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http://dx.doi.org/10.14695/KJSOS.2021.24.4.129

Evaluating Joint Motion Sensing Efficiency According to the Implementation Method of CNT-Based Fabric Sensors  

Cho, Hyun-Seung (연세대학교 생활과학대학 심바이오틱라이프텍연구원)
Yang, Jin-Hee (연세대학교 생활과학대학 심바이오틱라이프텍연구원)
Lee, Joo-Hyeon (연세대학교 생활과학대학 의류환경학과)
Publication Information
Science of Emotion and Sensibility / v.24, no.4, 2021 , pp. 129-138 More about this Journal
Abstract
This study aimed to determine the effects of the shape and attachment position of stretchable textile sensors coated with carbon nanotube on their performance when used to measure children's joint movements. Moreover, the child-safe requirements for fabric motion sensors are established. The child participants were advised to wear integrated clothing equipped with the sensors of various shapes (rectangular and boat-shaped) and attachment positions (at the knee and elbow joints or 4 cm below the joints). The voltage change induced by the elongation and contraction of the fabric sensors was determined for arm and leg flexion-extension motions at 60 deg/s (three measurements of 10 repeats each for 60°and 90°angles, for a total of 60 repetitions). Their dependability was determined by comparing the fabric motion sensors to the associated acceleration sensors. The experimental results indicate that the rectangular-shaped sensor affixed 4 cm below the joint is the most effective fabric motion sensor for measuring children's arm and leg motions. In this study, we designed a textile sensor capable of tracking children's joint motion and analyzed the sensor shape and attachment position on motion sensing clothing. We demonstrated that flexible fabric sensors integrated into garments may be used to detect the joint motions of the human body.
Keywords
Stretchable Fabric Sensor; Carbon Nano-Tube; Joint Motion Sensing; Garment Integrated Sensing;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 Totaro, M., Poliero, T., Mondini, A., Lucarotti, C., Cairoli, C., Ortiz, J., & Beccai, L. (2017). Soft smart garments for lower limb joint position analysis. Sensors, 17(10). DOI: 10.3390/s17102314   DOI
2 Adidas miCoach, Retrieved from http://www.adidas.com/kr/miCoach
3 Cho, G. S., Jeong., K. S., Paik, M. J., & Kwun, Y. E. (2011). Performance evaluation of textile-based electrodes and motion sensors for smart clothing. Sensors Journal IEEE, 11(12), 3183-3193. DOI: 10.1109/JSEN.2011.2167508   DOI
4 Cho, H. S., Park, S. H., Kang, D. H., Lee, K. H., Kang, S. J., Han, B. R., Oh, J. H., Lee, J. H., & Lee, J. W. (2015). Performance evaluation of fabric sensors for movement-monitoring smart clothing: Based on the experiment on a dummy. Science of Emotion & Sensibility, 18(4), 27-36. DOI: 10.14695/KJSOS.2015.18.4.25   DOI
5 Cho, H. S., Yang, J. H., Jeon, D. J., Lee, J. H. (2017). Effect of the shape and attached position of fabric sensors on the sensing performance of limb-motion sensing clothes. Science of Emotion & Sensibility, 20(3), 141-150. DOI: 10.14695/KJSOS.2017.20.3.141   DOI
6 Helmer, R. (2008). The wearable body-mapping sleeve, CSIRO science image. Retrieved from https://www.scienceimage.csiro.au/library/textile/i/7664/the-wearable-body-mapping-sleeve/
7 Dunne, L. (2010). Posture-monitoring vest, Retrieved from http://faculty.design.umn.edu/dunne/past_projects/
8 Hastings, C. (2019). Smart fabric can sense motion to help physical therapy patients to optimize recovery, Medgadget, Inc, APRIL 9TH. Retrieved from https://www.medgadget.com/2019/04/smartfabric-can-sense-motion-to-help-physical-therapy-patients-to-optimize-recovery.html
9 Daniel, R., Henk, L., & Per, S. (2013). Xsens MVN: Full 6DOF human motion tracking using miniature inertial sensors, XSENS TECHNOLOGIES - VERSION APRIL 3, 1-9.
10 Gioberto, G., & Dunne, L. (2014) Garment-integrated bend sensor. Electronics, 3, 564-581. DOI: 10.3390/ electronics3040564   DOI
11 Hofmann, C. (2012). Wearable sensors and wireless data transmission. Wearable Technologies Congress 2012, Munich.
12 Kang, D. H., Lee, Y. J., Lee, J. W., & Lee, J. H. (2011). A study on the sleeve-shaped platform of POF-based joint angle sensor for arm movement monitoring clothing. Science of Emotion & Sensibility, 14(2), 221-226.
13 Lorenzo, T. (2013). Wearable systems for movement recording in care support. Wearable Technologies Conference 2013, Munich.
14 Univ. of Harvard (2020), Arm muscle monitoring sensor, Retrieved from https://www.chosun.com/economy/science/2020/11/18/ILXXAOODRFBPDHZ4SQCFJJ3WJY/
15 Eskofier, B. (2013). Wearable computing systems for recreational and elite sports. Wearable Technologies Conference 2013, Munich.
16 Ding, Y., Kim, M., Kuindersma, S., & Walsh, C. J. (2018). Human-in-the-loop optimization of hip assistance with a soft exosuit during walking. Science Robotics, 3(15), eaar5438. 1-8. DOI: 10.1126/scirobotics.aar5438   DOI