Sensing touch force using active acoustic sensing

Makoto Ono, Buntarou Shizuki, Jiro Tanaka

研究成果: Conference contribution

14 引用 (Scopus)

抄録

We present a lightweight technique with which creators can prototype force-sensitive objects by attaching a pair of piezoelectric elements: one a vibration speaker and one a contact microphone. The key idea behind our technique is that touch force, in addition to the way the object is touched, can also be observed as different resonant frequency spectra. We also show that recognition of a touch and estimation of the touch force can be implemented by using the combination of support vector classification (SVC) and support vector regression (SVR). An experiment with an additional pressure sensor revealed that our technique might perform well in estimating touch force. We also show a tool for machine learning based on our technique that uses an animated guide, allowing creators to give the system both the training data and the labels for training machine learning needed for dealing with continuous-valued output such as SVR.

元の言語English
ホスト出版物のタイトルTEI 2015 - Proceedings of the 9th International Conference on Tangible, Embedded, and Embodied Interaction
出版者Association for Computing Machinery, Inc
ページ355-358
ページ数4
ISBN(電子版)9781450333054
DOI
出版物ステータスPublished - 2015 1 15
外部発表Yes
イベント9th International Conference on Tangible, Embedded, and Embodied Interaction, TEI 2015 - Stanford, United States
継続期間: 2015 1 152015 1 19

Other

Other9th International Conference on Tangible, Embedded, and Embodied Interaction, TEI 2015
United States
Stanford
期間15/1/1515/1/19

Fingerprint

Acoustics
Learning systems
Pressure sensors
Microphones
Labels
Natural frequencies
Experiments

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Software

これを引用

Ono, M., Shizuki, B., & Tanaka, J. (2015). Sensing touch force using active acoustic sensing. : TEI 2015 - Proceedings of the 9th International Conference on Tangible, Embedded, and Embodied Interaction (pp. 355-358). Association for Computing Machinery, Inc. https://doi.org/10.1145/2677199.2680585

Sensing touch force using active acoustic sensing. / Ono, Makoto; Shizuki, Buntarou; Tanaka, Jiro.

TEI 2015 - Proceedings of the 9th International Conference on Tangible, Embedded, and Embodied Interaction. Association for Computing Machinery, Inc, 2015. p. 355-358.

研究成果: Conference contribution

Ono, M, Shizuki, B & Tanaka, J 2015, Sensing touch force using active acoustic sensing. : TEI 2015 - Proceedings of the 9th International Conference on Tangible, Embedded, and Embodied Interaction. Association for Computing Machinery, Inc, pp. 355-358, 9th International Conference on Tangible, Embedded, and Embodied Interaction, TEI 2015, Stanford, United States, 15/1/15. https://doi.org/10.1145/2677199.2680585
Ono M, Shizuki B, Tanaka J. Sensing touch force using active acoustic sensing. : TEI 2015 - Proceedings of the 9th International Conference on Tangible, Embedded, and Embodied Interaction. Association for Computing Machinery, Inc. 2015. p. 355-358 https://doi.org/10.1145/2677199.2680585
Ono, Makoto ; Shizuki, Buntarou ; Tanaka, Jiro. / Sensing touch force using active acoustic sensing. TEI 2015 - Proceedings of the 9th International Conference on Tangible, Embedded, and Embodied Interaction. Association for Computing Machinery, Inc, 2015. pp. 355-358
@inproceedings{161e6f82348a48148a1376dfb0fce65d,
title = "Sensing touch force using active acoustic sensing",
abstract = "We present a lightweight technique with which creators can prototype force-sensitive objects by attaching a pair of piezoelectric elements: one a vibration speaker and one a contact microphone. The key idea behind our technique is that touch force, in addition to the way the object is touched, can also be observed as different resonant frequency spectra. We also show that recognition of a touch and estimation of the touch force can be implemented by using the combination of support vector classification (SVC) and support vector regression (SVR). An experiment with an additional pressure sensor revealed that our technique might perform well in estimating touch force. We also show a tool for machine learning based on our technique that uses an animated guide, allowing creators to give the system both the training data and the labels for training machine learning needed for dealing with continuous-valued output such as SVR.",
keywords = "Acoustic classification, Machine learning, Piezoelectric sensor, Pressure, Prototyping, Support vector classification, Support vector machine, Support vector regression, Tangential force, Tangibles",
author = "Makoto Ono and Buntarou Shizuki and Jiro Tanaka",
year = "2015",
month = "1",
day = "15",
doi = "10.1145/2677199.2680585",
language = "English",
pages = "355--358",
booktitle = "TEI 2015 - Proceedings of the 9th International Conference on Tangible, Embedded, and Embodied Interaction",
publisher = "Association for Computing Machinery, Inc",

}

TY - GEN

T1 - Sensing touch force using active acoustic sensing

AU - Ono, Makoto

AU - Shizuki, Buntarou

AU - Tanaka, Jiro

PY - 2015/1/15

Y1 - 2015/1/15

N2 - We present a lightweight technique with which creators can prototype force-sensitive objects by attaching a pair of piezoelectric elements: one a vibration speaker and one a contact microphone. The key idea behind our technique is that touch force, in addition to the way the object is touched, can also be observed as different resonant frequency spectra. We also show that recognition of a touch and estimation of the touch force can be implemented by using the combination of support vector classification (SVC) and support vector regression (SVR). An experiment with an additional pressure sensor revealed that our technique might perform well in estimating touch force. We also show a tool for machine learning based on our technique that uses an animated guide, allowing creators to give the system both the training data and the labels for training machine learning needed for dealing with continuous-valued output such as SVR.

AB - We present a lightweight technique with which creators can prototype force-sensitive objects by attaching a pair of piezoelectric elements: one a vibration speaker and one a contact microphone. The key idea behind our technique is that touch force, in addition to the way the object is touched, can also be observed as different resonant frequency spectra. We also show that recognition of a touch and estimation of the touch force can be implemented by using the combination of support vector classification (SVC) and support vector regression (SVR). An experiment with an additional pressure sensor revealed that our technique might perform well in estimating touch force. We also show a tool for machine learning based on our technique that uses an animated guide, allowing creators to give the system both the training data and the labels for training machine learning needed for dealing with continuous-valued output such as SVR.

KW - Acoustic classification

KW - Machine learning

KW - Piezoelectric sensor

KW - Pressure

KW - Prototyping

KW - Support vector classification

KW - Support vector machine

KW - Support vector regression

KW - Tangential force

KW - Tangibles

UR - http://www.scopus.com/inward/record.url?scp=84924020651&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84924020651&partnerID=8YFLogxK

U2 - 10.1145/2677199.2680585

DO - 10.1145/2677199.2680585

M3 - Conference contribution

SP - 355

EP - 358

BT - TEI 2015 - Proceedings of the 9th International Conference on Tangible, Embedded, and Embodied Interaction

PB - Association for Computing Machinery, Inc

ER -