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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:

Feature selection for elderly faller classification based on wearable sensors
Jennifer Howcroft, Jonathan Kofman, Edward D. Lemaire
Journal of NeuroEngineering and Rehabilitation (2017) Vol. 14, Iss. 1
Open Access | Times Cited: 64

Showing 1-25 of 64 citing articles:

Machine learning and computation-enabled intelligent sensor design
Zachary S. Ballard, Calvin Brown, Asad M. Madni, et al.
Nature Machine Intelligence (2021) Vol. 3, Iss. 7, pp. 556-565
Open Access | Times Cited: 159
Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review
Kathrin Seibert, Dominik Domhoff, Dominik Bruch, et al.
Journal of Medical Internet Research (2021) Vol. 23, Iss. 11, pp. e26522-e26522
Open Access | Times Cited: 139
A comprehensive review of elderly fall detection using wireless communication and artificial intelligence techniques
Sadik Kamel Gharghan, Huda Ali Hashim
Measurement (2024) Vol. 226, pp. 114186-114186
Closed Access | Times Cited: 15
Fall detection and fall risk assessment in older person using wearable sensors: A systematic review
Patrícia Bet, Paula Costa Castro, Moacir Antonelli Ponti
International Journal of Medical Informatics (2019) Vol. 130, pp. 103946-103946
Closed Access | Times Cited: 139
Type and Location of Wearable Sensors for Monitoring Falls during Static and Dynamic Tasks in Healthy Elderly: A Review
Rosaria Rucco, Antonietta Sorriso, Marianna Liparoti, et al.
Sensors (2018) Vol. 18, Iss. 5, pp. 1613-1613
Open Access | Times Cited: 108
Machine Learning-Enabled Internet of Things (IoT): Data, Applications, and Industry Perspective
Jamal Bzai, Furqan Alam, Arwa Dhafer, et al.
Electronics (2022) Vol. 11, Iss. 17, pp. 2676-2676
Open Access | Times Cited: 54
Application of Wearable Inertial Sensors and A New Test Battery for Distinguishing Retrospective Fallers from Non-fallers among Community-dwelling Older People
Hai Qiu, Rana Zia Ur Rehman, Xiaoqun Yu, et al.
Scientific Reports (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 70
Fall Risk Prediction in Multiple Sclerosis Using Postural Sway Measures: A Machine Learning Approach
Ruopeng Sun, Katherine L. Hsieh, Jacob J. Sosnoff
Scientific Reports (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 70
Wearables and Deep Learning Classify Fall Risk From Gait in Multiple Sclerosis
Brett M. Meyer, Lindsey J. Tulipani, Reed D. Gurchiek, et al.
IEEE Journal of Biomedical and Health Informatics (2020) Vol. 25, Iss. 5, pp. 1824-1831
Open Access | Times Cited: 68
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
Accelerometer-based predictive models of fall risk in older women: a pilot study
Andrew Hua, Zachary Stokes Quicksall, Chongzhi Di, et al.
npj Digital Medicine (2018) Vol. 1, Iss. 1
Open Access | Times Cited: 57
Using a Motion Sensor to Categorize Nonspecific Low Back Pain Patients: A Machine Learning Approach
Masoud Abdollahi, Sajad Ashouri, Mohsen Abedi, et al.
Sensors (2020) Vol. 20, Iss. 12, pp. 3600-3600
Open Access | Times Cited: 49
Cancer Classification with a Cost-Sensitive Naive Bayes Stacking Ensemble
Yueling Xiong, Mingquan Ye, Changrong Wu
Computational and Mathematical Methods in Medicine (2021) Vol. 2021, pp. 1-12
Open Access | Times Cited: 35
A systematic review of artificial neural network techniques for analysis of foot plantar pressure
Chongguang Wang, Kerrie Evans, Dean S. Hartley, et al.
Journal of Applied Biomedicine (2024) Vol. 44, Iss. 1, pp. 197-208
Open Access | Times Cited: 4
Revisiting sensor-based intelligent fall risk assessment for older people: A systematic review
Xiaoqun Yu, Yuqing Cai, Rong Yang, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 144, pp. 110176-110176
Closed Access
Psychological and physiological computing based on multi-dimensional foot information
Shengyang Li, Huilin Yao, Ruotian Peng, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 5
Open Access
Technology Utilization in Fall Prevention
Mooyeon Oh‐Park, Thao Doan, Carolin Dohle, et al.
American Journal of Physical Medicine & Rehabilitation (2020) Vol. 100, Iss. 1, pp. 92-99
Closed Access | Times Cited: 36
Development and validation of a robotic multifactorial fall-risk predictive model: A one-year prospective study in community-dwelling older adults
Alberto Cella, Alice De Luca, Valentina Squeri, et al.
PLoS ONE (2020) Vol. 15, Iss. 6, pp. e0234904-e0234904
Open Access | Times Cited: 35
A Novel Approach for Activity Recognition with Down-Sampling 1D Local Binary Pattern Features
Fatma KUNCAN, Yılmaz Kaya, Melih Kuncan
Advances in Electrical and Computer Engineering (2019) Vol. 19, Iss. 1, pp. 35-44
Open Access | Times Cited: 32
Enabling Older Adults’ Health Self-Management through Self-Report and Visualization—A Systematic Literature Review
Gabriela Cajamarca, Valeria Herskovic, Pedro O. Rossel
Sensors (2020) Vol. 20, Iss. 15, pp. 4348-4348
Open Access | Times Cited: 27
Empirical Study on Human Movement Classification Using Insole Footwear Sensor System and Machine Learning
Wolfe Anderson, Zachary Choffin, Nathan Jeong, et al.
Sensors (2022) Vol. 22, Iss. 7, pp. 2743-2743
Open Access | Times Cited: 17
Prospective elderly fall prediction by older-adult fall-risk modeling with feature selection
Jennifer Howcroft, Edward D. Lemaire, Jonathan Kofman
Biomedical Signal Processing and Control (2018) Vol. 43, pp. 320-328
Closed Access | Times Cited: 29
Prediction of Freezing of Gait in Parkinson’s Disease from Foot Plantar-Pressure Arrays using a Convolutional Neural Network
Gaurav Shalin, Scott Pardoel, Julie Nantel, et al.
(2020), pp. 244-247
Closed Access | Times Cited: 26
Classifying sitting, standing, and walking using plantar force data
Kohle Merry, Evan Macdonald, Megan MacPherson, et al.
Medical & Biological Engineering & Computing (2021) Vol. 59, Iss. 1, pp. 257-270
Closed Access | Times Cited: 21
Prediction of Freezing of Gait in Parkinson's Disease Using Unilateral and Bilateral Plantar-Pressure Data
Scott Pardoel, Julie Nantel, Jonathan Kofman, et al.
Frontiers in Neurology (2022) Vol. 13
Open Access | Times Cited: 14
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