{"title":"基于频率的智能纺织品设计","authors":"J. Mikkonen, R. Townsend","doi":"10.1145/3290605.3300524","DOIUrl":null,"url":null,"abstract":"Despite the increasing amount of smart textile design practitioners, the methods and tools commonly available have not progressed to the same scale. Most smart textile interaction designs today rely on detecting changes in resistance. The tools and sensors for this are generally limited to DC-voltage-divider based sensors and multimeters. Furthermore, the textiles and the materials used in smart textile design can exhibit behaviour making it difficult to identify even simple interactions using those means. For instance, steel-based textiles exhibit intrinsic semiconductive properties that are difficult to identify with current methods. In this paper, we show an alternative way to measure interaction with smart textiles. By relying on visualisation known as Lissajous-figures and frequency-based signals, we can detect even subtle and varied forms of interaction with smart textiles. We also show an approach to measuring frequency-based signals and present an Arduino-based system called Teksig to support this type of textile practice.","PeriodicalId":20454,"journal":{"name":"Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Frequency-Based Design of Smart Textiles\",\"authors\":\"J. Mikkonen, R. Townsend\",\"doi\":\"10.1145/3290605.3300524\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Despite the increasing amount of smart textile design practitioners, the methods and tools commonly available have not progressed to the same scale. Most smart textile interaction designs today rely on detecting changes in resistance. The tools and sensors for this are generally limited to DC-voltage-divider based sensors and multimeters. Furthermore, the textiles and the materials used in smart textile design can exhibit behaviour making it difficult to identify even simple interactions using those means. For instance, steel-based textiles exhibit intrinsic semiconductive properties that are difficult to identify with current methods. In this paper, we show an alternative way to measure interaction with smart textiles. By relying on visualisation known as Lissajous-figures and frequency-based signals, we can detect even subtle and varied forms of interaction with smart textiles. We also show an approach to measuring frequency-based signals and present an Arduino-based system called Teksig to support this type of textile practice.\",\"PeriodicalId\":20454,\"journal\":{\"name\":\"Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3290605.3300524\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3290605.3300524","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Despite the increasing amount of smart textile design practitioners, the methods and tools commonly available have not progressed to the same scale. Most smart textile interaction designs today rely on detecting changes in resistance. The tools and sensors for this are generally limited to DC-voltage-divider based sensors and multimeters. Furthermore, the textiles and the materials used in smart textile design can exhibit behaviour making it difficult to identify even simple interactions using those means. For instance, steel-based textiles exhibit intrinsic semiconductive properties that are difficult to identify with current methods. In this paper, we show an alternative way to measure interaction with smart textiles. By relying on visualisation known as Lissajous-figures and frequency-based signals, we can detect even subtle and varied forms of interaction with smart textiles. We also show an approach to measuring frequency-based signals and present an Arduino-based system called Teksig to support this type of textile practice.