“Payload estimation using forcemyography sensors for control of upper-body exoskeleton in load carrying assistance”
Authors: Muhammad R. U. Islam and Shaoping Bai,Affiliation: Aalborg University
Reference: 2019, Vol 40, No 4, pp. 189-198.
Keywords: Forcemyography, payload estimation, assistive exoskeleton, physical human-robot interaction
Abstract: In robotic assistive devices, the determination of required assistance is vital for proper functioning of assistive control. This paper presents a novel solution to measure conveniently and accurately carried payload in order to estimate the required assistance level. The payload is estimated using upper arm forcemyography (FMG) through a sensor band made of force sensitive resistors. The sensor band is worn on the upper arm and is able to measure the change of normal force applied due to muscle contraction. The readings of the sensor band are processed using support vector machine (SVM) regression technique to estimate the payload. The developed method was tested on human subjects, carrying a payload. Experiments were further conducted on an upper-body exoskeleton to provide the required assistance. The results show that the developed method is able to estimate the load carrying status, which can be used in exoskeleton control to provide effectively physical assistance needed.
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DOI: 10.4173/mic.2019.4.1DOI forward links to this article:
| [1] Muhammad Ahsan Gull, Shaoping Bai and Thomas Bak (2020), doi:10.3390/robotics9010016 |
| [2] Muhammad Raza Ul Islam, Asim Waris, Ernest Nlandu Kamavuako and Shaoping Bai (2020), doi:10.1177/2055668320938588 |
| [3] Muhammad Raza Ul Islam and Shaoping Bai (2020), doi:10.3389/frobt.2020.567491 |
| [4] Jasmine K. Proud, Daniel T. H. Lai, Kurt L. Mudie, Greg L. Carstairs, Daniel C. Billing, Alessandro Garofolini and Rezaul K. Begg (2020), doi:10.1177/0018720820957467 |
| [5] Shaoping Bai, Muhammad R. Islam, Karl Hansen, Jacob Norgaard, Chin-Yin Chen and Guilin Yang (2022), doi:10.1007/978-3-030-69547-7_49 |
| [6] Maria Lazzaroni, Ali Tabasi, Stefano Toxiri, Darwin G. Caldwell, Elena De Momi, Wietse van Dijk, Michiel P. de Looze, Idsart Kingma, Jaap H. van Dieen and Jesus Ortiz (2020), doi:10.1017/wtc.2020.8 |
| [7] Shaoping Bai, M.R. Islam, Valerie Power and Leonard O ullivan (2021), doi:10.1016/j.birob.2021.100032 |
| [8] Monica Tiboni, Alberto Borboni, Fabien Verite, Chiara Bregoli and Cinzia Amici (2022), doi:10.3390/s22030884 |
| [9] Xiaofeng Xiong, Cao Danh Do and Poramate Manoonpong (2022), doi:10.1109/TIE.2021.3116572 |
| [10] Stefano Massardi, David Rodriguez-Cianca, David Pinto-Fernandez, Juan C. Moreno, Matteo Lancini and Diego Torricelli (2022), doi:10.3390/s22113993 |
| [11] Robin Otterbein, Elizabeth Jochum, Daniel Overholt, Shaoping Bai and Alex Dalsgaard (2022), doi:10.1145/3537972.3537984 |
| [12] Pengpeng Xu, Dan Xia, Juncheng Li, Jiaming Zhou and Longhan Xie (2022), doi:10.1007/s11370-022-00435-5 |
| [13] Marek Sierotowicz, Donato Brusamento, Benjamin Schirrmeister, Mathilde Connan, Jonas Bornmann, Jose Gonzalez-Vargas and Claudio Castellini (2022), doi:10.3389/frobt.2022.919370 |
| [14] Muhammad Raza Ul Islam and Shaoping Bai (2022), doi:10.1016/j.bea.2022.100062 |
| [15] Abdullah Tahir, Shaoping Bai and Ming Shen (2023), doi:10.3390/s23104863 |
