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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:

Gait metrics analysis utilizing single-point inertial measurement units: a systematic review
Ralph J. Mobbs, Jordan Perring, Suresh Mahendra Raj, et al.
mHealth (2021) Vol. 8, pp. 9-9
Open Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

Machine Learning Approach to Support the Detection of Parkinson’s Disease in IMU-Based Gait Analysis
Dante Trabassi, Mariano Serrao, Tiwana Varrecchia, et al.
Sensors (2022) Vol. 22, Iss. 10, pp. 3700-3700
Open Access | Times Cited: 69
Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium
M. Encarna Micó-Amigo, Tecla Bonci, Anisoara Paraschiv-Ionescu, et al.
Journal of NeuroEngineering and Rehabilitation (2023) Vol. 20, Iss. 1
Open Access | Times Cited: 53
A multi-sensor wearable system for the assessment of diseased gait in real-world conditions
Francesca Salis, Stefano Bertuletti, Tecla Bonci, et al.
Frontiers in Bioengineering and Biotechnology (2023) Vol. 11
Open Access | Times Cited: 31
A wearable sensor and machine learning estimate step length in older adults and patients with neurological disorders
Assaf Zadka, Neta Rabin, Eran Gazit, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 7
Algorithms for gait: technical and clinical validity
Lisa Alcock, M. Encarna Micó-Amigo, Tecla Bonci, et al.
Elsevier eBooks (2025), pp. 277-321
Closed Access
Smooth Moves: Comparing Log Dimensionless Jerk Metrics from Body Center of Mass Trajectory and Wearable Sensor Acceleration During Walking
Paolo Brasiliano, Gaspare Pavei, Elena Bergamini
Sensors (2025) Vol. 25, Iss. 4, pp. 1233-1233
Open Access
Use of Smartphone-Based Experimental Data for the Calibration of Biodynamic Spring-Mass-Damper (SMD) Pedestrian Models
Chiara Bedon, Martina Sciomenta, Alessandro Mazelli
Sensors (2025) Vol. 25, Iss. 5, pp. 1387-1387
Open Access
Algorithm for Gait Parameters Estimation Based on Heel-Mounted Inertial Sensors
Baiqing Luo, Z Y Wang, Dongmei Wang, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 15, pp. 24723-24736
Closed Access | Times Cited: 3
Evaluation of Smartphone Technology on Spatiotemporal Gait in Older and Diseased Adult Populations
Coby Contreras, Ethan C. Stanley, Chanc Deschamps-Prescott, et al.
Sensors (2024) Vol. 24, Iss. 17, pp. 5839-5839
Open Access | Times Cited: 3
Investigating walking speed variability of young adults in the real world
Loubna Baroudi, Xinghui Yan, Mark Newman, et al.
Gait & Posture (2022) Vol. 98, pp. 69-77
Closed Access | Times Cited: 15
Stepping beyond Counts in Recovery of Total Knee Arthroplasty: A Prospective Study on Passively Collected Gait Metrics
Camdon Fary, Jason M. Cholewa, Scott Abshagen, et al.
Sensors (2023) Vol. 23, Iss. 12, pp. 5588-5588
Open Access | Times Cited: 8
Development of a Gait Feature–Based Model for Classifying Cognitive Disorders Using a Single Wearable Inertial Sensor
Jeongbin Park, Hyang Jun Lee, Ji Sun Park, et al.
Neurology (2023) Vol. 101, Iss. 1
Open Access | Times Cited: 7
Employing machine learning to enhance fracture recovery insights through gait analysis
Mostafa Rezapour, Rachel B. Seymour, Stephen H. Sims, et al.
Journal of Orthopaedic Research® (2024) Vol. 42, Iss. 8, pp. 1748-1761
Open Access | Times Cited: 2
Examining the validity of smart glasses in measuring spatiotemporal parameters of gait among people with Parkinson’s disease
James R. Fang, Rajesh Pahwa, Kelly E. Lyons, et al.
Gait & Posture (2024) Vol. 113, pp. 139-144
Open Access | Times Cited: 2
Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium
M. Encarna Micó-Amigo, Tecla Bonci, Anisoara Paraschiv-Ionescu, et al.
Research Square (Research Square) (2022)
Open Access | Times Cited: 11
Foot characteristics of the daily-life gait in postmenopausal females with distal radius fractures: a cross-sectional study
Akiko Yamamoto, Koji Fujita, Eriku Yamada, et al.
BMC Musculoskeletal Disorders (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 5
Inertial measurement unit sensor-based gait analysis in adults and older adults: A cross-sectional study
Dong Hyun Yoon, Jeonghyun Kim, Kyuwon Lee, et al.
Gait & Posture (2023) Vol. 107, pp. 212-217
Closed Access | Times Cited: 5
Using In-Shoe Inertial Measurement Unit Sensors to Understand Daily-Life Gait Characteristics in Patients With Distal Radius Fractures During 6 Months of Recovery: Cross-Sectional Study
Akiko Yamamoto, Eriku Yamada, Takuya Ibara, et al.
JMIR mhealth and uhealth (2024) Vol. 12, pp. e55178-e55178
Open Access | Times Cited: 1
Complexities and challenges of translating intervention success to real world gait in people with Parkinson’s disease
Charlotte Lang, Jaap H. van Dieën, Matthew A. Brodie, et al.
Frontiers in Neurology (2024) Vol. 15
Open Access | Times Cited: 1
Beyond timing and step counting in 360° turning-in-place assessment: a scoping review
Slávka Neťuková, Lucie Horáková, Zoltán Szabó, et al.
BioMedical Engineering OnLine (2024) Vol. 23, Iss. 1
Open Access | Times Cited: 1
The Potential Role of Wearable Inertial Sensors in Laboring Women with Walking Epidural Analgesia
Mikhail Dziadzko, Adrien Péneaud, Lionel Bouvet, et al.
Sensors (2024) Vol. 24, Iss. 6, pp. 1904-1904
Open Access | Times Cited: 1
Exploring unsupervised feature extraction of IMU-based gait data in stroke rehabilitation using a variational autoencoder
Richard A. W. Felius, Michiel Punt, Marieke Geerars, et al.
PLoS ONE (2024) Vol. 19, Iss. 10, pp. e0304558-e0304558
Open Access | Times Cited: 1
OA-Pain-Sense: Machine Learning Prediction of Hip and Knee Osteoarthritis Pain from IMU Data
Wafaa Salem Almuhammadi, Emmanuel Agu, Jean A. King, et al.
Informatics (2022) Vol. 9, Iss. 4, pp. 97-97
Open Access | Times Cited: 6
A Single-Sensor Approach to Quantify Gait in Patients with Hereditary Spastic Paraplegia
Linda Van Gelder, Tecla Bonci, Ellen Buckley, et al.
Sensors (2023) Vol. 23, Iss. 14, pp. 6563-6563
Open Access | Times Cited: 3
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