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Design and experimental testing of a tactile sensor for self-compensation of contact error in soft tissue stiffness measurement

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Abstract

The measurement of viscoelastic properties of soft tissues has become a research interest with applications in the stiffness estimation of soft tissues, sorting and quality control of postharvest fruit, and fruit ripeness estimation. This paper presents a tactile sensor configuration to estimate the stiffness properties of soft tissues, using fruit as case study. Previous stiffness-measuring tactile sensor models suffer from unstable and infinite sensor outputs due to irregularities and inclination angles of soft tissue surfaces. The proposed configuration introduces two low stiffness springs at the extreme ends of the sensor with one high stiffness spring in-between. This study also presents a closed form mathematical model that considers the maximum inclination angle of the tissue’s (fruit) surface, and a finite element analysis to verify the mathematical model, which yielded stable sensor outputs. A prototype of the proposed configuration was fabricated and tested on kiwifruit samples. The experimental tests revealed that the sensor’s output remained stable, finite, and independent on both the inclination angle of the fruit surface and applied displacement of the sensor. The sensor distinguished between kiwifruit at various stiffness and ripeness levels with an output error ranging between 0.18 % and 3.50 %, and a maximum accuracy of 99.81 %, which is reasonable and competitive compared to previous design concepts.

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Abbreviations

θ :

Inclination angle between sensor and the fruit tissue

θ max :

Maximum inclination angle

θ̃ :

Vertical component angle due to the inclination

C k :

Scaling factor

E f :

Elastic modulus of the fruit

F H :

High stiffness spring force

F L :

Low stiffness spring force

K f :

Fruit tissue stiffness

K h :

High stiffness spring constant

K H :

Equivalent high stiffness spring

K I :

Low stiffness spring constant

K L :

Equivalent low stiffness spring

L :

Distance between the sensor tips

NL :

Nonlinearity error

Ra :

Roughness average of the fruit’s tissue surface

r 1 :

Indenter radius

S :

Sensor output

S max :

Maximum output at end of measurement range

v :

Poisson’s ratio

x :

Applied displacement of the sensor

References

  1. L. Kitinoja, S. Saran, K. Roy and A. A. Kader, Postharvest technology for developing countries: challenges and opportunities in research, outreach and advocacy, Journal of the Science of Food and Agriculture, 91 (4) (2011) 597–603.

    Article  Google Scholar 

  2. Y. Chen, W. L. Cai, X. J. Zou and H. P. Xiang, Extrusion mechanical properties of fresh litchi, Transactions of the Chinese Society of Agricultural Engineering, 27 (8) (2011) 360–364.

    Google Scholar 

  3. S. Tian, J. Wang and H. Xu, Firmness measurement of kiwifruit using a self-designed device based on acoustic vibration technology, Postharvest Biology and Technology, 187 (2022) 111851.

    Article  Google Scholar 

  4. A. H. Gómez, G. Hu, J. Wang and A. G. Pereira, Evaluation of tomato maturity by electronic nose, Computers and Electronics in Agriculture, 54 (1) (2006) 44–52.

    Article  Google Scholar 

  5. E. H. Yossy, J. Pranata, T. Wijaya, H. Hermawan and W. Budiharto, Mango fruit sortation system using neural network and computer vision, Procedia Computer Science, 116 (2017) 596–603.

    Article  Google Scholar 

  6. M. Shiddiq, F. Fitmawati, R. Anjasmara, N. Sari and Hefniati, Ripeness detection simulation of oil palm fruit bunches using laser-based imaging system, AIP Conference Proceedings, 1801 (2017) 050003.

    Article  Google Scholar 

  7. M. Dadwa and V. K. Banga, Color image segmentation for fruit, 2nd International Conference on Electrical, Electronics and Civil Engineering, Singapore (2012).

  8. Q. Meng, J. Shang, R. Huang and Y. Zhang, Determination of soluble solids content and firmness in plum using hyperspectral imaging and chemometric algorithms, Journal of Food Process Engineering, 44 (1) (2021) e13597.

    Article  Google Scholar 

  9. Y. Dong, Y. Huang, B. Xu, B. Li and B. Guo, Bruise detection and classification in jujube using thermal imaging and densenet, Journal of Food Process Engineering, 45 (3) (2021) e13981.

    Google Scholar 

  10. H. Kang and C. Chen, Fast implementation of real-time fruit detection in apple orchards using deep learning, Computers and Electronics in Agriculture, 168 (2020) 105108.

    Article  Google Scholar 

  11. F. J. García-Ramos, C. Valero, I. Homer, J. Ortiz-Cañavate and M. Ruiz-Altisent, Non-destructive fruit firmness sensors: a review, Spanish Journal of Agricultural Research, 3 (1) (2005) 61–73.

