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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:

Towards Real-Time Prediction of Freezing of Gait in Patients With Parkinson’s Disease: A Novel Deep One-Class Classifier
Nader Naghavi, Eric Wade
IEEE Journal of Biomedical and Health Informatics (2021) Vol. 26, Iss. 4, pp. 1726-1736
Open Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

Deep learning and wearable sensors for the diagnosis and monitoring of Parkinson’s disease: A systematic review
Luis Sigcha, Luigi Borzì, Federica Amato, et al.
Expert Systems with Applications (2023) Vol. 229, pp. 120541-120541
Open Access | Times Cited: 54
Multi-Modal Deep Learning Diagnosis of Parkinson’s Disease—A Systematic Review
Vasileios Skaramagkas, Anastasia Pentari, Zinovia Kefalopoulou, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2023) Vol. 31, pp. 2399-2423
Open Access | Times Cited: 32
Real-time detection of freezing of gait in Parkinson’s disease using multi-head convolutional neural networks and a single inertial sensor
Luigi Borzì, Luis Sigcha, Daniel Rodríguez-Martín, et al.
Artificial Intelligence in Medicine (2022) Vol. 135, pp. 102459-102459
Closed Access | Times Cited: 37
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: 21
Improvement of Performance in Freezing of Gait detection in Parkinson’s Disease using Transformer networks and a single waist-worn triaxial accelerometer
Luis Sigcha, Luigi Borzì, Ignacio Pavón García, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 116, pp. 105482-105482
Open Access | Times Cited: 26
Insights into Parkinson’s Disease-Related Freezing of Gait Detection and Prediction Approaches: A Meta Analysis
Hagar Elbatanouny, Natasa Kleanthous, Hayssam Dahrouj, et al.
Sensors (2024) Vol. 24, Iss. 12, pp. 3959-3959
Open Access | Times Cited: 5
Deep learning algorithms for detecting freezing of gait in Parkinson’s disease: A cross-dataset study
Luis Sigcha, Luigi Borzì, Gabriella Olmo
Expert Systems with Applications (2024) Vol. 255, pp. 124522-124522
Open Access | Times Cited: 5
Context Recognition Algorithms for Energy-Efficient Freezing-of-Gait Detection in Parkinson’s Disease
Luigi Borzì, Luis Sigcha, Gabriella Olmo
Sensors (2023) Vol. 23, Iss. 9, pp. 4426-4426
Open Access | Times Cited: 12
Design of an integrated model with temporal graph attention and transformer-augmented RNNs for enhanced anomaly detection
Sai Babu Veesam, Aravapalli Rama Satish, Sreenivasulu Tupakula, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Freezing of gait detection: The effect of sensor type, position, activities, datasets, and machine learning model
Luigi Borzì, Florenc Demrozi, Ruggero Bacchin, et al.
Journal of Parkinson s Disease (2025)
Open Access
Ankle Sensor-Based Detection of Freezing of Gait in Parkinson’s Disease in Semi-Free Living Environments
Juan Daniel Delgado-Terán, Kjell Hilbrants, Dzeneta Mahmutović, et al.
Sensors (2025) Vol. 25, Iss. 6, pp. 1895-1895
Open Access
Digital Biomarkers for Parkinson's Disease: A Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait (Preprint)
Wenhao Qi, S. Shen, Chaoqun Dong, et al.
Journal of Medical Internet Research (2025)
Open Access
Forecasting motion trajectories of elbow and knee joints during infant crawling based on long–short-term memory (LSTM) networks
Jieyi Mo, Qiliang Xiong, Ying Chen, et al.
BioMedical Engineering OnLine (2025) Vol. 24, Iss. 1
Open Access
A new lightweight deep learning model optimized with pruning and dynamic quantization to detect freezing gait on wearable devices
Myung-Kyu Yi, Seong Oun Hwang
Computers in Biology and Medicine (2025) Vol. 191, pp. 110138-110138
Closed Access
Deep learning techniques for detecting freezing of gait episodes in Parkinson’s disease using wearable sensors
Mosleh Hmoud Al-Adhaileh, Asim Wadood, Theyazn H. H. Aldhyani, et al.
Frontiers in Physiology (2025) Vol. 16
Open Access
Predicting freezing of gait in patients with Parkinson's disease by combination of Manually-Selected and deep learning features
Hua Sun, Qiang Ye, Yi Xia
Biomedical Signal Processing and Control (2023) Vol. 88, pp. 105639-105639
Closed Access | Times Cited: 10
Prediction of Freezing of Gait in Parkinson’s disease based on multi-channel time-series neural network
Boyan Wang, Xuegang Hu, Rongjun Ge, et al.
Artificial Intelligence in Medicine (2024) Vol. 154, pp. 102932-102932
Closed Access | Times Cited: 3
Episode-level prediction of freezing of gait based on wearable inertial signals using a deep neural network model
Debin Huang, Chan Wu, Yiwen Wang, et al.
Biomedical Signal Processing and Control (2023) Vol. 88, pp. 105613-105613
Closed Access | Times Cited: 8
Comparison of state-of-the-art deep learning architectures for detection of freezing of gait in Parkinson’s disease
Emilie Klaver, Irene B. Heijink, Gianluigi Silvestri, et al.
Frontiers in Neurology (2023) Vol. 14
Open Access | Times Cited: 7
FoG-Finder: Real-time Freezing of Gait Detection and Treatment
Kenneth Koltermann, Woosub Jung, GinaMari G. Blackwell, et al.
(2023)
Open Access | Times Cited: 6
Quantitative Analysis of Lower Limb Motion in Parkinson’s Disease Based on Inertial Sensors
Ruichen Liu, Zhelong Wang, Hongyu Zhao, et al.
IEEE Sensors Journal (2022) Vol. 22, Iss. 21, pp. 20937-20946
Closed Access | Times Cited: 7
An insight on recent advancements and future perspectives in detection techniques of Parkinson’s disease
Snehith Sankineni, Aanchal Saraswat, M. Suchetha, et al.
Evolutionary Intelligence (2023) Vol. 17, Iss. 3, pp. 1715-1731
Closed Access | Times Cited: 2
Time Orient Acceleration Gait Pattern Based FOG Prediction on Parkinson Patients Using Deep Learning and Wearable Sensors
Ezhilarasi Jegadeesan, Senthil Kiumar Thillaigovindhan
Journal of Advanced Research in Applied Sciences and Engineering Technology (2024) Vol. 47, Iss. 1, pp. 219-229
Open Access
Gait-Guard: Turn-aware Freezing of Gait Detection for Non-intrusive Intervention Systems
Kenneth Koltermann, J. C. R. Clapham, GinaMari G. Blackwell, et al.
(2024), pp. 61-72
Closed Access
Enhancing Freezing of Gait Detection in Parkinson’s Through Fine-Tuned Deep Learning Models
M Tebaldi, Graziano Pravadelli, Florenc Demrozi, et al.
(2024), pp. 87-94
Closed Access
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