journal article·2026-07-05Open access

Differential Sensing of Lamb Wave Using Piezoelectric Transducer for Baseline-Free Tactile Sensing on a Glass Plate

Che-Yu Chieng, Yung-Chun Lee

Applied Sciences· Volume 16· Issue 13

Abstract

This paper utilizes only the anti-symmetric fundamental (A0) mode of Lamb waves for tactile sensing to realize a baseline-free ultrasound-based touchscreen. Disk-shaped piezoelectric transducers are mounted in pair on a glass plate to excite and detect pure A0 mode Lamb waves. When there is no finger touch, the symmetric nature of the boundary conditions ensures that the combined output wave signals from paired transducers are basically zero, which eliminates the need for reference or baseline signals. When there is a finger touch, the output wave signals can directly couple with a trained artificial intelligence (AI) model based on a convolutional neural network (CNN) to identify the touch and its touch position. Field tests show the accuracy for tactile position sensing is 96% and is not affected by environmental temperature variation. This demonstrates the effectiveness and robustness of the proposed baseline-free Lamb wave touchscreen as a human–machine interface.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Tactile and Sensory Interactions · Advanced Sensor and Energy Harvesting Materials · Surface Roughness and Optical Measurements

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Mechanical Engineering, National Cheng Kung University, Tainan 70101, Taiwan

Funding

National Science and Technology Council of Taiwan

References (24)

Show source-provided references
1. A review of technologies for sensing contact location on the surface of a display10.1002/jsid.100 ↗
2. Economical touch panel using SAW absorption10.1109/T-UFFC.1987.26932 ↗
3. Takeuchi, M., Tanaka, Y., Aroyan, J.L., and Kent, J. (2006, January 2–6). Characteristics of SAW grating reflectors with arbitrary angles of incidence in ultrasonic touch sensors. Proceedings of the 2006 IEEE Ultrasonics Symposium, Vancouver, BC, Canada.
4. In solid localization of finger impacts using acoustic time-reversal process10.1063/1.2130720 ↗
5. Reis, S., Correia, S.V., Martins, M., Barbosa, G., Sousa, R.M., Minas, G., Lanceros-Mendez, S., and Rocha, J.G. (2010, January 4–7). Touchscreen based on acoustic pulse recognition with piezoelectric polymer sensors. Proceedings of the 2010 IEEE International Symposium on Industrial Electronics, Bari, Italy.10.1109/ISIE.2010.5637672 ↗
6. Localization of taps on solid surfaces for human-computer touch interfaces10.1109/TMM.2013.2264656 ↗
7. Feasibility study on multi-touch ultrasound large-panel touchscreen using guided lamb waves10.1016/j.measurement.2022.110755 ↗
8. Lamb wave multitouch ultrasonic touchscreen10.1109/TUFFC.2016.2608781 ↗
9. Firouzi, K., Nikoozadeh, A., Carver, T.E., and Khuri-Yakub, B.T. (2017, January 6–9). Multitouch touchscreen using reverberant lamb waves. Proceedings of the 2017 IEEE International Ultrasonics Symposium (IUS), Washington, DC, USA.10.1109/ULTSYM.2017.8092369 ↗
10. Touchscreen surface based on interaction of ultrasonic guided waves with a contact impedance10.1109/JSEN.2016.2535386 ↗
11. Tactile objects based on an amplitude disturbed diffraction pattern method10.1063/1.3276549 ↗
12. An acoustic multi-touch sensing method using amplitude disturbed ultrasonic wave diffraction patterns10.1016/j.sna.2010.03.020 ↗
13. Yang, Z., Liu, X., Wu, B., and Liu, R. (2021). Adaptability of ultrasonic lamb wave touchscreen to the variations in touch force and touch area. Sensors, 21.10.3390/s21051736 ↗
14. Chang, C.-S., and Lee, Y.-C. (2020). Ultrasonic touch sensing system based on Lamb waves and convolutional neural network. Sensors, 20.10.3390/s20092619 ↗
15. Bahrami, S., Moriot, J., Masson, P., and Grondin, F. (2022). Machine learning for touch localization on an ultrasonic Lamb wave touchscreen. Sensors, 22.10.3390/s22093183 ↗
16. Design of underwater acoustic touchscreen based on deep convolutional neural network10.1016/j.apacoust.2023.109222 ↗
17. Application of artificial neural networks and probability ellipse methods for damage detection using Lamb waves10.1016/j.compstruct.2015.07.089 ↗
18. Improved damage localization and quantification of CFRP using Lamb waves and convolution neural network10.1109/JSEN.2019.2908838 ↗
19. Deep learning based crack damage detection technique for thin plate structures using guided lamb wave signals10.1088/1361-665X/ab58d6 ↗
20. Lamb wave based damage detection in metallic plates using multi-headed 1-dimensional convolutional neural network10.1088/1361-665X/abdd00 ↗
21. Azuara, G., Ruiz, M., and Barrera, E. (2021). Damage localization in composite plates using wavelet transform and 2-D convolutional neural networks. Sensors, 21.10.3390/s21175825 ↗
22. A review in guided-ultrasonic-wave-based structural health monitoring: From fundamental theory to machine learning techniques10.1016/j.ultras.2023.107014 ↗
23. A Tutorial on the Cross-Entropy Method10.1007/s10479-005-5724-z ↗
24. Kingma, D.P., and Ba, J. (2015, January 7–9). Adam: A method for Stochastic Optimization. Proceedings of the 3rd International Conference on Learning Representations, San Diego, CA, USA.