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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:

Identification of Characteristic Motor Patterns Preceding Freezing of Gait in Parkinson’s Disease Using Wearable Sensors
Luca Palmerini, Laura Rocchi, Sînziana Mazilu, et al.
Frontiers in Neurology (2017) Vol. 8
Open Access | Times Cited: 106

Showing 1-25 of 106 citing articles:

Gait impairments in Parkinson's disease
Anat Mirelman, Paolo Bonato, Richard Camicioli, et al.
The Lancet Neurology (2019) Vol. 18, Iss. 7, pp. 697-708
Closed Access | Times Cited: 550
Surgery for spontaneous intracerebral hemorrhage
Airton Leonardo de Oliveira Manoel
Critical Care (2020) Vol. 24, Iss. 1
Open Access | Times Cited: 247
Wearable-Sensor-Based Detection and Prediction of Freezing of Gait in Parkinson’s Disease: A Review
Scott Pardoel, Jonathan Kofman, Julie Nantel, et al.
Sensors (2019) Vol. 19, Iss. 23, pp. 5141-5141
Open Access | Times Cited: 158
Measuring freezing of gait during daily-life: an open-source, wearable sensors approach
Martina Mancini, Vrutangkumar V. Shah, Samuel Stuart, et al.
Journal of NeuroEngineering and Rehabilitation (2021) Vol. 18, Iss. 1
Open Access | Times Cited: 122
Multi-modality machine learning predicting Parkinson’s disease
Mary B. Makarious, Hampton L. Leonard, Dan Vitale, et al.
npj Parkinson s Disease (2022) Vol. 8, Iss. 1
Open Access | Times Cited: 85
Parkinson’s Disease Management via Wearable Sensors: A Systematic Review
Huma Mughal, Abdul Rehman Javed, Muhammad Rizwan, et al.
IEEE Access (2022) Vol. 10, pp. 35219-35237
Open Access | Times Cited: 75
Internet of Things Technologies and Machine Learning Methods for Parkinson’s Disease Diagnosis, Monitoring and Management: A Systematic Review
Κωνσταντίνα-Μαρία Γιαννακοπούλου, Ioanna Roussaki, Konstantinos Demestichas
Sensors (2022) Vol. 22, Iss. 5, pp. 1799-1799
Open Access | Times Cited: 69
Clinical and methodological challenges for assessing freezing of gait: Future perspectives
Martina Mancini, Bastiaan R. Bloem, Fay B. Horak, et al.
Movement Disorders (2019) Vol. 34, Iss. 6, pp. 783-790
Open Access | Times Cited: 141
Gait analysis in neurological populations: Progression in the use of wearables
Yunus Çelik, Samuel Stuart, Wai Lok Woo, et al.
Medical Engineering & Physics (2020) Vol. 87, pp. 9-29
Open Access | Times Cited: 124
Prediction of Freezing of Gait in Parkinson’s Disease Using Wearables and Machine Learning
Luigi Borzì, Ivan Mazzetta, Alessandro Zampogna, et al.
Sensors (2021) Vol. 21, Iss. 2, pp. 614-614
Open Access | Times Cited: 94
Wearable and Biodegradable Sensors for Clinical and Environmental Applications
Thaísa A. Baldo, Lucas F. de Lima, Letícia F. Mendes, et al.
ACS Applied Electronic Materials (2020) Vol. 3, Iss. 1, pp. 68-100
Closed Access | Times Cited: 70
DeepFoG: An IMU-Based Detection of Freezing of Gait Episodes in Parkinson’s Disease Patients via Deep Learning
Thomas Bikias, Dimitrios Iakovakis, Stelios Hadjidimitriou, et al.
Frontiers in Robotics and AI (2021) Vol. 8
Open Access | Times Cited: 65
Gait speed in clinical and daily living assessments in Parkinson’s disease patients: performance versus capacity
Arash Atrsaei, Marta Francisca Corrà, Farzin Dadashi, et al.
npj Parkinson s Disease (2021) Vol. 7, Iss. 1
Open Access | Times Cited: 62
Detection and assessment of Parkinson's disease based on gait analysis: A survey
Yao Guo, Jianxin Yang, Yuxuan Liu, et al.
Frontiers in Aging Neuroscience (2022) Vol. 14
Open Access | Times Cited: 38
Do the gait domains change in PD patients with freezing of gait during their ‘interictal’ period?
Jiahao Zhao, Chen Liu, Ying Wan, et al.
BMC Geriatrics (2025) Vol. 25, Iss. 1
Open Access | Times Cited: 1
Toward a Wearable System for Predicting Freezing of Gait in People Affected by Parkinson's Disease
Florenc Demrozi, Ruggero Bacchin, Stefano Tamburin, et al.
IEEE Journal of Biomedical and Health Informatics (2019) Vol. 24, Iss. 9, pp. 2444-2451
Closed Access | Times Cited: 64
Prediction of Freezing of Gait in Parkinson’s Disease Using Statistical Inference and Lower–Limb Acceleration Data
Nader Naghavi, Eric Wade
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2019) Vol. 27, Iss. 5, pp. 947-955
Open Access | Times Cited: 55
Early Detection of Freezing of Gait during Walking Using Inertial Measurement Unit and Plantar Pressure Distribution Data
Scott Pardoel, Gaurav Shalin, Julie Nantel, et al.
Sensors (2021) Vol. 21, Iss. 6, pp. 2246-2246
Open Access | Times Cited: 46
Recent trends in wearable device used to detect freezing of gait and falls in people with Parkinson’s disease: A systematic review
Tinghuai Huang, Meng Li, Jian‐Wei Huang
Frontiers in Aging Neuroscience (2023) Vol. 15
Open Access | Times Cited: 20
An Explainable Spatial-Temporal Graphical Convolutional Network to Score Freezing of Gait in Parkinsonian Patients
Hyeokhyen Kwon, Gari D. Clifford, Imari Genias, et al.
Sensors (2023) Vol. 23, Iss. 4, pp. 1766-1766
Open Access | Times Cited: 17
On‐Demand Cueing for Freezing of Gait in Parkinson's Disease: A Randomized Controlled Trial
Demi Zoetewei, Talia Herman, Pieter Ginis, et al.
Movement Disorders (2024) Vol. 39, Iss. 5, pp. 876-886
Open Access | Times Cited: 7
A machine learning contest enhances automated freezing of gait detection and reveals time-of-day effects
Amit Salomon, Eran Gazit, Pieter Ginis, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 7
Deep Domain Adaptation to Predict Freezing of Gait in Patients with Parkinson's Disease
Vishwas G. Torvi, Aditya Bhattacharya, Shayok Chakraborty
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA) (2018), pp. 1001-1006
Closed Access | Times Cited: 51
Prediction of Gait Freezing in Parkinsonian Patients: A Binary Classification Augmented With Time Series Prediction
Arash Arami, Antonios Poulakakis-Daktylidis, Yen Tai, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2019) Vol. 27, Iss. 9, pp. 1909-1919
Closed Access | Times Cited: 47
Prediction of Freezing of Gait in Patients With Parkinson’s Disease by Identifying Impaired Gait Patterns
Yuqian Zhang, Weiwu Yan, Yifei Yao, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2020) Vol. 28, Iss. 3, pp. 591-600
Closed Access | Times Cited: 47
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