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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Evaluating the performance of Kalman filter on elbow joint angle prediction based on electromyography
Triwiyanto Triwiyanto, Oyas Wahyunggoro, Hanung Adi Nugroho, et al.
International Journal of Precision Engineering and Manufacturing (2017) Vol. 18, Iss. 12, pp. 1739-1748
Closed Access | Times Cited: 33

Showing 1-25 of 33 citing articles:

Continuous Motion Intention Prediction Using sEMG for Upper-Limb Rehabilitation: A Systematic Review of Model-Based and Model-Free Approaches
Zijun Wei, Zhiqiang Zhang, Sheng Quan Xie
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2024) Vol. 32, pp. 1487-1504
Open Access | Times Cited: 7
Development of Robot-Based Upper Limb Devices for Rehabilitation Purposes: a Systematic Review
Jyotindra Narayan, Bhaben Kalita, Santosha K. Dwivedy
Augmented Human Research (2021) Vol. 6, Iss. 1
Closed Access | Times Cited: 40
Muscle fatigue compensation of the electromyography signal for elbow joint angle estimation using adaptive feature
Triwiyanto Triwiyanto, Oyas Wahyunggoro, Hanung Adi Nugroho, et al.
Computers & Electrical Engineering (2018) Vol. 71, pp. 284-293
Closed Access | Times Cited: 47
Recognizing and predicting muscular fatigue of biceps brachii in motion with novel fabric strain sensors based on machine learning
C.-C. Wang, Xi Wang, Qiao Li, et al.
Biomedical Signal Processing and Control (2024) Vol. 96, pp. 106647-106647
Closed Access | Times Cited: 4
Prediction of Joint Angles Based on Human Lower Limb Surface Electromyography
Hongyu Zhao, Zhibo Qiu, Daoyong Peng, et al.
Sensors (2023) Vol. 23, Iss. 12, pp. 5404-5404
Open Access | Times Cited: 10
Deep learning approach to improve the recognition of hand gesture with multi force variation using electromyography signal from amputees
Triwiyanto Triwiyanto, I Putu Alit Pawana, Wahyu Caesarendra
Medical Engineering & Physics (2024) Vol. 125, pp. 104131-104131
Closed Access | Times Cited: 2
Elbow Motion Trajectory Prediction Using a Multi-Modal Wearable System: A Comparative Analysis of Machine Learning Techniques
Kieran Little, Bobby K Pappachan, Sibo Yang, et al.
Sensors (2021) Vol. 21, Iss. 2, pp. 498-498
Open Access | Times Cited: 16
Dynamic Accuracy Improvement of a MEMS AHRS for Small UAVs
Min-Shik Roh, Beom-Soo Kang
International Journal of Precision Engineering and Manufacturing (2018) Vol. 19, Iss. 10, pp. 1457-1466
Closed Access | Times Cited: 19
Post-Stroke Rehabilitation Exosceleton Movement Control using EMG Signal
Akif Rahmatillah, Osmalina Nur Rahma, Muhammad Amin, et al.
International Journal on Advanced Science Engineering and Information Technology (2018) Vol. 8, Iss. 2, pp. 616-616
Open Access | Times Cited: 15
Adaptive threshold to compensate the effect of muscle fatigue on elbow-joint angle estimation based on electromyography
Triwiyanto Triwiyanto, Oyas Wahyunggoro, Hanung Adi Nugroho, et al.
JOURNAL OF MECHANICAL ENGINEERING AND SCIENCES (2018) Vol. 12, Iss. 3, pp. 3786-3796
Open Access | Times Cited: 10
Evaluating the linear regression of Kalman filter model on elbow joint angle estimation using electromyography signal
Triwiyanto Triwiyanto, Oyas Wahyunggoro, Hanung Adi Nugroho, et al.
AIP conference proceedings (2018) Vol. 2011, pp. 020004-020004
Open Access | Times Cited: 6
A Wearable Device based on IMU and EMG Sensors for Remote Monitoring of Elbow Rehabilitation
Diego M. Lavado, Emir A. Vela
2022 E-Health and Bioengineering Conference (EHB) (2022), pp. 1-4
Closed Access | Times Cited: 4
State of the Art Methods of Machine Learning for Prosthetic Hand Development: A Review
Triwiyanto Triwiyanto, Anita Miftahul Maghfiroh, Syevana Dita Musvika, et al.
