Mathias Wilhelm, Jan-Peter Lechler, Daniel G. Krakowczyk, S. Albayrak
{"title":"Demonstration of Finger Tracking Using Capacitive Sensing with a Ring","authors":"Mathias Wilhelm, Jan-Peter Lechler, Daniel G. Krakowczyk, S. Albayrak","doi":"10.1145/3379336.3381475","DOIUrl":null,"url":null,"abstract":"In this demo paper, we present a demonstrator for a ring-based finger tracking approach. The demonstrator consists of a ring-shaped interaction device, called PeriSense, utilizing capacitive sensing in order to enable finger tracking. The motion of the finger wearing the ring and the adjacent fingers is sensed by measuring the capacitive proximity between the electrodes and the human skin. To map the capacitive measurements to the finger angles, we apply a regression model based on long short-term memory (LSTM). A virtual 3D hand model renders simultaneous the predicted finger angles.","PeriodicalId":335081,"journal":{"name":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3379336.3381475","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this demo paper, we present a demonstrator for a ring-based finger tracking approach. The demonstrator consists of a ring-shaped interaction device, called PeriSense, utilizing capacitive sensing in order to enable finger tracking. The motion of the finger wearing the ring and the adjacent fingers is sensed by measuring the capacitive proximity between the electrodes and the human skin. To map the capacitive measurements to the finger angles, we apply a regression model based on long short-term memory (LSTM). A virtual 3D hand model renders simultaneous the predicted finger angles.