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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:

Digital Biomarkers of Mobility in Parkinson’s Disease During Daily Living
Vrutangkumar V. Shah, James McNames, Martina Mancini, et al.
Journal of Parkinson s Disease (2020) Vol. 10, Iss. 3, pp. 1099-1111
Open Access | Times Cited: 61

Showing 1-25 of 61 citing articles:

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: 125
Wearable movement-tracking data identify Parkinson’s disease years before clinical diagnosis
Ann‐Kathrin Schalkamp, Kathryn J. Peall, Neil A. Harrison, et al.
Nature Medicine (2023) Vol. 29, Iss. 8, pp. 2048-2056
Open Access | Times Cited: 79
The Role of Emergent Technologies in the Dynamic and Kinematic Assessment of Human Movement in Sport and Clinical Applications
Saeid Edriss, Cristian Romagnoli, Lucio Caprioli, et al.
Applied Sciences (2024) Vol. 14, Iss. 3, pp. 1012-1012
Open Access | Times Cited: 19
Body-Worn Sensors for Remote Monitoring of Parkinson’s Disease Motor Symptoms: Vision, State of the Art, and Challenges Ahead
Silvia Del Din, Cameron Kirk, Alison J. Yarnall, et al.
Journal of Parkinson s Disease (2021) Vol. 11, Iss. s1, pp. S35-S47
Open Access | Times Cited: 73
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: 42
Identification of motor progression in Parkinson’s disease using wearable sensors and machine learning
Charalampos Sotirakis, Zihui Su, Maksymilian A. Brzezicki, et al.
npj Parkinson s Disease (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 39
Quantitative Gait and Balance Outcomes for Ataxia Trials: Consensus Recommendations by the Ataxia Global Initiative Working Group on Digital-Motor Biomarkers
Winfried Ilg, Sarah Milne, Tanja Schmitz‐Hübsch, et al.
The Cerebellum (2023) Vol. 23, Iss. 4, pp. 1566-1592
Open Access | Times Cited: 28
Laboratory versus daily life gait characteristics in patients with multiple sclerosis, Parkinson’s disease, and matched controls
Vrutangkumar V. Shah, James McNames, Martina Mancini, et al.
Journal of NeuroEngineering and Rehabilitation (2020) Vol. 17, Iss. 1
Open Access | Times Cited: 63
Real‐Life Turning Movements Capture Subtle Longitudinal and Preataxic Changes in Cerebellar Ataxia
Annika Thierfelder, Jens Seemann, Natalie John, et al.
Movement Disorders (2022) Vol. 37, Iss. 5, pp. 1047-1058
Open Access | Times Cited: 33
Challenges and advances in the use of wearable sensors for lower extremity biomechanics
Jocelyn F. Hafer, Rachel V. Vitali, Reed D. Gurchiek, et al.
Journal of Biomechanics (2023) Vol. 157, pp. 111714-111714
Closed Access | Times Cited: 17
Integrating digital gait data with metabolomics and clinical data to predict outcomes in Parkinson’s disease
Cyril Brzenczek, Quentin Klopfenstein, Tom Hähnel, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 6
Evaluation of movement and brain activity
Mark Hallett, Lourdes M. DelRosso, Rodger J. Elble, et al.
Clinical Neurophysiology (2021) Vol. 132, Iss. 10, pp. 2608-2638
Open Access | Times Cited: 39
Balance telerehabilitation and wearable technology for people with Parkinson’s disease (TelePD trial)
Carla Silva‐Batista, Jennifer Wilhelm, Kathleen T. Scanlan, et al.
BMC Neurology (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 14
Wearable sensor devices can automatically identify the ON-OFF status of patients with Parkinson's disease through an interpretable machine learning model
Xiaolong Wu, Lin Ma, Penghu Wei, et al.
Frontiers in Neurology (2024) Vol. 15
Open Access | Times Cited: 5
Turning Detection During Gait: Algorithm Validation and Influence of Sensor Location and Turning Characteristics in the Classification of Parkinson’s Disease
Rana Zia Ur Rehman, Philipp Klocke, Sofia Hryniv, et al.
Sensors (2020) Vol. 20, Iss. 18, pp. 5377-5377
Open Access | Times Cited: 33
Effect of Bout Length on Gait Measures in People with and without Parkinson’s Disease during Daily Life
Vrutangkumar V. Shah, James McNames, Graham Harker, et al.
Sensors (2020) Vol. 20, Iss. 20, pp. 5769-5769
Open Access | Times Cited: 33
Sensors and algorithms for locomotion intention detection of lower limb exoskeletons
Duojin Wang, Xiaoping Gu, Hongliu Yu
Medical Engineering & Physics (2023) Vol. 113, pp. 103960-103960
Closed Access | Times Cited: 11
Specific Distribution of Digital Gait Biomarkers in Parkinson’s Disease Using Body-Worn Sensors and Machine Learning
Guoen Cai, Weikun Shi, Ying-Qing Wang, et al.
The Journals of Gerontology Series A (2023) Vol. 78, Iss. 8, pp. 1348-1354
Closed Access | Times Cited: 11
Predictive potential of circular walking in prodromal Parkinson's disease
M. Encarna Micó-Amigo, Idsart Kingma, Sebastian Heinzel, et al.
Journal of Parkinson s Disease (2025)
Open Access
Gait and mobility assessment in neurological conditions
Samuel Stuart, P Tait, Julia Das, et al.
Elsevier eBooks (2025), pp. 343-375
Closed Access
Deep learning models for improving Parkinson's disease management regarding disease stage, motor disability and quality of life
Helena R. Gonçalves, Pedro Vale Pinheiro, Cristiana Pinheiro, et al.
Computers in Biology and Medicine (2025) Vol. 189, pp. 109961-109961
Closed Access
Gait characteristics in people with Friedreich ataxia: daily life versus clinic measures
Hannah Casey, Vrutangkumar V. Shah, Daniel Muzyka, et al.
Frontiers in Neurology (2025) Vol. 16
Open Access
Will Health Experts Adopt a Clinical Decision Support System for Game-Based Digital Biomarkers? Investigating the Impact of Different Explanations on Perceived Ease-of-Use, Perceived Usefulness, and Trust
Yu Chen, Katrien Verbert, Kathrin Gerling, et al.
(2025), pp. 1581-1597
Closed Access
Digital gait biomarkers in Parkinson’s disease: susceptibility/risk, progression, response to exercise, and prognosis
Martina Mancini, Mitra Afshari, Quincy J. Almeida, et al.
npj Parkinson s Disease (2025) Vol. 11, Iss. 1
Open Access
Investigating the Impact of Environment and Data Aggregation by Walking Bout Duration on Parkinson’s Disease Classification Using Machine Learning
Rana Zia Ur Rehman, Yu Guan, Jian Qing Shi, et al.
Frontiers in Aging Neuroscience (2022) Vol. 14
Open Access | Times Cited: 18
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