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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:

Objective and automatic classification of Parkinson disease with Leap Motion controller
Abdul Haleem Butt, Erika Rovini, Cristina Dolciotti, et al.
BioMedical Engineering OnLine (2018) Vol. 17, Iss. 1
Open Access | Times Cited: 91

Showing 26-50 of 91 citing articles:

Parkinson’s Disease Detection by Using Machine Learning Algorithms and Hand Movement Signal from LeapMotion Sensor
Anastasia Moshkova, A. V. Samorodov, N.A. Voinova, et al.
(2020)
Closed Access | Times Cited: 27
Defining Optimal Exercises for Efficient Detection of Parkinson’s Disease Using Machine Learning and Wearable Sensors
Aleksandr Talitckii, Anna Anikina, Ekaterina Kovalenko, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-10
Closed Access | Times Cited: 22
Automatic range of motion measurement via smartphone images for telemedicine examination of the hand
Fanbin Gu, Jingyuan Fan, Zhaoyang Wang, et al.
Science Progress (2023) Vol. 106, Iss. 1
Open Access | Times Cited: 9
Deep learning framework for neurological diseases diagnosis through near-infrared eye video and time series imaging algorithms
Mohammed Hammoud, Ekaterina Kovalenko, Andrey Somov, et al.
Internet of Things (2023) Vol. 24, pp. 100914-100914
Closed Access | Times Cited: 8
Data-driven analyses of motor impairments in animal models of neurological disorders
Hardeep Singh Ryait, Edgar Bermudez-Contreras, Matthew Harvey, et al.
PLoS Biology (2019) Vol. 17, Iss. 11, pp. e3000516-e3000516
Open Access | Times Cited: 24
Evaluation for Parkinsonian Bradykinesia by deep learning modeling of kinematic parameters
Dong Jun Park, Jun Woo Lee, Myung Jun Lee, et al.
Journal of Neural Transmission (2021) Vol. 128, Iss. 2, pp. 181-189
Closed Access | Times Cited: 18
Using Multi-Factor Analysis to Predict Urban Flood Depth Based on Naive Bayes
Huiliang Wang, Hongfa Wang, Zening Wu, et al.
Water (2021) Vol. 13, Iss. 4, pp. 432-432
Open Access | Times Cited: 18
Distinguishing Between Parkinson’s Disease and Essential Tremor Through Video Analytics Using Machine Learning: A Pilot Study
Ekaterina Kovalenko, Aleksandr Talitckii, Anna Anikina, et al.
IEEE Sensors Journal (2020) Vol. 21, Iss. 10, pp. 11916-11925
Closed Access | Times Cited: 19
Non-Contact Hand Movement Analysis for Optimal Configuration of Smart Sensors to Capture Parkinson’s Disease Hand Tremor
Prashanna Khwaounjoo, Gurleen Singh, Sophie Grenfell, et al.
Sensors (2022) Vol. 22, Iss. 12, pp. 4613-4613
Open Access | Times Cited: 12
Stacked Denoising Autoencoder Based Parkinson’s Disease Classification using Improved Pigeon-Inspired Optimization Algorithm
P. Sukanya, Srinivasa B Rao
Computer Science (2024) Vol. 24, Iss. 4
Open Access | Times Cited: 2
Bradykinesia in dystonic hand tremor: kinematic analysis and clinical rating
Peter Matejička, Slavomir Kajan, Jozef Goga, et al.
Frontiers in Human Neuroscience (2024) Vol. 18
Open Access | Times Cited: 2
Real-time visual verification of leap motion controller measurements for reliable finger tapping test in Parkinson’s disease
Slavomír Kajan, Jozef Goga, Peter Matejička, et al.
Journal of Electrical Engineering (2024) Vol. 75, Iss. 4, pp. 325-332
Open Access | Times Cited: 2
Cervical Myelopathy Screening with Machine Learning Algorithm Focusing on Finger Motion Using Noncontact Sensor
Takafumi Koyama, Koji Fujita, Masaru Watanabe, et al.
Spine (2021) Vol. 47, Iss. 2, pp. 163-171
Closed Access | Times Cited: 15
A First Methodological Development and Validation of ReTap: An Open-Source UPDRS Finger Tapping Assessment Tool Based on Accelerometer-Data
Jeroen Habets, Rachel K. Spooner, Varvara Mathiopoulou, et al.
Sensors (2023) Vol. 23, Iss. 11, pp. 5238-5238
Open Access | Times Cited: 6
Assessing workload in using electromyography (EMG)-based prostheses
Junho Park, Joseph Berman, Albert Dodson, et al.
Ergonomics (2023) Vol. 67, Iss. 2, pp. 257-273
Closed Access | Times Cited: 6
Biomechanical parameters assessment for the classification of Parkinson Disease using Bidirectional Long Short-Term Memory
Abdul Haleem Butt, Filippo Cavallo, Carlo Maremmani, et al.
(2020), pp. 5761-5764
Closed Access | Times Cited: 15
Data-Driven Models for Objective Grading Improvement of Parkinson’s Disease
Abdul Haleem Butt, Erika Rovini, Hamido Fujita, et al.
Annals of Biomedical Engineering (2020) Vol. 48, Iss. 12, pp. 2976-2987
Open Access | Times Cited: 15
Towards Objective Quantification of Hand Tremors and Bradykinesia Using Contactless Sensors: A Systematic Review
Augusto García-Agúndez, Carsten Eickhoff
Frontiers in Aging Neuroscience (2021) Vol. 13
Open Access | Times Cited: 13
Sarcopenia and dynapenia is correlated to worse quality of life perception in middle-aged and older adults with Parkinson's disease
Jarson Pedro da Costa Pereira, José Reginaldo Alves de Queiroz Júnior, Luís César de Medeiros, et al.
Nutritional Neuroscience (2023) Vol. 27, Iss. 4, pp. 310-318
Closed Access | Times Cited: 5
Human-Robot Interaction (HRI) through hand gestures for possible future war robots: A leap motion controller application
Erhan Sesli
Multimedia Tools and Applications (2023) Vol. 83, Iss. 12, pp. 36547-36570
Closed Access | Times Cited: 5
Detection of Parkinson’s disease with keystroke data
Bahar Demir, Sezer Ulukaya, Oğuzhan Erdem
Computer Methods in Biomechanics & Biomedical Engineering (2023) Vol. 26, Iss. 13, pp. 1653-1667
Closed Access | Times Cited: 5
PD-Net: Quantitative Motor Function Evaluation for Parkinson's Disease via Automated Hand Gesture Analysis
Yifei Chen, Haoyu Ma, Jiangyuan Wang, et al.
(2021)
Closed Access | Times Cited: 12
Machine learning based risk prediction for Parkinson's disease with nationwide health screening data
Yu Hyun Park, Jee Hyun Suh, Yong Wook Kim, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 8
Offline Learning of Closed-Loop Deep Brain Stimulation Controllers for Parkinson Disease Treatment
Qitong Gao, Stephen L. Schmidt, Afsana Chowdhury, et al.
(2023), pp. 44-55
Open Access | Times Cited: 4
Classification of Hand-Movement Disabilities in Parkinson’s Disease Using a Motion-Capture Device and Machine Learning
Jungpil Shin, Masahiro Matsumoto, Md. Maniruzzaman, et al.
IEEE Access (2024) Vol. 12, pp. 52466-52479
Open Access | Times Cited: 1

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