publication . Preprint . 2021

Surface Electromyography as a Natural Human-Machine Interface: A Review

Zheng, Mingde; Crouch, Michael S.; Eggleston, Michael S.;
Open Access English
  • Published: 12 Jan 2021
Abstract
Surface electromyography (sEMG) is a non-invasive method of measuring neuromuscular potentials generated when the brain instructs the body to perform both fine and coarse locomotion. This technique has seen extensive investigation over the last two decades, with significant advances in both the hardware and signal processing methods used to collect and analyze sEMG signals. While early work focused mainly on medical applications, there has been growing interest in utilizing sEMG as a sensing modality to enable next-generation, high-bandwidth, and natural human-machine interfaces. In the first part of this review, we briefly overview the human skeletomuscular phy...
Subjects
free text keywords: Computer Science - Human-Computer Interaction, Physics - Biological Physics
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154 references, page 1 of 11

P. Papcun, E. Kajáti, and J. Koziorek, “Human machine interface in concept of industry 4.0,” in DISA 2018 - IEEE World Symposium on Digital Intelligence for Systems and Machines, Proceedings, Aug. 2018, pp. 289- 296, doi: 10.1109/DISA.2018.8490603. [OpenAIRE]

34, no. 16, pp. 1-9, Sep. 2001, doi: 10.1016/S1474-6670(17)41493-5.

K. Wucherer, “HMI, The Window to the Manufacturing and Process Industry,” IFAC Proc. Vol., vol. 34, no. 16, pp. 101-108, Sep. 2001, doi: 10.1016/S1474-6670(17)41508-4.

V. Villani, L. Sabattini, J. N. Czerniaki, A. Mertens, B. Vogel-Heuser, and C. Fantuzzi, “Towards modern inclusive factories: A methodology for the development of smart adaptive human-machine interfaces,” in 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Sep.

2017, pp. 1-7, doi: 10.1109/ETFA.2017.8247634.

[6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] H. Viswanathan and P. E. Mogensen, “Communications in the 6G Era,” IEEE Access, vol. 8, pp. 57063-57074, 2020, doi: 10.1109/ACCESS.2020.2981745.

E. Palermo, J. Laut, O. Nov, P. Cappa, and M. Porfiri, “A natural user interface to integrate citizen science and physical exercise,” PLoS One, vol. 12, no. 2, p. e0172587, Feb. 2017, doi: 10.1371/journal.pone.0172587.

44, no. 9, p. 144, Sep. 2020, doi: 10.1007/s10916-020-01602-w.

R. A. Suarez Fernandez, J. L. Sanchez-Lopez, C. Sampedro, H. Bavle, M. Molina, and P. Campoy, “Natural user interfaces for human-drone multi-modal interaction,” in 2016 International Conference on Unmanned Aircraft Systems (ICUAS), Jun. 2016, pp. 1013-1022, doi: 10.1109/ICUAS.2016.7502665.

J. Grubb and J. Cohn, “The Evolution of Human Systems: A Brief Overview,” Springer, Berlin, Heidelberg, 2011, pp. 60-66.

N. O-larnnithipong, A. Barreto, S. Tangnimitchok, and N. Ratchatanantakit, “Orientation correction for a 3D hand motion tracking interface using inertial measurement units,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Jul. 2018, vol.

10903 LNCS, pp. 321-333, doi: 10.1007/978-3-319-91250-9_25.

B. Schabron, A. Reust, J. Desai, and Y. Yihun, “Integration of Forearm sEMG Signals with IMU Sensors for Trajectory Planning and Control of Assistive Robotic Arm,” in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Jul. 2019, pp. 5274-5277, doi: 10.1109/EMBC.2019.8856699. [OpenAIRE]

C. J. Wu, K. H. Lin, M. L. Hsieh, and J.-Y. Y. Chang, “Realization of natural user interface for computer control with KNN classifier enhanced smart glove,” in ASME 2019 28th Conference on Information Storage and Processing Systems, ISPS 2019, Jun. 2019, doi: 10.1115/ISPS2019-7493.

L. Almeida et al., “Towards natural interaction in immersive reality with a cyber-glove,” in Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, Oct. 2019, vol. 2019-Octob, pp. 2653-2658, doi: 10.1109/SMC.2019.8914239.

