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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:

Comparison of Laboratory and Daily-Life Gait Speed Assessment during ON and OFF States in Parkinson’s Disease
Marta Francisca Corrà, Arash Atrsaei, Ana Sardoreira, et al.
Sensors (2021) Vol. 21, Iss. 12, pp. 3974-3974
Open Access | Times Cited: 16

Showing 16 citing articles:

Virtual exam for Parkinson’s disease enables frequent and reliable remote measurements of motor function
Maximilien Burq, Erin Rainaldi, King Chung Ho, et al.
npj Digital Medicine (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 63
A Deep Learning Approach for Gait Event Detection from a Single Shank-Worn IMU: Validation in Healthy and Neurological Cohorts
Robbin Romijnders, Elke Warmerdam, Clint Hansen, et al.
Sensors (2022) Vol. 22, Iss. 10, pp. 3859-3859
Open Access | Times Cited: 41
Can Digital Mobility Assessment Enhance the Clinical Assessment of Disease Severity in Parkinson’s Disease?
Cameron Kirk, Rana Zia Ur Rehman, Brook Galna, et al.
Journal of Parkinson s Disease (2023) Vol. 13, Iss. 6, pp. 999-1009
Open Access | Times Cited: 7
Gait and turning characteristics from daily life increase ability to predict future falls in people with Parkinson's disease
Vrutangkumar V. Shah, Adam E. Jagodinsky, James McNames, et al.
Frontiers in Neurology (2023) Vol. 14
Open Access | Times Cited: 6
Predicting a Fall Based on Gait Anomaly Detection: A Comparative Study of Wrist-Worn Three-Axis and Mobile Phone-Based Accelerometer Sensors
Primož Kocuvan, Aleksander Hrastič, Andrea Kareska, et al.
Sensors (2023) Vol. 23, Iss. 19, pp. 8294-8294
Open Access | Times Cited: 6
Deep Clinical Phenotyping of Parkinson’s Disease: Towards a New Era of Research and Clinical Care
Zhiheng Xu, Bo Shen, Yilin Tang, et al.
Phenomics (2022) Vol. 2, Iss. 5, pp. 349-361
Open Access | Times Cited: 8
Accuracy of Step Count Estimations in Parkinson’s Disease Can Be Predicted Using Ambulatory Monitoring
Navid Shokouhi, Hamid Khodakarami, Chathurini V. Fernando, et al.
Frontiers in Aging Neuroscience (2022) Vol. 14
Open Access | Times Cited: 8
Assessing the clinical utility of inertial sensors for home monitoring in Parkinson’s disease: a comprehensive review
Stefano Sapienza, Olena Tsurkalenko, Marijus Giraitis, et al.
npj Parkinson s Disease (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 1
Cognition and Activity of Daily Living Function in people with Parkinson’s disease
Merle Bode, Elke Kalbe, Inga Liepelt‐Scarfone
Journal of Neural Transmission (2024) Vol. 131, Iss. 10, pp. 1159-1186
Open Access | Times Cited: 1
Effect of Levodopa and Environmental Setting on Gait and Turning Digital Markers Related to Falls in People with Parkinson's Disease
Vrutangkumar V. Shah, James McNames, Patricia Carlson‐Kuhta, et al.
Movement Disorders Clinical Practice (2022) Vol. 10, Iss. 2, pp. 223-230
Open Access | Times Cited: 6
Wearable systems in movement disorders
Edoardo Bianchini, Walter Maetzler
International review of movement disorders (2023), pp. 93-113
Closed Access | Times Cited: 3
Unsupervised but not supervised gait parameters are related to fatigue in Parkinson’s disease: a pilot study
Andrea Pilotto, Andrea Rizzardi, Cinzia Zatti, et al.
Frontiers in Aging Neuroscience (2023) Vol. 15
Open Access | Times Cited: 3
What about the use of Wearable Sensors to assess Fall Risk in Neurological Disorders? A Systematic Review. (Preprint)
Mirjam Bonanno, Augusto Ielo, Paolo De Pasquale, et al.
(2024)
Open Access
The Forward and Lateral Tilt Angle of the Neck and Trunk Measured by Three-Dimensional Gait and Motion Analysis as a Candidate for a Severity Index in Patients with Parkinson’s Disease
Hirofumi Matsumoto, Makoto Shiraishi, Ariaki Higashi, et al.
Neurology International (2022) Vol. 14, Iss. 3, pp. 727-737
Open Access | Times Cited: 2
Virtual Exam for Parkinson’s Disease Enables Frequent and Reliable Remote Measurements of Motor Function
Maximilien Burq, Erin Rainaldi, King Chung Ho, et al.
medRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 1
A Tool for Home Monitoring in Parkinson's Disease
Marco Mercuri, Francesco Pio Cecca, Sara Mattioli, et al.
(2022), pp. 1-5
Closed Access
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