TY - GEN
T1 - VibSense
T2 - 14th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2017
AU - Liu, Jian
AU - Chen, Yingying
AU - Gruteser, Marco
AU - Wang, Yan
N1 - Funding Information:
IX. ACKNOWLEDGEMENT This work was partially supported by the National Science Foundation Grants CNS-1409767, CNS-1514436, CNS-1409811 and CNS-1618019.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/6/30
Y1 - 2017/6/30
N2 - VibSense pushes the limits of vibration-based sensing to determine the location of a touch on extended surface areas as well as identify the object touching the surface leveraging a single sensor. Unlike capacitive sensing, it does not require conductive materials and compared to audio sensing it is more robust to acoustic noise. It supports a broad array of applications through either passive or active sensing using only a single sensor. In VibSense's passive sensing, the received vibration signals are determined by the location of the touch impact. This allows location discrimination of touches precise enough to enable emerging applications such as virtual keyboards on ubiquitous surfaces for mobile devices. Moreover, in the active mode, the received vibration signals carry richer information of the touching object's characteristics (e.g., weight, size, location and material). This further enables VibSense to match the signals to the trained profiles and allows it to differentiate personal objects in contact with any surface. VibSense is evaluated extensively in the use cases of localizing touches (i.e., virtual keyboards), object localization and identification. Our experimental results demonstrate that VibSense can achieve high accuracy, over 95%, in all these use cases.
AB - VibSense pushes the limits of vibration-based sensing to determine the location of a touch on extended surface areas as well as identify the object touching the surface leveraging a single sensor. Unlike capacitive sensing, it does not require conductive materials and compared to audio sensing it is more robust to acoustic noise. It supports a broad array of applications through either passive or active sensing using only a single sensor. In VibSense's passive sensing, the received vibration signals are determined by the location of the touch impact. This allows location discrimination of touches precise enough to enable emerging applications such as virtual keyboards on ubiquitous surfaces for mobile devices. Moreover, in the active mode, the received vibration signals carry richer information of the touching object's characteristics (e.g., weight, size, location and material). This further enables VibSense to match the signals to the trained profiles and allows it to differentiate personal objects in contact with any surface. VibSense is evaluated extensively in the use cases of localizing touches (i.e., virtual keyboards), object localization and identification. Our experimental results demonstrate that VibSense can achieve high accuracy, over 95%, in all these use cases.
UR - http://www.scopus.com/inward/record.url?scp=85031698724&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85031698724&partnerID=8YFLogxK
U2 - 10.1109/SAHCN.2017.7964907
DO - 10.1109/SAHCN.2017.7964907
M3 - Conference contribution
AN - SCOPUS:85031698724
T3 - 2017 14th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2017
BT - 2017 14th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2017
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 June 2017 through 14 June 2017
ER -