluated by comparing the recommended assistant options with the selections of an expert occupational therapist. Then, we questioned the final users, i.e. occupational therapists, about the usefulness of such a system. This first prototype demonstrated promising results, with about 80% correct recommendations for selection (with an average percentage ranging from 77.0% to 86.2% depending on the threshold set for recommended functionalities, using a database of 16 cases). Additionally, the system was found to be robust against an unbalanced database and has been estimated as useful and relevant by end-users, who remain the final decision-makers. The latter also expressed concerns and suggested improvements, which were incorporated early in the development process to enhance acceptance and facilitate the tool’s integration into clinical practice. As a result, the tools and methods used by the multidisciplinary team led to the successful development of a generic human-centered recommendation system that can be used to personalize smart assistive technologies to each unique person’s needs.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"205 ","pages":"Article 103624"},"PeriodicalIF":5.1000,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Defining a recommendation system to configure personalized assistance for individuals with cognitive impairments due to a traumatic brain injury\",\"authors\":\"Marlène Gilles , Mireille Gagnon-Roy , Carolina Bottari , Hubert Kenfack Ngankam , Eric Maisel , Sylvain Giroux , Gireg Desmeulles , Hélène Pigot , Pierre De Loor\",\"doi\":\"10.1016/j.ijhcs.2025.103624\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Smart assistive technologies are increasingly being used to support independent living. Occupational therapists perceive such technologies as useful to helping their clients become more independent in their everyday activities, particularly individuals having sustained a traumatic brain injury. However, adapting and configuring these technologies to meet each person’s individual needs remain challenging. In this study, occupational therapists and computer scientists collaborate to develop a recommendation system designed to assist in configuring a smart assistive technology that helps people having sustained a traumatic brain injury cook safely. The relevance of the recommendations made by this case-based recommendation system was first evaluated by comparing the recommended assistant options with the selections of an expert occupational therapist. Then, we questioned the final users, i.e. occupational therapists, about the usefulness of such a system. This first prototype demonstrated promising results, with about 80% correct recommendations for selection (with an average percentage ranging from 77.0% to 86.2% depending on the threshold set for recommended functionalities, using a database of 16 cases). Additionally, the system was found to be robust against an unbalanced database and has been estimated as useful and relevant by end-users, who remain the final decision-makers. The latter also expressed concerns and suggested improvements, which were incorporated early in the development process to enhance acceptance and facilitate the tool’s integration into clinical practice. As a result, the tools and methods used by the multidisciplinary team led to the successful development of a generic human-centered recommendation system that can be used to personalize smart assistive technologies to each unique person’s needs.</div></div>\",\"PeriodicalId\":54955,\"journal\":{\"name\":\"International Journal of Human-Computer Studies\",\"volume\":\"205 \",\"pages\":\"Article 103624\"},\"PeriodicalIF\":5.1000,\"publicationDate\":\"2025-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Human-Computer Studies\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1071581925001818\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, CYBERNETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Human-Computer Studies","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1071581925001818","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
Defining a recommendation system to configure personalized assistance for individuals with cognitive impairments due to a traumatic brain injury
Smart assistive technologies are increasingly being used to support independent living. Occupational therapists perceive such technologies as useful to helping their clients become more independent in their everyday activities, particularly individuals having sustained a traumatic brain injury. However, adapting and configuring these technologies to meet each person’s individual needs remain challenging. In this study, occupational therapists and computer scientists collaborate to develop a recommendation system designed to assist in configuring a smart assistive technology that helps people having sustained a traumatic brain injury cook safely. The relevance of the recommendations made by this case-based recommendation system was first evaluated by comparing the recommended assistant options with the selections of an expert occupational therapist. Then, we questioned the final users, i.e. occupational therapists, about the usefulness of such a system. This first prototype demonstrated promising results, with about 80% correct recommendations for selection (with an average percentage ranging from 77.0% to 86.2% depending on the threshold set for recommended functionalities, using a database of 16 cases). Additionally, the system was found to be robust against an unbalanced database and has been estimated as useful and relevant by end-users, who remain the final decision-makers. The latter also expressed concerns and suggested improvements, which were incorporated early in the development process to enhance acceptance and facilitate the tool’s integration into clinical practice. As a result, the tools and methods used by the multidisciplinary team led to the successful development of a generic human-centered recommendation system that can be used to personalize smart assistive technologies to each unique person’s needs.
期刊介绍:
The International Journal of Human-Computer Studies publishes original research over the whole spectrum of work relevant to the theory and practice of innovative interactive systems. The journal is inherently interdisciplinary, covering research in computing, artificial intelligence, psychology, linguistics, communication, design, engineering, and social organization, which is relevant to the design, analysis, evaluation and application of innovative interactive systems. Papers at the boundaries of these disciplines are especially welcome, as it is our view that interdisciplinary approaches are needed for producing theoretical insights in this complex area and for effective deployment of innovative technologies in concrete user communities.
Research areas relevant to the journal include, but are not limited to:
• Innovative interaction techniques
• Multimodal interaction
• Speech interaction
• Graphic interaction
• Natural language interaction
• Interaction in mobile and embedded systems
• Interface design and evaluation methodologies
• Design and evaluation of innovative interactive systems
• User interface prototyping and management systems
• Ubiquitous computing
• Wearable computers
• Pervasive computing
• Affective computing
• Empirical studies of user behaviour
• Empirical studies of programming and software engineering
• Computer supported cooperative work
• Computer mediated communication
• Virtual reality
• Mixed and augmented Reality
• Intelligent user interfaces
• Presence
...