An Explicable Keystroke Recognition Algorithm for Customizable Ring-Type Keyboards

In our previous work, we developed an IMU (Inertial Measurement Unit) based smart ring that allows users to type characters without a physical keyboard and adopt well-known pattern recognition algorithms, such as Support Vector Machine (SVM), and Naive Bayes (NB), for keystroke recognition. However,...

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Veröffentlicht in:	IEEE access Jg. 8; S. 22933 - 22944
Hauptverfasser:	Sha, Xiaopeng, Lian, Chao, Zhao, Yuliang, Yu, Jianing, wang, shuyu, Li, Wen Jung
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Acceleration Algorithms Classification Decision trees feature analysis Feature extraction human–computer interaction Inertial platforms Keyboards keystroke recognition motion detection Pattern recognition recognition algorithm Support vector machines Virtual keyboard
ISSN:	2169-3536, 2169-3536
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Abstract	In our previous work, we developed an IMU (Inertial Measurement Unit) based smart ring that allows users to type characters without a physical keyboard and adopt well-known pattern recognition algorithms, such as Support Vector Machine (SVM), and Naive Bayes (NB), for keystroke recognition. However, these algorithms always require intensive computing resources or offer limited recognition accuracy. Moreover, they are often seen as black boxes incapable of providing readily comprehensible and visible clues for classification. This hampers the improvement of keystroke recognition accuracy and the ring-type virtual keyboard's character layout design. Here we present a novel algorithm to recognize keystrokes in a fast and accurate manner. Firstly, the standard feature vector, including five attitude angle features and one acceleration feature, is built to express a specific stroke. Then, the feature vector of the testing keystroke is compared with the standard features. The most similar keystroke is matched and recognized after three times of voting. Based on this algorithm, we can identify the easily confused keystrokes and understand the mechanisms behind it. With this interpretability, we will be able to achieve the customized ring-type virtual keyboard application if necessary. The performance of this algorithm was evaluated by using a dataset with 1500 keystrokes of three different subjects. The results show that our algorithm is more effective in keystroke recognition than traditional algorithms for this ring-type keyboard. In addition to its application on virtual keyboards, this algorithm can also be potentially applied on other classification tasks with easy-to-understand results.
AbstractList	In our previous work, we developed an IMU (Inertial Measurement Unit) based smart ring that allows users to type characters without a physical keyboard and adopt well-known pattern recognition algorithms, such as Support Vector Machine (SVM), and Naive Bayes (NB), for keystroke recognition. However, these algorithms always require intensive computing resources or offer limited recognition accuracy. Moreover, they are often seen as black boxes incapable of providing readily comprehensible and visible clues for classification. This hampers the improvement of keystroke recognition accuracy and the ring-type virtual keyboard's character layout design. Here we present a novel algorithm to recognize keystrokes in a fast and accurate manner. Firstly, the standard feature vector, including five attitude angle features and one acceleration feature, is built to express a specific stroke. Then, the feature vector of the testing keystroke is compared with the standard features. The most similar keystroke is matched and recognized after three times of voting. Based on this algorithm, we can identify the easily confused keystrokes and understand the mechanisms behind it. With this interpretability, we will be able to achieve the customized ring-type virtual keyboard application if necessary. The performance of this algorithm was evaluated by using a dataset with 1500 keystrokes of three different subjects. The results show that our algorithm is more effective in keystroke recognition than traditional algorithms for this ring-type keyboard. In addition to its application on virtual keyboards, this algorithm can also be potentially applied on other classification tasks with easy-to-understand results.
Author	Zhao, Yuliang Sha, Xiaopeng wang, shuyu Li, Wen Jung Yu, Jianing Lian, Chao
Author_xml	– sequence: 1 givenname: Xiaopeng orcidid: 0000-0003-3323-7322 surname: Sha fullname: Sha, Xiaopeng organization: School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China – sequence: 2 givenname: Chao orcidid: 0000-0002-1919-3063 surname: Lian fullname: Lian, Chao organization: School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China – sequence: 3 givenname: Yuliang orcidid: 0000-0002-4519-7404 surname: Zhao fullname: Zhao, Yuliang email: zhaoyuliang@neuq.edu.cn organization: School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China – sequence: 4 givenname: Jianing orcidid: 0000-0001-6649-1330 surname: Yu fullname: Yu, Jianing organization: School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China – sequence: 5 givenname: shuyu orcidid: 0000-0002-0038-1347 surname: wang fullname: wang, shuyu organization: School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China – sequence: 6 givenname: Wen Jung orcidid: 0000-0001-9616-6213 surname: Li fullname: Li, Wen Jung email: wenjli@cityu.edu.hk organization: Department of Mechanical Engineering, City University of Hong Kong, Hong Kong
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SubjectTerms	Acceleration Algorithms Classification Decision trees feature analysis Feature extraction human–computer interaction Inertial platforms Keyboards keystroke recognition motion detection Pattern recognition recognition algorithm Support vector machines Virtual keyboard
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Title	An Explicable Keystroke Recognition Algorithm for Customizable Ring-Type Keyboards
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