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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:

Evaluation of the Tinetti score and fall risk assessment via accelerometry-based movement analysis
Massimo W. Rivolta, Md Aktaruzzaman, Giovanna Rizzo, et al.
Artificial Intelligence in Medicine (2018) Vol. 95, pp. 38-47
Closed Access | Times Cited: 58

Showing 1-25 of 58 citing articles:

Wearable Sensor Systems for Fall Risk Assessment: A Review
Sophini Subramaniam, Abu Ilius Faisal, M. Jamal Deen
Frontiers in Digital Health (2022) Vol. 4
Open Access | Times Cited: 71
Use of Wearable Sensor Technology in Gait, Balance, and Range of Motion Analysis
Steven Díaz, J. Stephenson, Miguel A. Labrador
Applied Sciences (2019) Vol. 10, Iss. 1, pp. 234-234
Open Access | Times Cited: 103
The Effect of Exercise Intervention on Reducing the Fall Risk in Older Adults: A Meta-Analysis of Randomized Controlled Trials
Mingyu Sun, Leizi Min, Na Xu, et al.
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 23, pp. 12562-12562
Open Access | Times Cited: 58
Fall Risk Assessment Using Wearable Sensors: A Narrative Review
R. Ferreira, Nuno Ferrete Ribeiro, Cristina P. Santos
Sensors (2022) Vol. 22, Iss. 3, pp. 984-984
Open Access | Times Cited: 30
Sensor-based fall risk assessment in older adults with or without cognitive impairment: a systematic review
Jelena Bezold, Janina Krell‐Roesch, Tobias Eckert, et al.
European Review of Aging and Physical Activity (2021) Vol. 18, Iss. 1
Open Access | Times Cited: 32
Effectiveness of a Sustainable Training Program Combining Supervised Outdoor Exercise with Telecoaching on Physical Performance in Elderly People
Ignazio Leale, Valerio Giustino, Jessica Brusa, et al.
Sustainability (2024) Vol. 16, Iss. 8, pp. 3254-3254
Open Access | Times Cited: 5
Inertial Sensor Reliability and Validity for Static and Dynamic Balance in Healthy Adults: A Systematic Review
Nicky Baker, Claire Gough, Susan Gordon
Sensors (2021) Vol. 21, Iss. 15, pp. 5167-5167
Open Access | Times Cited: 31
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
Developing smart buildings to reduce indoor risks for safety and health of the elderly: A systematic and bibliometric analysis
Fan Zhang, Albert P.C. Chan, Dezhi Li
Safety Science (2023) Vol. 168, pp. 106310-106310
Closed Access | Times Cited: 11
Marker-Based Movement Analysis of Human Body Parts in Therapeutic Procedure
Muhammad Hassan Khan, Martin Zöller, Muhammad Shahid Farid, et al.
Sensors (2020) Vol. 20, Iss. 11, pp. 3312-3312
Open Access | Times Cited: 28
On the feature extraction process in machine learning. An experimental study about guided versus non-guided process in falling detection systems
Elena Escobar-Linero, Francisco Luna-Perejón, Luis Muñoz-Saavedra, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 114, pp. 105170-105170
Open Access | Times Cited: 13
Pay attention: you can fall! The Mini-BESTest scale and the turning duration of the TUG test provide valid balance measures in neurological patients: a prospective study with falls as the balance criterion
Antonio Caronni, Michela Picardi, Stefano Scarano, et al.
Frontiers in Neurology (2023) Vol. 14
Open Access | Times Cited: 7
Evaluation of Hemiplegic Gait Based on Plantar Pressure and Inertial Sensors
Zewei Pan, Huigang Gao, Yan Chen, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 11, pp. 12008-12017
Closed Access | Times Cited: 6
Electromyography and dynamometry in the prediction of risk of falls in the elderly using machine learning tools
Daniele Alves da Silva, Nayra Ferreira Lima Castelo Branco, Laiana Sepúlveda de Andrade Mesquita, et al.
Biomedical Signal Processing and Control (2023) Vol. 88, pp. 105635-105635
Closed Access | Times Cited: 6
Foreseeing future falls with accelerometer features in active community-dwelling older persons with no recent history of falls
Patrícia Bet, Paula Costa Castro, Moacir Antonelli Ponti
Experimental Gerontology (2020) Vol. 143, pp. 111139-111139
Closed Access | Times Cited: 16
Use of Standardized and Non-Standardized Tools for Measuring the Risk of Falls and Independence in Clinical Practice
Jan Neugebauer, Valérie Tóthová, J Dolezalová
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 6, pp. 3226-3226
Open Access | Times Cited: 13
Evaluation of the health level of the elderly: patient care team considerations
Maria Clara Duarte Monteiro, María Manuela Martins, Soraia Dornelles Schoeller
Revista Brasileira de Enfermagem (2021) Vol. 75, Iss. 1
Open Access | Times Cited: 12
Leveraging feature selection for enhanced fall risk prediction in elderly using gait analysis
Sabri Altunkaya
Medical & Biological Engineering & Computing (2024) Vol. 62, Iss. 12, pp. 3887-3897
Open Access | Times Cited: 1
Improved screening of fall risk using free-living based accelerometer data
Daniel Kelly, Joan Condell, James B. Gillespie, et al.
Journal of Biomedical Informatics (2022) Vol. 131, pp. 104116-104116
Open Access | Times Cited: 6
A machine learning approach to identify fall risk for older adults
Prithwi Raj Chakraborty, Golam Sorwar
Smart Health (2022) Vol. 26, pp. 100303-100303
Closed Access | Times Cited: 6
Accelerometry applications and methods to assess standing balance in older adults and mobility-limited patient populations: a narrative review
Kayla Bohlke, Mark S. Redfern, Andrea Rosso, et al.
Aging Clinical and Experimental Research (2023) Vol. 35, Iss. 10, pp. 1991-2007
Closed Access | Times Cited: 3
Empirical Mode Decomposition-Derived Entropy Features Are Beneficial to Distinguish Elderly People with a Falling History on a Force Plate Signal
Li‐Wei Chou, Kang-Ming Chang, Yi-Chun Wei, et al.
Entropy (2021) Vol. 23, Iss. 4, pp. 472-472
Open Access | Times Cited: 8
Automatic Recognition and Analysis of Balance Activity in Community-Dwelling Older Adults: Algorithm Validation
Yu‐Cheng Hsu, Hailiang Wang, Yang Zhao, et al.
Journal of Medical Internet Research (2021) Vol. 23, Iss. 12, pp. e30135-e30135
Open Access | Times Cited: 7
Fall risk assessment through a synergistic multi-source DNN learning model
Olga Andreeva, Wei Ding, Suzanne G. Leveille, et al.
Artificial Intelligence in Medicine (2022) Vol. 127, pp. 102280-102280
Open Access | Times Cited: 5
Barriers to Artificial Intelligence Adoption in Healthcare Management: A Systematic Review
Mir Mohammed Assadullah
SSRN Electronic Journal (2019)
Closed Access | Times Cited: 7
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