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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:

Improved Kinect sensor based motion capturing system for gait assessment
Björn Müller, Winfried Ilg, Martin A. Giese, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2017)
Open Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

Wearable thermoelectric generator to harvest body heat for powering a miniaturized accelerometer
Yancheng Wang, Yaoguang Shi, Deqing Mei, et al.
Applied Energy (2018) Vol. 215, pp. 690-698
Closed Access | Times Cited: 243
The Role of Movement Analysis in Diagnosing and Monitoring Neurodegenerative Conditions: Insights from Gait and Postural Control
Christopher Buckley, Lisa Alcock, Ríona Mc Ardle, et al.
Brain Sciences (2019) Vol. 9, Iss. 2, pp. 34-34
Open Access | Times Cited: 159
Towards Inertial Sensor Based Mobile Gait Analysis: Event-Detection and Spatio-Temporal Parameters
Wolfgang Teufl, Michael Lorenz, Markus Miezal, et al.
Sensors (2018) Vol. 19, Iss. 1, pp. 38-38
Open Access | Times Cited: 109
Computation of Gait Parameters in Post Stroke and Parkinson’s Disease: A Comparative Study Using RGB-D Sensors and Optoelectronic Systems
Verônica Cimolin, Luca Vismara, Claudia Ferraris, et al.
Sensors (2022) Vol. 22, Iss. 3, pp. 824-824
Open Access | Times Cited: 38
Accuracy, Validity, and Reliability of Markerless Camera-Based 3D Motion Capture Systems versus Marker-Based 3D Motion Capture Systems in Gait Analysis: A Systematic Review and Meta-Analysis
Sofia Scataglini, Eveline Abts, Cas Van Bocxlaer, et al.
Sensors (2024) Vol. 24, Iss. 11, pp. 3686-3686
Open Access | Times Cited: 12
Feasibility of Home-Based Automated Assessment of Postural Instability and Lower Limb Impairments in Parkinson’s Disease
Claudia Ferraris, Roberto Nerino, Antonio Chimienti, et al.
Sensors (2019) Vol. 19, Iss. 5, pp. 1129-1129
Open Access | Times Cited: 43
Monitoring of Gait Parameters in Post-Stroke Individuals: A Feasibility Study Using RGB-D Sensors
Claudia Ferraris, Verônica Cimolin, Luca Vismara, et al.
Sensors (2021) Vol. 21, Iss. 17, pp. 5945-5945
Open Access | Times Cited: 33
Clinical Whole-Body Gait Characterization Using a Single RGB-D Sensor
Lukas Boborzi, Johannes Bertram, Roman Schniepp, et al.
Sensors (2025) Vol. 25, Iss. 2, pp. 333-333
Open Access
Early Postoperative Gait Analysis in Elderly Patients Following Hip Fracture Surgery
Gereon Anton Hecht, Rachel Senden, Rik Marcellis, et al.
Sensors (2025) Vol. 25, Iss. 6, pp. 1888-1888
Open Access
Beneficial Effect of Foot Plantar Stimulation in Gait Parameters in Individuals with Parkinson’s Disease
Lorenzo Brognara, Emmanuel Navarro‐Flores, Lorenzo Iachemet, et al.
Brain Sciences (2020) Vol. 10, Iss. 2, pp. 69-69
Open Access | Times Cited: 36
Fusion of Multiple Lidars and Inertial Sensors for the Real-Time Pose Tracking of Human Motion
Ashok Kumar Patil, Adithya Balasubramanyam, Jaeyeong Ryu, et al.
Sensors (2020) Vol. 20, Iss. 18, pp. 5342-5342
Open Access | Times Cited: 35
Quantifying Spatiotemporal Gait Parameters with HoloLens in Healthy Adults and People with Parkinson’s Disease: Test-Retest Reliability, Concurrent Validity, and Face Validity
Daphne J. Geerse, Bert Coolen, Melvyn Roerdink
Sensors (2020) Vol. 20, Iss. 11, pp. 3216-3216
Open Access | Times Cited: 32
WM–STGCN: A Novel Spatiotemporal Modeling Method for Parkinsonian Gait Recognition
Jieming Zhang, Jongmin Lim, Moon-Hyun Kim, et al.
