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Tytuł artykułu

A Fabric-Based Integrated Sensor Glove System Recognizing Hand Gesture

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The research on wearable glove sensor system has been increasing over recent years because of the need for portability and comfort. This study presents a fabric-based integrated sensor glove system with five sensing zones. Five sensors are knitted by silver-plated nylon yarn and embedded into glove directly using intarsia technology. Various parameters including sensor elasticity, sizes of embedded sensor as well as glove are discussed, respectively. Further, selected or chosen integrated sensor glove is manufactured and tested for recognizing gestures. Results show that elasticity affects effective sensing range of knitted sensors, size has significant influence on sensors’ sensitivity, and appropriate glove size helps avoiding nonlinear sensing phenomenon. Finally, the glove system, by extracting feature data, can distinguish Chinese number gestures very well and has also the potential to recognize more hand gestures in the future.
Rocznik
Strony
458--465
Opis fizyczny
Bibliogr. 21 poz.
Twórcy
autor
  • Jiangnan University, Lihu Road, 1800 Binhu District, Wuxi, Jiangsu 214122, China
autor
  • Jiangnan University, Lihu Road, 1800 Binhu District, Wuxi, Jiangsu 214122, China
autor
  • Jiangnan University, Lihu Road, 1800 Binhu District, Wuxi, Jiangsu 214122, China
autor
  • Jiangnan University, Lihu Road, 1800 Binhu District, Wuxi, Jiangsu 214122, China
autor
  • Jiangnan University, Lihu Road, 1800 Binhu District, Wuxi, Jiangsu 214122, China
Bibliografia
  • [1] Chalechale, A., Naghdy, G. (2007). Visual-based human-machine interface using hand gestures. In: 9th International Symposium on Signal Processing and Its Applications. IEEE, pp. 1-4.
  • [2] Guo, Z. (2011). Research of hand positioning and gesture recognition based on binocular vision. In: IEEE International Symposium on VR Innovation. IEEE, pp. 311-315.
  • [3] Park, Y., Bae, J. (2020). A three-dimensional fi nger motion measurement system of a thumb and an index finger without a calibration process. Sensors, 20(3), 756.
  • [4] Fahn, C. S., Sun, H. (2005). Development of a data glove with reducing sensors based on magnetic induction. IEEE Transactions on Industrial Electronics, 52(2), 585-594.
  • [5] Chen, W., Yu, C., Tu, C., Lyu, Z., Tang, J., et al. (2020). A survey on hand pose estimation with wearable sensors and computer-vision-based methods. Sensors, 20(4), 1074.
  • [6] Shen, Z., Yi, J., Li, X., Mark, L. H. P., Hu, Y., et al. (2016). A soft stretchable bending sensor and data glove applications. Robotics and Biomimetics, 3(1), 22.
  • [7] Borghetti, M., Sardini, E., Serpelloni, M. (2013). Sensorized glove for measuring hand finger flexion for rehabilitation purposes. IEEE Transactions on Instrumentation and Measurement, 62(12), 3308-3314.
  • [8] da Silva, A. F., Gonçalves, A. F., Mendes, P. M., Correia, J. H. (2011). FBG sensing glove for monitoring hand posture. IEEE Sensors Journal, 11(10), 2442-2448.
  • [9] Nishiyama, M, Watanabe K. (2009). Wearable sensing glove with embed hetero-core fiber-optic nerves for unconstrained hand motion capture. IEEE Transactions on Instrumentation and Measurement, 58(12), 3995-4000.
  • [10] Fujiwara, E., dos Santos, M. F. M., Suzuki, C. K. (2014). Flexible optical fiber bending transducer for application in glove-based sensors. IEEE Sensors Journal, 14(10), 3631-3636.
  • [11] Amjadi, M., Pichitpajongkit, A., Lee, S., Ryu, S., Park, I. (2014). Highly stretchable and sensitive strain sensor based on silver nanowire–elastomer nanocomposite. ACS Nano, 8(5), 5154-5163.
  • [12] Cai, G., Yang, M., Xu, Z., Liu, J., Tang, B., et al. (2017). Flexible and wearable strain sensing fabrics. Chemical Engineering Journal, 325, 396-403.
  • [13] Lu, S., Wang, S., Wang, G., Ma, J., Wang, X., et al. (2019). Wearable graphene film strain sensors encapsulated with nylon fabric for human motion monitoring. Sensors and Actuators A: Physical, 295, 200-209.
  • [14] Tadesse, M. G., Mengistie, D. A., Chen, Y, Wang, L., Loghin, C., et al. (2019). Electrically conductive highly elastic polyamide/lycra fabric treated with PEDOT:PSS and polyurethane. Journal of Materials Science, 54, 9591–9602.
  • [15] Li, Y., Miao, X., Niu, L., Gian, G., Pibo, M. (2020). Human motion recognition of knitted flexible sensor in walking cycle. Sensors, 20(1), 35.
  • [16] Mattmann, C., Clemens, F., Tröster, G. (2008). Sensor for measuring strain in textile. Sensors, 8(6), 3719-3732.
  • [17] Raji, R. K., Miao, X., Wan, A., Niu, L., Li, Y., et al. (2019). Knitted piezoresistive smart chest band and its application for respiration patterns assessment. Journal of Engineered Fibers and Fabrics, 14, 1558925019868474.
  • [18] Han, X., Miao, X., Chen, X., Jiang, G., Niu, L. (2019). Research on finger movement sensing performance of conductive gloves. Journal of Engineered Fibers and Fabrics, 14(17), 155892501988762.
  • [19] Han, X., Miao, X. (2019). Longitudinal electrical physical properties of spandex weft-knitted conductive fabric. Journal of Textile Research, 40(4), 66-71. (Chinese with English abstract)
  • [20] Seyedin, S., Razal, J., Innis, P. C., Jeiranikhameneh, A., Beirne, S., et al. (2015). Knitted strain sensor textiles of highly conductive all polymeric fibers. ACS Applied Materials & Interfaces, 7, 21150-21158.
  • [21] Pacelli, M., Loriga, G., Paradiso, R. (2007). Flat knitted sensors for respiration monitoring. In: IEEE International Symposium on Industrial Electronics. IEEE, pp. 2838-2841.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-30cd55cb-4359-4dd0-a515-15477b13073d
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