| [16] Emir Mobedi, Sebastian Hjorth, Wansoo Kim, Elena De Momi, Nikos G. Tsagarakis and Arash Ajoudani (2023), doi:10.1109/LRA.2023.3282385 |
| [17] Abdullah Tahir, Zeliang An, Shaoping Bai and Ming Shen (2023), doi:10.1109/TCSII.2023.3266827 |
| [18] Xianhe Wang, Haotian Zhang, Long Teng and Chak Yin Tang (2023), doi:10.1016/j.jfranklin.2023.08.046 |
| [19] S. Perera, K. N. D. Widanage, I. D. Wijegunawardana, R. K. P. S. Ranaweera and R. A. R. C. Gopura (2023), doi:10.1109/ACCESS.2023.3323249 |
| [20] Huibin Qin, Weijie Duan, Xiling Shi, Zefeng Zhang and Muddaser Abbas (2024), doi:10.1109/WRRC62201.2024.10696346 |
| [21] Junyi Shen, Swaninda Ghosh, Tetsuro Miyazaki and Kenji Kawashima (2024), doi:10.1109/BioRob60516.2024.10719718 |
| [22] Junyi Shen, Tetsuro Miyazaki, Swaninda Ghosh, Toshihiro Kawase and Kenji Kawashima (2024), doi:10.1002/aisy.202400278 |
[1] Abdallah, I.B., Bouteraa, Y., and Rekik, C. (2017). Abdallah, I, B., Bouteraa, Y., and Rekik, C. Design and development of 3D printed myoelectric robotic exoskeleton for hand rehabilitation. International Journal on Smart Sensing & Intelligent Systems, 2017. 10(2). doi:10.21307/ijssis-2017-215
[2] Bai, S., Christensen, S., and Islam, M. R.U. (2017). Bai, S, , Christensen, S., and Islam, M. R.U. An upper-body exoskeleton with a novel shoulder mechanism for assistive applications. In 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM). pages 1041--1046. doi:10.1109/AIM.2017.8014156
[3] Bai, S., Virk, G.S., and Sugar, T. (2018). Bai, S, , Virk, G.S., and Sugar, T. Wearable Exoskeleton Systems: Design, Control and Applications. Institution of Engineering and Technology. doi:10.1049/PBCE108E
[4] Castro, M.N., Rasmussen, J., Andersen, M.S., and Bai, S. (2019). Castro, M, N., Rasmussen, J., Andersen, M.S., and Bai, S. A compact 3-DOF shoulder mechanism constructed with scissors linkages for exoskeleton applications. Mechanism and Machine Theory. 132:264--278. doi:10.1016/j.mechmachtheory.2018.11.007
[5] Cho, E., Chen, R., Merhi, L.-K., Xiao, Z., Pousett, B., and Menon, C. (2016). Cho, E, , Chen, R., Merhi, L.-K., Xiao, Z., Pousett, B., and Menon, C. Force myography to control robotic upper extremity prostheses: a feasibility study. Frontiers in Bioengineering and Biotechnology. 4:18. doi:10.3389/fbioe.2016.00018
[6] Christensen, S. and Bai, S. (2018). Christensen, S, and Bai, S. Kinematic analysis and design of a novel shoulder exoskeleton using a double parallelogram linkage. Journal of Mechanisms and Robotics. 10(4):041008. doi:10.1115/1.4040132
[7] Cui, X., Chen, W., Jin, X., and Agrawal, S.K. (2016). Cui, X, , Chen, W., Jin, X., and Agrawal, S.K. Design of a 7-DOF cable-driven arm exoskeleton (CAREX-7) and a controller for dexterous motion training or assistance. IEEE/ASME Transactions on Mechatronics. 22(1):161--172. doi:10.1109/TMECH.2016.2618888
[8] Fan, Y. and Yin, Y. (2013). Fan, Y, and Yin, Y. Active and progressive exoskeleton rehabilitation using multisource information fusion from EMG and force-position epp. IEEE Transactions on Biomedical Engineering. 60(12):3314--3321. doi:10.1109/TBME.2013.2267741
[9] Gunasekara, J., Gopura, R., Jayawardane, T., and Lalitharathne, S. (2012). Gunasekara, J, , Gopura, R., Jayawardane, T., and Lalitharathne, S. Control methodologies for upper limb exoskeleton robots. In 2012 IEEE/SICE International Symposium on System Integration (SII). pages 19--24. doi:10.1109/SII.2012.6427387
