[1]
A. Saudabayev and H. A. Varol, Sensors for robotic hands: A survey of state of the art,, IEEE Access, vol. 3, p.1765–1782, (2015).
DOI: 10.1109/access.2015.2482543
Google Scholar
[2]
P. Geethanjali, Myoelectric control of prosthetic hands: state-of-the-art review,, Med. Devices Evid. Res., vol. Volume 9, p.247–255, Jul. (2016).
DOI: 10.2147/mder.s91102
Google Scholar
[3]
C. J. De Luca, The Use of Surface Electromyography in Biomechanics,, J. Appl. Biomech., vol. 13, no. 2, p.135–163, May (1997).
Google Scholar
[4]
F. Gaetani, P. Primiceri, G. A. Zappatore, and P. Visconti, Hardware design and software development of a motion control and driving system for transradial prosthesis based on a wireless myoelectric armband,, IET Sci. Meas. Technol., vol. 13, no. 3, p.354–362, (2019).
DOI: 10.1049/iet-smt.2018.5108
Google Scholar
[5]
A. Akhtar et al., A low-cost, open-source, compliant hand for enabling sensorimotor control for people with transradial amputations,, in 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2016, p.4642–4645.
DOI: 10.1109/embc.2016.7591762
Google Scholar
[6]
J. Segil, R. Patel, J. Klingner, R. F. ff Weir, and N. Correll, Multi-modal prosthetic fingertip sensor with proximity, contact, and force localization capabilities,, Adv. Mech. Eng., vol. 11, no. 4, p.1–9, (2019).
DOI: 10.1177/1687814019844643
Google Scholar
[7]
D. Pamungkas and K. Ward, Electro-tactile feedback system for a prosthetic hand,, 22nd Annu. Int. Conf. Mechatronics Mach. Vis. Pract. M2VIP 2015, p.27–38, (2015).
Google Scholar
[8]
L. M. R. Romero, XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013: MEDICON 2013, 25-28 September 2013, Seville, Spain,, IFMBE Proc., vol. 41, p.1, (2014).
DOI: 10.1007/978-3-319-00846-2
Google Scholar
[9]
M. S. Bahari, A. Jaffar, C. Y. Low, R. Jaafar, K. Roese, and H. Yussof, Design and Development of a Multifingered Prosthetic Hand,, Int. J. Soc. Robot., vol. 4, no. S1, p.59–66, Nov. (2012).
DOI: 10.1007/s12369-011-0133-8
Google Scholar
[10]
D. A. Bennett, S. Member, and M. Goldfarb, IMU-Based Wrist Rotation Control of a Transradial Myoelectric Prosthesis,, vol. 4320, no. c, (2017).
DOI: 10.1109/tnsre.2017.2682642
Google Scholar
[11]
C. Calderon-cordova, C. Ramírez, V. Barros, P. A. Quezada-sarmiento, and L. Barba-, EMG Signal Patterns Recognition based on Feedforward Artificial Neural Network Applied to Robotic Prosthesis Myoelectric Control,, in FTC 2016 - Future Technologies Conference 2016, 2016, no. December, p.868–875.
DOI: 10.1109/ftc.2016.7821705
Google Scholar
[12]
W. T. Shi, Z. J. Lyu, S. T. Tang, T. L. Chia, and C. Y. Yang, A bionic hand controlled by hand gesture recognition based on surface EMG signals: A preliminary study,, Biocybern. Biomed. Eng., vol. 38, no. 1, p.126–135, (2018).
DOI: 10.1016/j.bbe.2017.11.001
Google Scholar
[13]
P. Geethanjali and K. K. Ray, A Low-Cost Real-Time Research Platform for EMG Pattern Recognition-Based Prosthetic Hand,, IEEE/ASME Trans. Mechatronics, vol. 20, no. 4, p.1948–1955, Aug. (2015).
DOI: 10.1109/tmech.2014.2360119
Google Scholar
[14]
M. Tavakoli, C. Benussi, and J. L. Lourenco, Single channel surface EMG control of advanced prosthetic hands: A simple, low cost and efficient approach,, Expert Syst. Appl., vol. 79, p.322–332, Aug. (2017).
DOI: 10.1016/j.eswa.2017.03.012
Google Scholar
[15]
T. Triwiyanto, I. P. A. Pawana, T. Hamzah, and S. Luthfiyah, Low-Cost and Open-Source Anthropomorphic Prosthetics Hand Using Linear Actuators,, Telkomnika (Telecommunication Comput. Electron. Control., vol. 18, no. 2, p.281–288, (2020).
