Abstract
Field Programmable Gate Arrays (FPGAs) platform has been increasingly used in sensor-based applications because of reconfigurable and parallelisms features offered in the FPGA. However, most of the application designers are unfamiliar with hardware programming and design concepts of the FPGA. This paper presents an implementation of real-time sensor data acquisition (ReSDAq) for rowing monitoring system using LabVIEW FPGA which utilising the high-level synthesis (HLS) technique. The HLS allows application designers to use high-level language for configuring the FPGA. The ReSDAq application comprises of a tri-axis accelerometer sensor, an LCD monitor, and a National Instrument (NI) sbRIO-9632 board. The sbRIO-9632 board was targeted programmed on the Xilinx FPGA core to acquire sensor data and compute acceleration of the arm movement of the rower. From this study, it was found that the compilation time to convert G-code into hardware description language (HDL) code depends on the size of the code. Apart from having an interesting experience in graphical programming approach, the LabVIEW FPGA module could be used by application designers to facilitate and accelerate the development of FPGA-based systems.
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References
Sforza, C., Casiraghi, E., Lovecchio, N., Galante, D., Ferrario, V.F.: A three-dimensional study of body motion during Ergometer rowing. Open Sports Med. J. 1(6), 22–28 (2012)
Bernstein, I.A., Webber, O., Woledge, R.: An ergonomic comparison of rowing machine designs: possible implications for safety. Br. J. Sports Med. 36, 108–112 (2002)
Shi, G., He, Y., Ye, F., Yang, J., Wang, P., Jin, Y.: Towards an ubiquitous motion capture system using inertial MEMS sensors and ZigBee network. In: International Conference on Cyber Tech. in Automation, Control, and Intelligent System, pp. 230–234. IEEE, Kunming (2011)
Borghetti, M., Sardini, E., Serpelloni, M.: Evaluation of bend sensors for limb motion monitoring. In: International Symposium on Medical Measurements and Applications, pp. 1–5. IEEE, Lisboa (2014)
Byrd, G.: 21st Century Pong. Computer 48(10), 80–84 (2015)
Valeria, R., Stefan, L., Vesa, L., Yves, V., Walter, R., Laura, G.: Trunk kinematics during cross country Sit-skiing Ergometry: Skiing strategies associated to neuromusculoskeletal impairment. In: International Symposium on Medical Measurements and Applications (MeMeA), pp. 1–6. IEEE, Benevento (2016)
Taha, Z., Hassan, M.S.S., Yap, H.J., Yeo, W.K.: Preliminary investigation of an innovative digital motion analysis device for badminton athlete performance evaluation. In: 11th Conference of the International Sports English Association. Procedia Engineering 147, 461–465 (2016)
Chapter 3 Motion Capture. http://www.uio.no/imv/literature/knkap3–4
Zhu, R., Zhaoying, Z.: A real-time articulated human motion tracking using tri-axis inertial/magnetic sensors package. IEEE Trans. Neural Syst. Rehabil. Eng. 12(2), 295–302 (2004)
King, R.C., McIlwraith, D.G., Lo, B., Pansiot, J., McGregor, A.H., Yang, G.Z.: Body sensor networks for monitoring rowing technique. In: 2009 Proceedings on 6th International Workshop on Wearable and Implantable Body Sensor Networks, pp. 251–255. IEEE, Berkeley (2009)
Yurish, S.Y.: High Performance Digital Sensors Design: How to Make It Smarter, http://www.iaria.org/conferences2014/filesSENSORCOMM14/Yurish_Tutorial_2014.pdf
De La Piedra, A., Braeken, A., Touhafi, A.: Sensor systems based on FPGAs and their applications: a survey. Sensors 12(9), 12235–12264 (2012)
Minouni, E.H.E., Karim, M., Kouache, M.E., Amarouch, M.Y.: An FPGA-based system for real-time electrocardiographic detection of STEMI. In: 2nd International Conference on Advanced Technologies for Signal and Image Processing (ATSIP, pp. 830–835. IEEE, Monastir) (2016)
Oballe-Peinado, Ó., Vidal-Verdú, F., Sánchez-Durán, J.A., Castellanos-Ramos, J., Hidalgo-López, J.A.: Smart capture modules for direct sensor-to-FPGA interfaces. Sensors. 15(12), 31762–31780 (Dec 16, 2015)
GarcÃa, G.J., Jara, C.A., Pomares, J., Alabdo, A., Poggi, L.M., Torres, F.: A Survey on FPGA-based sensor systems: towards intelligent and reconfigurable low-power sensors for computer vision. Control Signal Process. Sensors 14, 6247–6278 (2014)
Ponce-Cruz, P., Molina, A., MacCleery, B.: LabVIEWTM FPGA. In: Fuzzy Logic Type 1 and Type 2 Based on LabVIEW™ FPGA. Series Studies in Fuzziness and Soft Computing. vol. 334, pp 71–138. Springer International Publishing, Switzerland (2016)
Andrade, H.A., Ahrends, S., Hogg, S.: Making FPGAs Accessible with LabVIEW. In: Koch, D., Hanning, F., Ziener, D. (eds.) FPGAs for Software Programmers, pp. 63–79. Springer International Publishing, Switzerland (2016)
Wang, G., Tran, T.N., Andrade, H.A.: A graphical programming and design environment for FPGA-based hardware. In: 2010 International Conference on Field Programmable Technology, pp. 337–340. IEEE, Beijing (2010)
Nane, R., Sima, V.M., Pilato, C., Choi, J., Fort, B., Canis, A., Chen, Y.T., Hsiao, H., Brown, S., Ferrandi, F., Anderson, J., Bertels, K.: A Survey and evaluation of FPGA high-level synthesis tools. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 35(10), 1591–1604 (2016)
Fuller, D.: The Future of FPGA Design Software, Jan. 24, 2013, http://www.ni.com/newsletter/51624/en/
Accelerometer ADXL335 Datasheet, 2009–2010 Analog Devices. https://www.sparkfun.com/datasheets/Components/SMD/adxl335.pdf
NI sbRIO-961x/963x/964x and NI sbRIO-9612XT/9632XT/9642XT National Instruments, http://www.ni.com/pdf/manuals/375052c.pdf
FPGA Module Help National Instruments, http://zone.ni.com/reference/en-XX/help/371599K-01/lvfpgsahelp/fpga_compile_window_reports/
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The authors would like to thank the Ministry of Higher Education, Malaysia and Universiti Tun Hussein Onn Malaysia (UTHM) for funding this study.
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Tukiran, Z., Ahmad, A. (2018). Exploiting LabVIEW FPGA in Implementation of Real-Time Sensor Data Acquisition for Rowing Monitoring System. In: Ghazali, R., Deris, M., Nawi, N., Abawajy, J. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2018. Advances in Intelligent Systems and Computing, vol 700. Springer, Cham. https://doi.org/10.1007/978-3-319-72550-5_27
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