[10] Hsieh, H.-C., Chen, D.-F., Chien, L., and Lan, C.-C. (2017). Hsieh, H, -C., Chen, D.-F., Chien, L., and Lan, C.-C. Design of a parallel actuated exoskeleton for adaptive and safe robotic shoulder rehabilitation. IEEE/ASME Transactions on Mechatronics. 22(5):2034--2045. doi:10.1109/TMECH.2017.2717874
[11] Huang, J., Huo, W., Xu, W., Mohammed, S., and Amirat, Y. (2015). Huang, J, , Huo, W., Xu, W., Mohammed, S., and Amirat, Y. Control of upper-limb power-assist exoskeleton using a human-robot interface based on motion intention recognition. IEEE Transactions on Automation Science and Engineering. 12(4):1257--1270. doi:10.1109/TASE.2015.2466634
[12] Islam, M.R., Xu, K., and Bai, S. (2018). Islam, M, R., Xu, K., and Bai, S. Position sensing and control with FMG sensors for exoskeleton physical assistance. In International Symposium on Wearable Robotics. pages 3--7, 2018. doi:10.1007/978-3-030-01887-0_1
[13] Islam, M. R.U. and Bai, S. (2017). Islam, M, R.U. and Bai, S. Intention detection for dexterous human arm motion with FSR sensor bands. In Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction. pages 139--140. doi:10.1145/3029798.3038377
[14] Jiang, X., Chu, H.T., Xiao, Z.G., Merhi, L.-K., and Menon, C. (2016). Jiang, X, , Chu, H.T., Xiao, Z.G., Merhi, L.-K., and Menon, C. Ankle positions classification using force myography: An exploratory investigation. In 2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT). pages 29--32. doi:10.1109/HIC.2016.7797689
[15] Kadkhodayan, A., Jiang, X., and Menon, C. (2016). Kadkhodayan, A, , Jiang, X., and Menon, C. Continuous prediction of finger movements using force myography. Journal of Medical and Biological Engineering. 36(4):594--604. doi:10.1007/s40846-016-0151-y
[16] Keller, U., van Hedel, H.J., Klamroth-Marganska, V., and Riener, R. (2016). Keller, U, , van Hedel, H.J., Klamroth-Marganska, V., and Riener, R. ChARMin:The first actuated exoskeleton robot for pediatric arm rehabilitation. IEEE/ASME Transactions on Mechatronics. 21(5):2201--2213. doi:10.1109/TMECH.2016.2559799
[17] Kiguchi, K. and Hayashi, Y. (2012). Kiguchi, K, and Hayashi, Y. An EMG-based control for an upper-limb power-assist exoskeleton robot. IEEE Transactions on Systems, Man, and Cybernetics. 42(4):1064--1071. doi:10.1109/TSMCB.2012.2185843
[18] Lee, H.-D., Lee, B.-K., Kim, W.-S., Han, J.-S., Shin, K.-S., and Han, C.-S. (2014). Lee, H, -D., Lee, B.-K., Kim, W.-S., Han, J.-S., Shin, K.-S., and Han, C.-S. Human--robot cooperation control based on a dynamic model of an upper limb exoskeleton for human power amplification. Mechatronics. 24(2):168--176. doi:10.1016/j.mechatronics.2014.01.007
[19] Leonardis, D., Barsotti, M., Loconsole, C., Solazzi, M., Troncossi, M., Mazzotti, C., Castelli, V.P., Procopio, C., Lamola, G., Chisari, C., etal. (2015). Leonardis, D, , Barsotti, M., Loconsole, C., Solazzi, M., Troncossi, M., Mazzotti, C., Castelli, V.P., Procopio, C., Lamola, G., Chisari, C., etal. An EMG-controlled robotic hand exoskeleton for bilateral rehabilitation. IEEE Transactions on Haptics. 8(2):140--151. doi:10.1109/TOH.2015.2417570
[20] Li, Z., Wang, B., Sun, F., Yang, C., Xie, Q., and Zhang, W. (2013). Li, Z, , Wang, B., Sun, F., Yang, C., Xie, Q., and Zhang, W. sEMG-based joint force control for an upper-limb power-assist exoskeleton robot. IEEE Journal of Biomedical and Health Informatics. 18(3):1043--1050. doi:10.1109/JBHI.2013.2286455
