Using High Density EMG to Proportionally Control 3D Model of Human Hand
How to cite (IJASEIT) :
F. I. Serdana, “Controlling 3D Model of Human Hand Exploiting Synergistic Activation of The Upper Limb Muscles,” IES 2022 - 2022 International Electronics Symposium: Energy Development for Climate Change Solution and Clean Energy Transition, Proceeding, pp. 142-149, 2022, doi: 10.1109/IES55876.2022.9888488.
A. Theuer et al., “Case Report: Optimizing Daily Function for People with Below-elbow Limb Deficiency with the SoftHand Pro.,” Open Journal of Occupational Therapy, vol. 8, no. 4, pp. 1-9, Sep. 2020, doi: 10.15453/2168-6408.1602.
M. H. Hasbani, D. Y. Barsakcioglu, M. K. Jung, and D. Farina, “Simultaneous and proportional control of wrist and hand degrees of freedom with kinematic prediction models from high-density EMG,” Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2022-July, pp. 764-767, 2022, doi: 10.1109/EMBC48229.2022.9871346.
M. Nowak, I. Vujaklija, A. Sturma, C. Castellini, and D. Farina, “Simultaneous and Proportional Real-Time Myocontrol of up to Three Degrees of Freedom of the Wrist and Hand,” IEEE Trans Biomed Eng, 2022, doi: 10.1109/TBME.2022.3194104.
“bebionic Hand EQD | The most lifelike prosthetic hand.” https://www.ottobock.com/en-us/product/8E70 (accessed Dec. 09, 2022).
“Open Bionics - Turning Disabilities into Superpowers.” https://openbionics.com/en/ (accessed Dec. 09, 2022).
M. N. Castro and S. Dosen, “Continuous Semi-autonomous Prosthesis Control Using a Depth Sensor on the Hand,” Front Neurorobot, vol. 16, p. 51, Mar. 2022, doi: 10.3389/FNBOT.2022.814973/BIBTEX.
P. Weiner, J. Starke, S. Rader, F. Hundhausen, and T. Asfour, “Designing Prosthetic Hands With Embodied Intelligence: The KIT Prosthetic Hands,” Front Neurorobot, vol. 16, p. 25, Mar. 2022, doi: 10.3389/FNBOT.2022.815716/BIBTEX.
R. F. Becker, “The cerebral cortex of man. By Wilder Penfield and Theodore Rasmussen. The Macmillan Company, New York, N.Y. 1950. 248 pp,” Am. J. Phys. Anthropol., vol. 11, no. 3, pp. 441-444, 1953.
B. Xu et al., “Natural grasping movement recognition and force estimation using electromyography,” Front Neurosci, vol. 16, p. 1020086, Oct. 2022, doi: 10.3389/FNINS.2022.1020086.
R. J. Smith, F. Tenore, D. Huberdeau, R. Etienne-cummings, and N. v Thakor, “Continuous Decoding of Finger Position from Surface EMG Signals for the Control of Powered Prostheses,” Crit. Rev., pp, pp. 197-200, 2009.
M. Hioki and H. Kawasaki, “Estimation of Finger Joint Angles from sEMG Using a Neural Network Including Time Delay Factor and Recurrent Structure,” ISRN Rehabil., vol. 2012, pp. 1-13, 2012.
J. Ngeo, T. Tamei, and T. Shibata, “Estimation of continuous multi-DOF finger joint kinematics from surface EMG using a multi-output Gaussian Process,” in 2014 36th Annu, 2014: Int. Conf. IEEE Eng. Med. Biol. Soc. EMBC, 2014, pp. 3537-3540.
C. Chen, G. Chai, W. Guo, X. Sheng, D. Farina, and X. Zhu, “Prediction of finger kinematics from discharge timings of motor units: Implications for intuitive control of myoelectric prostheses,” J. Neural Eng, vol. 16, p. 2, 2019.
D. Blana, W. Murray, A. Ganguly, A. Krasoulis, K. Nazarpour, and E. Chadwick, “Model-based control of individual finger movements for prosthetic hand function,” Keele Univ, pp. 1-9, 2019.
S. Muceli and D. Farina, “Simultaneous and proportional estimation of hand kinematics from EMG during mirrored movements at multiple degrees-of-freedom,” IEEE Trans. Neural Syst. Rehabil. Eng, vol. 20, no. 3, pp. 371-378, 2012.
W. Li, P. Shi, and H. Yu, “Gesture Recognition Using Surface Electromyography and Deep Learning for Prostheses Hand: State-of-the-Art, Challenges, and Future,” Front Neurosci, vol. 15, p. 259, Apr. 2021, doi: 10.3389/FNINS.2021.621885/BIBTEX.
