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:

Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease
Alfonso Maria Ponsiglione, Carlo Ricciardi, Francesco Amato, et al.
Sensors (2022) Vol. 22, Iss. 5, pp. 1708-1708
Open Access | Times Cited: 12

Showing 12 citing articles:

Using Features Extracted From Upper Limb Reaching Tasks to Detect Parkinson’s Disease by Means of Machine Learning Models
Giuseppe Cesarelli, Leandro Donisi, Francesco Amato, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2023) Vol. 31, pp. 1056-1063
Open Access | Times Cited: 13

The Use of Head-Mounted Display Systems for Upper Limb Kinematic Analysis in Post-Stroke Patients: A Perspective Review on Benefits, Challenges and Other Solutions
Paolo De Pasquale, Mirjam Bonanno, Sepehr Mojdehdehbaher, et al.
Bioengineering (2024) Vol. 11, Iss. 6, pp. 538-538
Open Access | Times Cited: 4

A Pilot Study on Mixed-Reality Approaches for Detecting Upper-Limb Dysfunction in Multiple Sclerosis: Insights on Cerebellar Tremor
Etty Sabatino, Miriam Moschetta, Andrea Lucaroni, et al.
Virtual Worlds (2025) Vol. 4, Iss. 1, pp. 4-4
Open Access

A Full-Body IMU-Based Motion Dataset of Daily Tasks by Older and Younger Adults
Loreen Pogrzeba, Evelyn Muschter, Simon Hanisch, et al.
Scientific Data (2025) Vol. 12, Iss. 1
Open Access

The effect of gravity on hand spatio-temporal kinematic features during functional movements
Anna Bucchieri, Federico Tessari, Stefano Buccelli, et al.
PLoS ONE (2024) Vol. 19, Iss. 12, pp. e0310192-e0310192
Open Access | Times Cited: 1

A Cluster Analysis for Parkinson's Disease Phenotyping with Gait Parameters
Michela Russo, Carlo Ricciardi, Marianna Amboni, et al.
2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) (2023), pp. 882-887
Closed Access | Times Cited: 3

Feasibility of Tree-Based Machine Learning Models to Discriminate Safe and Unsafe Posture During Weight Lifting
G. Prisco, Maria Romano, Fabrizio Esposito, et al.
2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) (2023), pp. 870-875
Closed Access | Times Cited: 3

A neuromechanical model characterizing the motor planning and posture control in the voluntary lean in Parkinson’s disease
Niromand Jasimi Zindashti, Zahra Rahmati, Abolfazl Mohebbi, et al.
Journal of NeuroEngineering and Rehabilitation (2024) Vol. 21, Iss. 1
Open Access

A Statistical Approach for Functional Reach-to-Grasp Segmentation Using a Single Inertial Measurement Unit
Gregorio Dotti, Marco Caruso, Daniele Fortunato, et al.
Sensors (2024) Vol. 24, Iss. 18, pp. 6119-6119
Open Access

Performing a short sway to distinguish Parkinsonisms
Michela Russo, Carlo Ricciardi, Marianna Amboni, et al.
2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) (2022) Vol. 5, pp. 340-345
Closed Access | Times Cited: 2

Upper limb smoothness evaluation in Parkinson's disease: A preliminary study on the effects of a complementary therapy
Elena Pegolo, M. Romanato, C. Riccò, et al.
Gait & Posture (2022) Vol. 97, pp. S144-S145
Closed Access | Times Cited: 1

The Use of Kinematic Features in Evaluating Upper Limb Motor Function Learning Progress Based on Machine Learning
S.B. Dong, Justin Gallagher, Andrew Jackson, et al.
(2023), pp. 1-6
Closed Access

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