DOI: 10.12928/telkomnika.v18i2.14799
Google Scholar
[16]
D. T. G. D. A. A. R. Neto, Human Prosthetic Interaction Integration Of Several Techniques,, in XIII Simposio Brasileiro de Automacao Inteligente, 2017, p.200.
Google Scholar
[17]
M. A. Oskoei and H. Hu, Myoelectric control systems — A survey Author ' s personal copy,, vol. 2, p.275–294, (2007).
Google Scholar
[18]
T. Triwiyanto, I. P. A. Pawana, T. Hamzah, and S. Luthfiyah, Low-cost and open-source anthropomorphic prosthetics hand using linear actuators,, Telkomnika (Telecommunication Comput. Electron. Control., vol. 18, no. 2, p.953–960, (2020).
DOI: 10.12928/telkomnika.v18i2.14799
Google Scholar
[19]
Triwiyanto, T. Hamzah, S. Luthfiyah, I. P. A. Pawana, and B. Utomo, A low cost and open-source anthropomorphic prosthetics hand for transradial amputee,, AIP Conf. Proc., vol. 2202, (2019).
DOI: 10.1063/1.5141699
Google Scholar
[20]
Triwiyanto, O. Wahyunggoro, H. A. Nugroho, and Herianto, An investigation into time domain features of surface electromyography to estimate the elbow joint angle,, Adv. Electr. Electron. Eng., vol. 15, no. 3, p.448–458, (2017).
DOI: 10.15598/aeee.v15i3.2177
Google Scholar
[21]
D. Brunelli, A. M. Tadesse, B. Vodermayer, M. Nowak, and C. Castellini, Low-cost wearable multichannel surface EMG acquisition for prosthetic hand control,, Proc. - 2015 6th IEEE Int. Work. Adv. Sensors Interfaces, IWASI 2015, p.94–99, (2015).
DOI: 10.1109/iwasi.2015.7184964
Google Scholar
[22]
T. Triwiyanto, I. P. A. Pawana, B. G. Irianto, T. B. Indrato, and I. D. G. H. Wisana, Embedded system for upper-limb exoskeleton based on electromyography control,, Telkomnika (Telecommunication Comput. Electron. Control., vol. 17, no. 6, p.2992–3002, (2019).
DOI: 10.12928/telkomnika.v17i6.11670
Google Scholar
[23]
D. Brunellli, S. Member, E. Farella, D. Giovanelli, B. Milosevic, and I. Minakov, Design Considerations for Wireless Acquisition of Multichannel sEMG Signals in Prosthetic Hand Control,, IEEE Sens. J., no. c, p.1–10, (2016).
DOI: 10.1109/jsen.2016.2596712
Google Scholar
[24]
N. E. Krausz, R. A. L. Rorrer, and R. F. F. Weir, Design and Fabrication of a Six Degree-of-Freedom Open Source Hand,, IEEE Trans. Neural Syst. Rehabil. Eng., vol. 24, no. 5, p.562–572, (2016).
DOI: 10.1109/tnsre.2015.2440177
Google Scholar
[25]
A. L. Fougner, Ø. Stavdahl, and P. J. Kyberd, System training and assessment in simultaneous proportional myoelectric prosthesis control,, J. Neuroeng. Rehabil., p.1–13, (2014).
DOI: 10.1186/1743-0003-11-75
Google Scholar
[26]
C. Fleischer and A. Wege, Application of EMG signals for controlling exoskeleton robots EMG is better than force sensor,, p.314–319, (2006).
DOI: 10.1515/bmt.2006.063
Google Scholar
[27]
P. Laferriere, E. D. Lemaire, and A. D. C. Chan, Surface Electromyographic Signals Using Dry Electrodes,, IEEE Trans. Instrum. Meas., vol. 60, no. 10, p.3259–3268, (2011).
DOI: 10.1109/tim.2011.2164279
Google Scholar
[28]
C. Pylatiuk et al., Comparison of Surface Monitoring Electrodes for Long Term Use in Rehabilitation Device Control,, in 2009 IEEE International Conference on Rehabilitation Robotics, Kyoto, 2009, 2009, p.300–304.
DOI: 10.1109/icorr.2009.5209576
Google Scholar
[29]
P. Visconti and F. Gaetani, Technical Features and Functionalities of Myo Armband : An Overview on Related Literature and Advanced Applications of Myoelectric Armbands Mainly Focused on Arm Prostheses,, Int. J. Smart Sens. Intell. Syst., vol. 0, no. 0, p.1–25, (2018).
DOI: 10.21307/ijssis-2018-005
Google Scholar
[30]
P. Konrad, The ABC of EMG A Practical Introduction to Kinesiological Electromyography, no. April. (2005).
Google Scholar