Zongjian Liu, Jieling He, Jianjiang Feng, Jie Zhou
{"title":"PrinType:通过指纹识别的文本输入","authors":"Zongjian Liu, Jieling He, Jianjiang Feng, Jie Zhou","doi":"10.1145/3569491","DOIUrl":null,"url":null,"abstract":"A 12-person user study was conducted to evaluate the performance of different strategies. Our user evaluation showed that participants achieved an average of 29.56, 32.38, and 34.22 WPM with 0.79%, 0.20%, and 0.21% not corrected error rate in the three strategies. In addition, we provided a detailed analysis of various micro metrics to further understand user performance and technical characteristics. Overall, PrinType is favored by users for its usability, efficiency, and novelty.","PeriodicalId":20463,"journal":{"name":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.","volume":"6 1","pages":"174:1-174:31"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PrinType: Text Entry via Fingerprint Recognition\",\"authors\":\"Zongjian Liu, Jieling He, Jianjiang Feng, Jie Zhou\",\"doi\":\"10.1145/3569491\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A 12-person user study was conducted to evaluate the performance of different strategies. Our user evaluation showed that participants achieved an average of 29.56, 32.38, and 34.22 WPM with 0.79%, 0.20%, and 0.21% not corrected error rate in the three strategies. In addition, we provided a detailed analysis of various micro metrics to further understand user performance and technical characteristics. Overall, PrinType is favored by users for its usability, efficiency, and novelty.\",\"PeriodicalId\":20463,\"journal\":{\"name\":\"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.\",\"volume\":\"6 1\",\"pages\":\"174:1-174:31\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3569491\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3569491","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A 12-person user study was conducted to evaluate the performance of different strategies. Our user evaluation showed that participants achieved an average of 29.56, 32.38, and 34.22 WPM with 0.79%, 0.20%, and 0.21% not corrected error rate in the three strategies. In addition, we provided a detailed analysis of various micro metrics to further understand user performance and technical characteristics. Overall, PrinType is favored by users for its usability, efficiency, and novelty.