    Article  Google Scholar 

  12. F. Zahed, A. Mohammad and H. B. S. Reza, Nondestructive methods for determining the firmness of apple fruit flesh, Information Processing in Agriculture, 8 (4) (2021) 515–527.

    Article  Google Scholar 

  13. J. Sun, R. Künnemeyer and A. McGlone, Optical methods for firmness assessment of fresh produce: a review, Postharvest Handling, IntechOpen, London (2017).

    Google Scholar 

  14. T. Shijie and X. Huirong, Mechanical-based and optical-based methods for nondestructive evaluation of fruit firmness, Food Reviews International (2022) 2015376.

  15. A. Fekete and J. Felföldi, Firmness-based expert system for fruit quality assessment, IFAC Proc. Volumes (1998) 61–65.

  16. H. Zhu, L. Yang, J. Fei, L. Zhao and Z. Han, Recognition of carrot appearance quality based on deep feature and support vector machine, Computers and Electronics in Agriculture, 186 (2021) 106185.

    Article  Google Scholar 

  17. H. Zhu, L. Yang, Y. Sun and Z. Han, Identifying carrot appearance quality by an improved dense capnet, Journal of Food Process Engineering, 44 (1) (2021) e13586.

    Article  Google Scholar 

  18. T. Kunpeng, S. Cheng, L. Xianwang, H. Jicheng, C. Qiaomin and Z. Bin, Mechanical properties and compression damage simulation by finite element for kiwifruit, International Agricultural Engineering Journal, 26 (4) (2017) 193–203.

    Google Scholar 

  19. A. Jahanbakhshi, R. Yeganeh and G. Shahgoli, Determination of mechanical properties of banana fruit under quasi-static loading in pressure, bending, and shearing tests, International Journal of Fruit Science, 20 (3) (2020) 314–322.

    Article  Google Scholar 

  20. G. Shahgholi, M. Latifi and A. Jahanbakhshi, Potato creep analysis during storage using experimental measurement and finite element method (FEM), Journal of Food Process Engineering, 43 (11) (2020) e13522.

    Article  Google Scholar 

  21. C. T. Nnodim, A. M. R. Fath-ElBab, B. W. Ikua and D. N. Sila, Design, simulation, and experimental testing of a tactile sensor for fruit ripeness detection, Transactions on Engineering Technologies, Springer Nature Singapore (2021) 59–73.

  22. C. T. Nnodim, A. M. R. Fath El-Bab, B. W. Ikua and D. N. Sila, Estimation of the modulus of elasticity of mango for fruit sorting, International Journal of Mechanical and Mechatronics Engineering, 19 (2) (2019) 1–10.

    Google Scholar 

  23. C. T. Christopher, A. M. R. FathElbab, C. O. Osueke, B. W. Ikua, D. N. Sila and A. Fouly, A piezoresistive dual-tip stiffness tactile sensor for mango ripeness assessment, Cogent Engineering, 9 (1) (2022) 2030098.

    Article  Google Scholar 

  24. T. Tsuji, Y. Kaneko and S. Abe, Whole-body force sensation by force sensor with shell-shaped end-effector, IEEE Transactions on Industrial Electronics, 56 (5) (2009) 1375–1382.

    Article  Google Scholar 

  25. A. Esmaeel, K. I. E. Ahmed and A. M. R. FathEl-Bab, Determination of damping coefficient of soft tissues using piezoelectric transducer, Biomedical Microdevices, 23 (2) (2021) 23.

    Article  Google Scholar 

  26. A. M. Fath El-Bab, M. E. Eltaib, M. M. Sallam and O. Tabata, Tactile sensor for compliance detection, Sensors and Materials, 19 (3) (2007) 165–177.

    Google Scholar 

  27. A. Fath El-Bab, T. Tamura, K. Sugano, T. Tsuchiya, O. Tabata, M. E. H. Eltaib and M. Sallam, Design and simulation of a tactile sensor for soft-tissue compliance detection, IEEJ Transactions on Sensors and Micromachines, 128 (5) (2008) 186–192.

    Article  Google Scholar 

  28. A. Fouly, A. Fath El-Bab, M. Nasr and A. Abouelsoud, Modeling and experimental testing of three-tip configuration tactile sensor for compensating the error due to soft tissue surface irregularities during stiffness detection, Measurement, 98 (2017) 112–122.

    Article  Google Scholar 

  29. ASME B46.1-2019, Surface Texture (Surface Roughness, Waviness, and Lay), The American Society of Mechanical Engineers, New York (2019).

  30. S. Hall, Fluid flow, Chapter 1, Rules of Thumb for Chemical Engineers, 5th Ed., Butterworth-Heinemann, Oxford (2012).