Sensors (2023) Vol. 23, Iss. 10, pp. 4980-4980
Open Access | Times Cited: 11
An Integrated Multi-Sensor Approach for the Remote Monitoring of Parkinson’s Disease
Giovanni Albani, Claudia Ferraris, Roberto Nerino, et al.
Sensors (2019) Vol. 19, Iss. 21, pp. 4764-4764
Open Access | Times Cited: 32
Monitoring and Assessment of Rehabilitation Progress on Range of Motion After Total Knee Replacement by Sensor-Based System
Yo‐Ping Huang, Yuyu Liu, Wei‐Hsiu Hsu, et al.
Sensors (2020) Vol. 20, Iss. 6, pp. 1703-1703
Open Access | Times Cited: 31
Precision Balance Assessment in Parkinson’s Disease: Utilizing Vision-Based 3D Pose Tracking for Pull Test Analysis
Nina Ellrich, Kasimir Niermeyer, Daniela Peto, et al.
Sensors (2024) Vol. 24, Iss. 11, pp. 3673-3673
Open Access | Times Cited: 3
3D Analysis of Upper Limbs Motion during Rehabilitation Exercises Using the KinectTM Sensor: Development, Laboratory Validation and Clinical Application
Bruno Bonnechère, Victor Sholukha, Luboš Omelina, et al.
Sensors (2018) Vol. 18, Iss. 7, pp. 2216-2216
Open Access | Times Cited: 30
A Comparative Study of Markerless Systems Based on Color-Depth Cameras, Polymer Optical Fiber Curvature Sensors, and Inertial Measurement Units: Towards Increasing the Accuracy in Joint Angle Estimation
Nicolas Jacobo Valencia Jiménez, Arnaldo Leal‐Junior, Letícia Avellar, et al.
Electronics (2019) Vol. 8, Iss. 2, pp. 173-173
Open Access | Times Cited: 24
Measurement Accuracy of the HTC VIVE Tracker 3.0 Compared to Vicon System for Generating Valid Positional Feedback in Virtual Reality
Sebastian Merker, Stefan Pastel, Dan Bürger, et al.
Sensors (2023) Vol. 23, Iss. 17, pp. 7371-7371
Open Access | Times Cited: 7
A Transferable Lidar-Based Method to Conduct Contactless Assessments of Gait Parameters in Diverse Home-like Environments
Michael Single, Lena C. Bruhin, Aaron Colombo, et al.
Sensors (2024) Vol. 24, Iss. 4, pp. 1172-1172
Open Access | Times Cited: 2
Towards an articulated avatar in VR: Improving body and hand tracking using only depth cameras
Yuanjie Wu, Yu Wang, Sungchul Jung, et al.
Entertainment Computing (2019) Vol. 31, pp. 100303-100303
Closed Access | Times Cited: 20
Validation of Marker-Less System for the Assessment of Upper Joints Reaction Forces in Exoskeleton Users
Simone Pasinetti, Cristina Nuzzi, Nicola Covre, et al.
Sensors (2020) Vol. 20, Iss. 14, pp. 3899-3899
Open Access | Times Cited: 17
Non-Invasive Assessment of Back Surface Topography: Technologies, Techniques and Clinical Utility
Bhavna Mehta, Nachiappan Chockalingam, Thomas Shannon, et al.
Sensors (2023) Vol. 23, Iss. 20, pp. 8485-8485
Open Access | Times Cited: 5
Gait Biomechanical Parameters Related to Falls in the Elderly: A Systematic Review
Jullyanne Silva, Tiago Atalaia, João Abrantes, et al.
Biomechanics (2024) Vol. 4, Iss. 1, pp. 165-218
Open Access | Times Cited: 1
Quaternion-Based Local Frame Alignment between an Inertial Measurement Unit and a Motion Capture System
Jung Keun Lee, Woo Chang Jung
Sensors (2018) Vol. 18, Iss. 11, pp. 4003-4003
Open Access | Times Cited: 14
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