154 references, page 1 of 11
Abstract
Surface electromyography (sEMG) is a non-invasive method of measuring neuromuscular potentials generated when the brain instructs the body to perform both fine and coarse locomotion. This technique has seen extensive investigation over the last two decades, with significant advances in both the hardware and signal processing methods used to collect and analyze sEMG signals. While early work focused mainly on medical applications, there has been growing interest in utilizing sEMG as a sensing modality to enable next-generation, high-bandwidth, and natural human-machine interfaces. In the first part of this review, we briefly overview the human skeletomuscular phy...
Subjects
free text keywords: Computer Science - Human-Computer Interaction, Physics - Biological Physics
Download from
154 references, page 1 of 11

P. Papcun, E. Kajáti, and J. Koziorek, “Human machine interface in concept of industry 4.0,” in DISA 2018 - IEEE World Symposium on Digital Intelligence for Systems and Machines, Proceedings, Aug. 2018, pp. 289- 296, doi: 10.1109/DISA.2018.8490603. [OpenAIRE]

34, no. 16, pp. 1-9, Sep. 2001, doi: 10.1016/S1474-6670(17)41493-5.

K. Wucherer, “HMI, The Window to the Manufacturing and Process Industry,” IFAC Proc. Vol., vol. 34, no. 16, pp. 101-108, Sep. 2001, doi: 10.1016/S1474-6670(17)41508-4.

V. Villani, L. Sabattini, J. N. Czerniaki, A. Mertens, B. Vogel-Heuser, and C. Fantuzzi, “Towards modern inclusive factories: A methodology for the development of smart adaptive human-machine interfaces,” in 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Sep.

2017, pp. 1-7, doi: 10.1109/ETFA.2017.8247634.

[6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] H. Viswanathan and P. E. Mogensen, “Communications in the 6G Era,” IEEE Access, vol. 8, pp. 57063-57074, 2020, doi: 10.1109/ACCESS.2020.2981745.

E. Palermo, J. Laut, O. Nov, P. Cappa, and M. Porfiri, “A natural user interface to integrate citizen science and physical exercise,” PLoS One, vol. 12, no. 2, p. e0172587, Feb. 2017, doi: 10.1371/journal.pone.0172587.

44, no. 9, p. 144, Sep. 2020, doi: 10.1007/s10916-020-01602-w.

R. A. Suarez Fernandez, J. L. Sanchez-Lopez, C. Sampedro, H. Bavle, M. Molina, and P. Campoy, “Natural user interfaces for human-drone multi-modal interaction,” in 2016 International Conference on Unmanned Aircraft Systems (ICUAS), Jun. 2016, pp. 1013-1022, doi: 10.1109/ICUAS.2016.7502665.

J. Grubb and J. Cohn, “The Evolution of Human Systems: A Brief Overview,” Springer, Berlin, Heidelberg, 2011, pp. 60-66.

N. O-larnnithipong, A. Barreto, S. Tangnimitchok, and N. Ratchatanantakit, “Orientation correction for a 3D hand motion tracking interface using inertial measurement units,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Jul. 2018, vol.

10903 LNCS, pp. 321-333, doi: 10.1007/978-3-319-91250-9_25.

B. Schabron, A. Reust, J. Desai, and Y. Yihun, “Integration of Forearm sEMG Signals with IMU Sensors for Trajectory Planning and Control of Assistive Robotic Arm,” in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Jul. 2019, pp. 5274-5277, doi: 10.1109/EMBC.2019.8856699. [OpenAIRE]

C. J. Wu, K. H. Lin, M. L. Hsieh, and J.-Y. Y. Chang, “Realization of natural user interface for computer control with KNN classifier enhanced smart glove,” in ASME 2019 28th Conference on Information Storage and Processing Systems, ISPS 2019, Jun. 2019, doi: 10.1115/ISPS2019-7493.

L. Almeida et al., “Towards natural interaction in immersive reality with a cyber-glove,” in Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, Oct. 2019, vol. 2019-Octob, pp. 2653-2658, doi: 10.1109/SMC.2019.8914239.

154 references, page 1 of 11
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