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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:

Home detection of freezing of gait using support vector machines through a single waist-worn triaxial accelerometer
Daniel Rodríguez-Martín, Albert Samà, Carlos Pérez‐López, et al.
PLoS ONE (2017) Vol. 12, Iss. 2, pp. e0171764-e0171764
Open Access | Times Cited: 205

Showing 1-25 of 205 citing articles:

Machine learning in human movement biomechanics: Best practices, common pitfalls, and new opportunities
Eni Halilaj, Apoorva Rajagopal, Madalina Fiterau, et al.
Journal of Biomechanics (2018) Vol. 81, pp. 1-11
Open Access | Times Cited: 333
Deep learning for freezing of gait detection in Parkinson’s disease patients in their homes using a waist-worn inertial measurement unit
Julià Camps, Albert Samà, Mario Martín, et al.
Knowledge-Based Systems (2017) Vol. 139, pp. 119-131
Open Access | Times Cited: 195
Wearable sensors for Parkinson’s disease: which data are worth collecting for training symptom detection models
Luca Lonini, Andrew Dai, Nicholas Shawen, et al.
npj Digital Medicine (2018) Vol. 1, Iss. 1
Open Access | Times Cited: 173
Artificial intelligence for assisting diagnostics and assessment of Parkinson’s disease—A review
Minja Belić, Vladislava Bobić, Milica Badža Atanasijević, et al.
Clinical Neurology and Neurosurgery (2019) Vol. 184, pp. 105442-105442
Closed Access | Times Cited: 167
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
The Yin and Yang of exosome isolation methods: conventional practice, microfluidics, and commercial kits
Saeedreza Zeibi Shirejini, Fatih İnci
Biotechnology Advances (2021) Vol. 54, pp. 107814-107814
Closed Access | Times Cited: 122
Artificial intelligence in neurodegenerative diseases: A review of available tools with a focus on machine learning techniques
Alexandra-Maria Tăuƫan, Bogdan Ionescu, Emiliano Santarnecchi
Artificial Intelligence in Medicine (2021) Vol. 117, pp. 102081-102081
Closed Access | Times Cited: 105
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: 52
An update on adaptive deep brain stimulation in Parkinson's disease
Jeroen Habets, Monique Heijmans, Mark L. Kuijf, et al.
Movement Disorders (2018) Vol. 33, Iss. 12, pp. 1834-1843
Open Access | Times Cited: 142
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
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
Emerging role of extracellular vesicles in musculoskeletal diseases
Cameron Murphy, Joseph Withrow, Monte Hunter, et al.
Molecular Aspects of Medicine (2017) Vol. 60, pp. 123-128
Open Access | Times Cited: 99
Wearables for independent living in older adults: Gait and falls
Alan Godfrey
Maturitas (2017) Vol. 100, pp. 16-26
Open Access | Times Cited: 95
Deep Learning Approaches for Detecting Freezing of Gait in Parkinson’s Disease Patients through On-Body Acceleration Sensors
Luis Sigcha, Nélson Costa, Ignacio Pavón García, et al.
Sensors (2020) Vol. 20, Iss. 7, pp. 1895-1895
Open Access | Times Cited: 93
Monitoring Motor Symptoms During Activities of Daily Living in Individuals With Parkinson's Disease
Jenna E. Thorp, Peter G. Adamczyk, Heidi‐Lynn Ploeg, et al.
Frontiers in Neurology (2018) Vol. 9
Open Access | Times Cited: 89
Monitoring Parkinson’s disease symptoms during daily life: a feasibility study
Margot Heijmans, Jeroen Habets, Christian Herff, et al.
npj Parkinson s Disease (2019) Vol. 5, Iss. 1
Open Access | Times Cited: 75
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
Prediction and detection of freezing of gait in Parkinson’s disease from plantar pressure data using long short-term memory neural-networks
Gaurav Shalin, Scott Pardoel, Edward D. Lemaire, et al.
Journal of NeuroEngineering and Rehabilitation (2021) Vol. 18, Iss. 1
Open Access | Times Cited: 65
Didelphis spp. opossums and their parasites in the Americas: A One Health perspective
Marcos Antônio Bezerra‐Santos, Rafael Antonio Nascimento Ramos, Artur Kanadani Campos, et al.
Parasitology Research (2021) Vol. 120, Iss. 12, pp. 4091-4111
Open Access | Times Cited: 55
Assessing inertial measurement unit locations for freezing of gait detection and patient preference
Johanna O’Day, Marissa Lee, Kirsten Seagers, et al.
Journal of NeuroEngineering and Rehabilitation (2022) Vol. 19, Iss. 1
Open Access | Times Cited: 47
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
Overview on wearable sensors for the management of Parkinson’s disease
Caroline Moreau, Tiphaine Rouaud, David Grabli, et al.
npj Parkinson s Disease (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 37
Parkinson’s disease diagnosis using deep learning: A bibliometric analysis and literature review
Rabab Ali Abumalloh, Mehrbakhsh Nilashi, Sarminah Samad, et al.
Ageing Research Reviews (2024) Vol. 96, pp. 102285-102285
Closed Access | Times Cited: 11
Novelty Detection using Deep Normative Modeling for IMU-Based Abnormal Movement Monitoring in Parkinson’s Disease and Autism Spectrum Disorders
Nastaran Mohammadian Rad, Twan van Laarhoven, Cesare Furlanello, et al.
Sensors (2018) Vol. 18, Iss. 10, pp. 3533-3533
Open Access | Times Cited: 73
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