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
AN - SCOPUS:84924020651
T3 - TEI 2015 - Proceedings of the 9th International Conference on Tangible, Embedded, and Embodied Interaction
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
T2 - 9th International Conference on Tangible, Embedded, and Embodied Interaction, TEI 2015
Y2 - 15 January 2015 through 19 January 2015
ER -