DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Namhyun | ko |
dc.contributor.author | Lee, Junseong | ko |
dc.contributor.author | Whang, Joyce Jiyoung | ko |
dc.contributor.author | Lee, Jinkyu | ko |
dc.date.accessioned | 2020-10-16T08:55:10Z | - |
dc.date.available | 2020-10-16T08:55:10Z | - |
dc.date.created | 2020-07-07 | - |
dc.date.created | 2020-07-07 | - |
dc.date.created | 2020-07-07 | - |
dc.date.created | 2020-07-07 | - |
dc.date.issued | 2020-10 | - |
dc.identifier.citation | PERSONAL AND UBIQUITOUS COMPUTING, v.24, no.5, pp.643 - 654 | - |
dc.identifier.issn | 1617-4909 | - |
dc.identifier.uri | http://hdl.handle.net/10203/276668 | - |
dc.description.abstract | Although many studies have attempted to detect the hand postures of a mobile device to utilize these postures as a user interface, they either require additional hardware or can differentiate a limited number of grips only if there is a touch event on the mobile device's screen. In this paper, we propose a novel grip sensing system, called SmartGrip, which allows a mobile device to detect different hand postures without any additional hardware and a screen touch event. SmartGrip emits carefully designed sound signals and differentiates the propagated signals distorted by different user grips. To achieve this, we analyze how a sound signal propagates from the speaker to the microphone of a mobile device and then address three key challenges: sound structure design, volume control, and feature extraction and classification. We implement and evaluate SmartGrip on three Android mobile devices. With six representative grips, SmartGrip exhibits 93.1% average accuracy for ten users in an office environment. We also demonstrate that SmartGrip operates with 83.5 to 98.3% accuracy in six different (noisy) locations. Further demonstrating the feasibility of SmartGrip as a user interface, we develop an Android application that exploits SmartGrip, validating its practical usage. | - |
dc.language | English | - |
dc.publisher | SPRINGER LONDON LTD | - |
dc.title | SmartGrip: Grip Sensing System for Commodity Mobile Devices through Sound Signals | - |
dc.type | Article | - |
dc.identifier.wosid | 000496254800001 | - |
dc.identifier.scopusid | 2-s2.0-85075213702 | - |
dc.type.rims | ART | - |
dc.citation.volume | 24 | - |
dc.citation.issue | 5 | - |
dc.citation.beginningpage | 643 | - |
dc.citation.endingpage | 654 | - |
dc.citation.publicationname | PERSONAL AND UBIQUITOUS COMPUTING | - |
dc.identifier.doi | 10.1007/s00779-019-01337-7 | - |
dc.contributor.localauthor | Whang, Joyce Jiyoung | - |
dc.contributor.nonIdAuthor | Kim, Namhyun | - |
dc.contributor.nonIdAuthor | Lee, Junseong | - |
dc.contributor.nonIdAuthor | Lee, Jinkyu | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Grip sensing system | - |
dc.subject.keywordAuthor | Mobile device | - |
dc.subject.keywordAuthor | Sound signals | - |
dc.subject.keywordAuthor | Sound structure design | - |
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