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2020 – today
- 2023
[j4]M. S. Çelik, Cengiz Tepe, Ilyas Eminoglu:
Comparison of myo-electrical control methods: From muscle energy consumption to mechanical speed output. Biomed. Signal Process. Control. 84: 104732 (2023)- 2022
- [j3]Cengiz Tepe
, Muhammed Erdim:
Classification of surface electromyography and gyroscopic signals of finger gestures acquired by Myo armband using machine learning methods. Biomed. Signal Process. Control. 75: 103588 (2022) - [j2]Cengiz Tepe, Ertugrul F. Savastaer:
A computer-aided educational device and toolbox for biomedical signal processing at the undergraduate level. Comput. Appl. Eng. Educ. 30(6): 1725-1738 (2022) - 2021
- [j1]Cengiz Tepe, Mehmet Can Demir:
The effects of the number of channels and gyroscopic data on the classification performance in EMG data acquired by Myo armband. J. Comput. Sci. 51: 101348 (2021)
2010 – 2019
- 2016
- [c5]Mustafa Resit Tavus, Nurettin Senyer, Cengiz Tepe, Bunyamin Karabulut:
A novel approach to detect QRS based on partition and intensity on ECG signals. SIU 2016: 2213-2216 - 2015
- [c4]Cengiz Tepe, Ilyas Eminoglu, Nurettin Senyer:
Estimate angle information of hand open-close from surface electromyogram (sEMG). SIU 2015: 1-4 - 2014
- [c3]Cengiz Tepe, Nurettin Senyer, Ilyas Eminoglu:
Prediction speed of hand open-close by using Neural Network. SIU 2014: 1090-1093 - [c2]Cengiz Tepe, Ilyas Eminoglu, Nurettin Senyer:
Feature extraction of wavelet transform for sEMG pattern classification. SIU 2014: 1098-1101 - 2013
- [c1]Hanife Kucuk, Cengiz Tepe, Ilyas Eminoglu:
Classification of EMG signals by k-Nearest Neighbor algorithm and Support vector machine methods. SIU 2013: 1-4
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