[21] Mangukiya, Y., Purohit, B., and George, K. (2017). Mangukiya, Y, , Purohit, B., and George, K. Electromyography EMG sensor controlled assistive orthotic robotic arm for forearm movement. In 2017 IEEE Sensors Applications Symposium (SAS). pages 1--4, 2017. doi:10.1109/SAS.2017.7894065
[22] McDonald, C.G., Dennis, T.A., and O'Malley, M.K. (2017). McDonald, C, G., Dennis, T.A., and O'Malley, M.K. Characterization of surface electromyography patterns of healthy and incomplete spinal cord injury subjects interacting with an upper-extremity exoskeleton. In 2017 International Conference on Rehabilitation Robotics (ICORR). pages 164--169. doi:10.1109/ICORR.2017.8009240
[23] Mghames, S., Laghi, M., DellaSantina, C., Garabini, M., Catalano, M., Grioli, G., and Bicchi, A. (2017). Mghames, S, , Laghi, M., DellaSantina, C., Garabini, M., Catalano, M., Grioli, G., and Bicchi, A. Design, control and validation of the variable stiffness exoskeleton FLEXO. In 2017 International Conference on Rehabilitation Robotics (ICORR). pages 539--546. doi:10.1109/ICORR.2017.8009304
[24] Rahman, M.H., Ochoa-Luna, C., Saad, M., and Archambault, P. (2015). Rahman, M, H., Ochoa-Luna, C., Saad, M., and Archambault, P. EMG based control of a robotic exoskeleton for shoulder and elbow motion assist. Journal of Automation and Control Engineering. 3(4). doi:10.12720/joace.3.4.270-276
[25] Rosen, J., Brand, M., Fuchs, M.B., and Arcan, M. (2001). Rosen, J, , Brand, M., Fuchs, M.B., and Arcan, M. A myosignal-based powered exoskeleton system. IEEE Transactions on Systems, Man, and Cybernetics-part A: Systems and humans. 31(3):210--222. doi:10.1109/3468.925661
[26] Sadarangani, G.P. and Menon, C. (2017). Sadarangani, G, P. and Menon, C. A preliminary investigation on the utility of temporal features of force myography in the two-class problem of grasp vs. no-grasp in the presence of upper-extremity movements. Biomedical Engineering online. 16(1):59. doi:10.1186/s12938-017-0349-4
[27] Tang, Z., Zhang, K., Sun, S., Gao, Z., Zhang, L., and Yang, Z. (2014). Tang, Z, , Zhang, K., Sun, S., Gao, Z., Zhang, L., and Yang, Z. An upper-limb power-assist exoskeleton using proportional myoelectric control. Sensors. 14(4):6677--6694. doi:10.3390/s140406677
[28] Xiao, Z.G., Elnady, A.M., and Menon, C. (2014). Xiao, Z, G., Elnady, A.M., and Menon, C. Control an exoskeleton for forearm rotation using FMG. In 5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics. pages 591--596. doi:10.1109/BIOROB.2014.6913842
[29] Xiao, Z.G. and Menon, C. (2017). Xiao, Z, G. and Menon, C. Counting grasping action using force myography: an exploratory study with healthy individuals. JMIR Rehabilitation and Assistive technologies. 4(1):e5. doi:10.2196/rehab.6901
[30] Zhou, L., Bai, S., Andersen, M.S., and Rasmussen, J. (2015). Zhou, L, , Bai, S., Andersen, M.S., and Rasmussen, J. Modeling and design of a spring-loaded, cable-driven, wearable exoskeleton for the upper extremity. Modeling, Identification and Control. 36(3):167--177. doi:10.4173/mic.2015.3.4
BibTeX:
@article{MIC-2019-4-1,
title={{Payload estimation using forcemyography sensors for control of upper-body exoskeleton in load carrying assistance}},
author={Islam, Muhammad R. U. and Bai, Shaoping},
journal={Modeling, Identification and Control},
volume={40},
number={4},
pages={189--198},
year={2019},
doi={10.4173/mic.2019.4.1},
publisher={Norwegian Society of Automatic Control}
};