    Google Scholar 

  31. A. Fouly, A. M. R. Fath El Bab, A. A. Abouelsoud and M. N. Nasr, Error source identification in measuring soft tissue stiffness and self compensating this error using three probes configuration, 2016 7th IEEE International Conference on Intelligent Systems, Modelling and Simulation, Bangkok (2016).

  32. W. C. Hayes, L. M. Keer, G. Herrmann and L. F. Mockros, A mathematical analysis for indentation tests of articular cartilage, Journal of Biomechanics, 5 (5) (1972) 541–551.

    Article  Google Scholar 

  33. Z. E. Zhou, Physical Properties of Agricultural Materials, China Agricultural Press, Beijing (1994).

    Google Scholar 

  34. M. Zhang, Y. P. Zheng and A. F. T. Mak, Estimating the effective Young’s modulus of soft tissues from indentation tests — nonlinear finite element analysis of effects of friction and large deformation, Medical Engineering and Physics, 19 (6) (1997) 512–517.

    Article  Google Scholar 

Download references

Acknowledgments

This study was supported, for the first author, by the Egypt-Japan University of Science and Technology (E-JUST) scholarship, co-sponsored between the Egyptian Ministry of Higher Education (MoHE) and the Japan International Cooperation Agency (JICA). The authors thank the Science and Technology Development Fund (STDF-12417 project) of the Egyptian Ministry of Scientific Research for providing the equipment used in this research at the Micro Fabrication Centre of E-JUST.

Author information

Authors and Affiliations

  1. Department of Mechatronics and Robotics Engineering, Egypt-Japan University of Science and Technology, New Borg El-Arab City, 21934, Alexandria, Egypt

    Frank Efe Erukainure, Victor Parque & Ahmed M. R. FathEl-Bab

  2. Department of Mechanical and Mechatronics Engineering, Federal University Otuoke, P.M.B. 126, Yenagoa, Bayelsa State, Nigeria

    Frank Efe Erukainure

  3. Department of Modern Mechanical Engineering, Waseda University, Tokyo, 169-8555, Japan

    Victor Parque

  4. Department of Materials Science and Engineering, Egypt-Japan University of Science and Technology, New Borg El-Arab City, 21934, Alexandria, Egypt

    Mohsen A. Hassan

Authors
  1. Frank Efe Erukainure
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  2. Victor Parque
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  4. Ahmed M. R. FathEl-Bab
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Corresponding author

Correspondence to Frank Efe Erukainure.

Additional information

Frank Efe Erukainure is a Postgraduate Research Student at the Department of Mechatronics and Robotics Engineering, Egypt-Japan University of Science and Technology, Alexandria, Egypt. Also, he is currently a Graduate Assistant Lecturer at Federal University Otuoke, Bayelsa State, Nigeria. His research interests include MEMS/NEMS, machine learning, mechatronics & robotic systems design, and artificial intelligence.

Victor Parque is an Associate Professor at the Department of Modern Mechanical Engineering, Waseda University, as well as a JSUC Visiting Professor at Egypt-Japan University of Science and Technology. He obtained the Ph.D. from the Graduate School of Information, Production and Systems, Waseda University, 2011. He was a post-doctoral fellow at the Department of Mechanical Engineering, Toyota Technological Institute in 2012–2014. His research interests span the principles of learning systems and artificial intelligence and its applications to design engineering, planning and control.

Mohsen A. Hassan is a Professor at the Department of Materials Science and Engineering, Egypt-Japan University of Science and Technology, Egypt. He received the Master’s degree in 1998 (Egypt), and the Ph.D. in Information and Production Science (Forming Technology) at Kyoto Institute of Technology, Japan. He has published more than 180 research articles in the field of material models, modelling and simulation, forming and micro forming, MEMS, piezoelectric thin films, heart mechanics, ceramics processing and rubbers.

Ahmed M. R. FathEl-Bab is a Professor at the Department of Mechatronics and Robotics Engineering, Egypt-Japan University of Science and Technology, Alexandria, Egypt. He received the M.Sc. and Ph.D. degrees from Assiut University, Egypt, in 2002 and 2008, respectively. From October 2006–October 2008, he was a visiting researcher at the Tabata Laboratory, Kyoto University, Japan. During this period, he gained practical experience in the microfabrication of MEMS/NEMS. His current interests include microsensors (principles, simulation, design, and fabrication), micromachining and its application in MEMS, tactile sensing systems (tactile sensing and display), micro energy harvesting devices, and micro fluidic systems.

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Erukainure, F.E., Parque, V., Hassan, M.A. et al. Design and experimental testing of a tactile sensor for self-compensation of contact error in soft tissue stiffness measurement. J Mech Sci Technol 36, 5309–5324 (2022). https://doi.org/10.1007/s12206-022-0943-7

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  • DOI: https://doi.org/10.1007/s12206-022-0943-7

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