Tactile Evaluation Feedback System for Multi-Layered Structure Inspired by Human Tactile Perception Mechanism - PubMed (original) (raw)
Tactile Evaluation Feedback System for Multi-Layered Structure Inspired by Human Tactile Perception Mechanism
Iza Husna Mohamad Hashim et al. Sensors (Basel). 2017.
Abstract
Tactile sensation is one type of valuable feedback in evaluating a product. Conventionally, sensory evaluation is used to get direct subjective responses from the consumers, in order to improve the product's quality. However, this method is a time-consuming and costly process. Therefore, this paper proposes a novel tactile evaluation system that can give tactile feedback from a sensor's output. The main concept of this system is hierarchically layering the tactile sensation, which is inspired by the flow of human perception. The tactile sensation is classified from low-order of tactile sensation (LTS) to high-order of tactile sensation (HTS), and also to preference. Here, LTS will be correlated with physical measures. Furthermore, the physical measures that are used to correlate with LTS are selected based on four main aspects of haptic information (roughness, compliance, coldness, and slipperiness), which are perceived through human tactile sensors. By using statistical analysis, the correlation between each hierarchy was obtained, and the preference was derived in terms of physical measures. A verification test was conducted by using unknown samples to determine the reliability of the system. The results showed that the system developed was capable of estimating preference with an accuracy of approximately 80%.
Keywords: affective engineering; sensory evaluation; tactile sensation; tactile sensor.
Conflict of interest statement
The authors declare no conflict of interest.
Figures
Figure 1
Hierarchical layered structure of tactile sensation and physical measures.
Figure 2
Cross-sectional structure types of door armrest samples.
Figure 3
Experimental apparatus for measuring vibration.
Figure 4
Measurement of bulk displacement.
Figure 5
Measurement of thermal property.
Figure 6
Experimental apparatus for measuring frictional force.
Figure 7
Multiple regression analysis result.
Figure 8
Comparison between actual and estimated scores.
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References
- Citrin A.V., Stem D.E., Spangenberg E.R., Clark M.J. Consumer need for tactile input. J. Bus. Res. 2003;56:915–922. doi: 10.1016/S0148-2963(01)00278-8. - DOI
- McCabe D.B., Nowlis S.M. The effect of examining actual products or product descriptions on consumer preference. J. Consum. Psychol. 2003;13:431–439. doi: 10.1207/S15327663JCP1304_10. - DOI
- Peck J., Childers T.L. To have and to hold: The influence of haptic information on product judgments. J. Mark. 2003;67:35–48. doi: 10.1509/jmkg.67.2.35.18612. - DOI
- Nishimatsu T., Takahashi T., Kanai H., Ishizawa H., Matsumoto Y., Toba E. Influence of combination of covering fabrics and seat pad on sitting comfort of automotive seat. J. Text. Mach. Soc. Jpn. 2004;57:T67–T72. doi: 10.4188/transjtmsj.57.T67. - DOI
- Shen Y., Pomeory C., Xi N., Chen Y. Quantification and verification of automobile interior textures by a high performance tactile-haptic interface; Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems; Beijing, China. 9–13 October 2006; pp. 3773–3778.
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