Lecture notes in electrical engineering (2023), pp. 555-574
Closed Access | Times Cited: 2
Impact of robotic exoskeleton based on electromyography for rehabilitation of post stroke patient
Bedjo Utomo, Triwiyanto Triwiyanto, Suhartini Suhartini, et al.
AIP conference proceedings (2018) Vol. 2011, pp. 020105-020105
Open Access | Times Cited: 4
Deep Convolution Neural Network to Improve Hand Motion Classification Performance Against Varying Orientation Using Electromyography Signal
Triwiyanto Triwiyanto, Vugar Abdullayev, Abdussalam Ali Ahmed
International Journal of Precision Engineering and Manufacturing (2024) Vol. 25, Iss. 6, pp. 1289-1301
Closed Access
A CNN-LSTM neural network model for upper limb joint angle estimation based on mechanomyograph
Zhenjiu Ma, Gangsheng Cao, Gaofeng Kang, et al.
(2024), pp. 483-489
Closed Access
In-silico development and assessment of a Kalman filter motor decoder for prosthetic hand control
Mai Gamal, Mohamed H. Mousa, Seif Eldawlatly, et al.
Computers in Biology and Medicine (2021) Vol. 132, pp. 104353-104353
Open Access | Times Cited: 4
Simulation of Knee Joint Angle Estimation from EMG Signal for Post ACL Reconstruction Surgical Rehabilitation
Yusrinourdi Muhammad Zuchruf, Talitha Asmaria, Riries Rulaningtyas, et al.
Journal of Physics Conference Series (2021) Vol. 1805, Iss. 1, pp. 012019-012019
Open Access | Times Cited: 4
Upper Limb Elbow Joint Angle Estimation Based on Electromyography Using Artificial Neural Network
Triwiyanto Triwiyanto, Oyas Wahyunggoro, Hanung Adi Nugroho, et al.
(2018), pp. 1-6
Closed Access | Times Cited: 3
Dynamic feature for an effective elbow-joint angle estimation based on electromyography signals
Triwiyanto Triwiyanto, Triana Rahmawati, Endro Yulianto, et al.
Indonesian Journal of Electrical Engineering and Computer Science (2020) Vol. 19, Iss. 1, pp. 178-178
Open Access | Times Cited: 3
Preliminary research of surface electromyogram (sEMG) signal analysis for robotic arm control
Pringgo Widyo Laksono, Minoru Sasaki, Kojiro Matsushita, et al.
AIP conference proceedings (2020) Vol. 2217, pp. 030034-030034
Closed Access | Times Cited: 3
Comparative SNR Analysis Between Instrument ADAS1000 and AD620
Tri Arief Sardjono, Hendra Kusuma, Tasripan Tasripan, et al.
Jurnal Sistim Informasi dan Teknologi (2022), pp. 129-133
Open Access | Times Cited: 2
Time Delay Neural Network to Estimate the Elbow Joint Angle Based on Electromyography
Triwiyanto Triwiyanto, Oyas Wahyunggoro, Hanung Adi Nugroho, et al.
(2018), pp. 100-105
Closed Access | Times Cited: 2
Performance Analysis of the Windowing Technique on Elbow Joint Angle Estimation Using Electromyography Signal
Triwiyanto Triwiyanto, Oyas Wahyunggoro, Hanung Adi Nugroho, et al.
Journal of Physics Conference Series (2018) Vol. 1108, pp. 012004-012004
Open Access | Times Cited: 2
Application of EMG and Force Signals of Elbow Joint on Robot-assisted Arm Training
Riky Tri Yunardi, Eva Inaiyah Agustin, Risalatul Latifah, et al.
TELKOMNIKA (Telecommunication Computing Electronics and Control) (2018) Vol. 16, Iss. 6, pp. 2913-2913
Open Access | Times Cited: 2
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