N. J. Jarque-Bou, J. L. Sancho-Bru, and M. Vergara, “A systematic review of EMG applications for the characterization of forearm and hand muscle activity during activities of daily living: Results, challenges, and open issues,” Sensors, vol. 21, no. 9. MDPI AG, May 01, 2021. doi: 10.3390/s21093035.
C. Boudreau, J. Corkum, I. Grant, and D. T. Tang, “A comparative study using electromyography to assess hand exercises for rehabilitation after ulnar nerve decompression,” Journal of Plastic, Reconstructive & Aesthetic Surgery, vol. 75, no. 1, pp. 307-313, Jan. 2022, doi: 10.1016/J.BJPS.2021.08.042.
A. A. Adewuyi, L. J. Hargrove, and T. A. Kuiken, “An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control,” in IEEE Trans, vol. 24, no. 4: neural Syst. Rehabil. Eng. a Publ. IEEE Eng. Med. Biol. Soc, 2016, pp. 485-494.
K. Fujimura, H. Kagaya, and H. Tanikawa, “Kinematic Analysis for Repetitive Peripheral Magnetic Stimulation of the Intrinsic Muscles of the Hand,” Applied Sciences (Switzerland), vol. 12, no. 18, Sep. 2022, doi: 10.3390/app12189015.
M. Barsotti, S. Dupan, I. Vujaklija, S. DoÅ¡en, A. Frisoli, and D. Farina, “Online Finger Control Using High-Density EMG and Minimal Training Data for Robotic Applications,” IEEE Robot Autom Lett, vol. 4, no. 2, pp. 217-223, Apr. 2019, doi: 10.1109/LRA.2018.2885753.
E. J. Weiss and M. Flanders, “Muscular and postural synergies of the human hand,” J. Neurophysiol., vol. 92, no. 1, pp. 523-535, 2004.
S. Tateno, H. Liu, and J. Ou, “Development of sign language motion recognition system for hearing-impaired people using electromyography signal,” Sensors (Switzerland), vol. 20, no. 20, pp. 1-22, Oct. 2020, doi: 10.3390/s20205807.
I. Carpinella, P. Mazzoleni, M. Rabuffetti, R. Thorsen, and M. Ferrarin, “Experimental protocol for the kinematic analysis of the hand: Definition and repeatability,” Gait Posture, vol. 23, no. 4, pp. 445-454, 2006.
T. Bao, A. Zaidi, S. Xie, and Z. Zhang, “Surface-EMG based Wrist Kinematics Estimation using Convolutional Neural Network,” p, pp. 1-4, 2019.
A. Sharma, P. Madhushri, V. Kushvaha, and A. Kumar, “Prediction of the Fracture Toughness of Silicafilled Epoxy Composites using K-Nearest Neighbor (KNN) Method,” 2020 International Conference on Computational Performance Evaluation, ComPE 2020, pp. 194-198, Jul. 2020, doi: 10.1109/COMPE49325.2020.9200093.
U. Phutane, M. Roller, A. Boebel, and S. Leyendecker, “Optimal control of grasping problem using postural synergies,” in Advances in Transdisciplinary Engineering, Aug. 2020, vol. 11, pp. 206-213. doi: 10.3233/ATDE200026.
J. A. Raszewski, A. C. Black, and M. Varacallo, “Anatomy, Shoulder and Upper Limb, Hand Compartments,” StatPearls, Sep. 2022, Accessed: Dec. 09, 2022. [Online]. Available: https://www.ncbi.nlm.nih.gov/books/NBK532942/
N. J. Jarque-Bou, M. Vergara, J. L. Sancho-Bru, V. Gracia-Ibí¡ñez, and A. Roda-Sales, “A calibrated database of kinematics and EMG of the forearm and hand during activities of daily living,” Sci Data, vol. 6, no. 1, Dec. 2019, doi: 10.1038/s41597-019-0285-1.
X. Hu, A. Song, J. Wang, H. Zeng, and W. Wei, “Finger Movement Recognition via High-Density Electromyography of Intrinsic and Extrinsic Hand Muscles,” Sci Data, vol. 9, no. 1, p. 373, 2022, doi: 10.1038/s41597-022-01484-2.
B.-S. Lin, I.-J. Lee, P.-Y. Chiang, S.-Y. Huang, and C.-W. Peng, “A Modular Data Glove System for Finger and Hand Motion Capture Based on Inertial Sensors,” in J, vol. 39, no. 4: Med. Biol. Eng, 2019, pp. 532-540.
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