Simulation on Application of EMG Signals for DC Motor Control
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-5547-3_14
Reference17 articles.
1. Ahmed R, Halder R, Uddin M, Mondal PC, Karmaker AK (2018) Prosthetic arm control using electromyography (EMG) signal. IEEE. https://doi.org/10.1109/ICAEEE.2018.8642968
2. Devaraj A, Nair AK (2020) Hand gesture signal classification using machine learning. In: 2020 international conference on communication and signal processing (ICCSP), 28–30 July 2020, pp 0390–0394. https://doi.org/10.1109/ICCSP48568.2020.9182045
3. Kaczmarek P, Mánkowski T, Tomczýnski J (2019) PutEMG—a surface electromyography hand gesture recognition dataset. Sensors (Switzerland) 19(16). https://doi.org/10.3390/s19163548
4. Khairuddin IM, Sidek SN, Majeed APPA, Puzi AA (2019) Classifying motion intention from EMG signal: a k-NN approach. In: 2019 7th international conference on mechatronics engineering (ICOM), 30–31 October 2019, pp 1–4. https://doi.org/10.1109/ICOM47790.2019.8952042
5. Kunapipat M, Phukpattaranont P, Neranon P, Thongpull K (2018) Sensor-assisted EMG data recording system. In: 2018 15th international conference on electrical engineering/electronics, computer, telecommunications and information technology (ECTI-CON), 18–21 July 2018, pp 772–775. https://doi.org/10.1109/ECTICon.2018.8619880
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