Daniel Devaprakash

591 total citations
18 papers, 378 citations indexed

About

Daniel Devaprakash is a scholar working on Biomedical Engineering, Orthopedics and Sports Medicine and Surgery. According to data from OpenAlex, Daniel Devaprakash has authored 18 papers receiving a total of 378 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Biomedical Engineering, 8 papers in Orthopedics and Sports Medicine and 3 papers in Surgery. Recurrent topics in Daniel Devaprakash's work include Muscle activation and electromyography studies (13 papers), Sports injuries and prevention (7 papers) and Prosthetics and Rehabilitation Robotics (5 papers). Daniel Devaprakash is often cited by papers focused on Muscle activation and electromyography studies (13 papers), Sports injuries and prevention (7 papers) and Prosthetics and Rehabilitation Robotics (5 papers). Daniel Devaprakash collaborates with scholars based in Australia, United States and New Zealand. Daniel Devaprakash's co-authors include Claudio Pizzolato, David G. Lloyd, Laura E. Diamond, Christopher P. Carty, Mohammad Fazle Rabbi, Rod Barrett, Bryce A. Killen, David J. Saxby, Jacqueline Alderson and Giorgio Davico and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of Applied Physiology.

In The Last Decade

Daniel Devaprakash

18 papers receiving 371 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel Devaprakash Australia 11 281 137 97 80 33 18 378
Beat Goepfert Switzerland 8 334 1.2× 331 2.4× 54 0.6× 129 1.6× 25 0.8× 10 505
Giorgio Davico Italy 10 193 0.7× 64 0.5× 38 0.4× 81 1.0× 45 1.4× 26 291
Margit Gfoehler Austria 10 244 0.9× 54 0.4× 49 0.5× 54 0.7× 48 1.5× 26 327
Ryosuke Ando Japan 11 265 0.9× 224 1.6× 74 0.8× 50 0.6× 19 0.6× 32 409
Farhad Tabatabai Ghomshe Iran 12 238 0.8× 61 0.4× 35 0.4× 61 0.8× 99 3.0× 42 359
Valdeci Carlos Dioní­sio Brazil 11 210 0.7× 139 1.0× 33 0.3× 103 1.3× 47 1.4× 49 396
Matteo Scorcelletti Germany 4 186 0.7× 140 1.0× 79 0.8× 95 1.2× 14 0.4× 6 367
Hoa Hoang Australia 10 292 1.0× 68 0.5× 40 0.4× 145 1.8× 104 3.2× 15 380
Brent J. Raiteri Australia 14 435 1.5× 435 3.2× 67 0.7× 75 0.9× 31 0.9× 30 616
Momoko Yamagata Japan 13 197 0.7× 108 0.8× 87 0.9× 95 1.2× 63 1.9× 42 408

Countries citing papers authored by Daniel Devaprakash

Since Specialization
Citations

This map shows the geographic impact of Daniel Devaprakash's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Devaprakash with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Devaprakash more than expected).

Fields of papers citing papers by Daniel Devaprakash

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Devaprakash. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Devaprakash. The network helps show where Daniel Devaprakash may publish in the future.

Co-authorship network of co-authors of Daniel Devaprakash

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Devaprakash. A scholar is included among the top collaborators of Daniel Devaprakash based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Devaprakash. Daniel Devaprakash is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Pizzolato, Claudio, et al.. (2024). Hip contact forces can be predicted with a neural network using only synthesised key points and electromyography in people with hip osteoarthritis. Osteoarthritis and Cartilage. 32(6). 730–739. 4 indexed citations
2.
Devaprakash, Daniel, et al.. (2024). Prediction of Achilles Tendon Force During Common Motor Tasks From Markerless Video. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 32. 2070–2077. 3 indexed citations
3.
Devaprakash, Daniel, et al.. (2024). Inclusion of a skeletal model partly improves the reliability of lower limb joint angles derived from a markerless depth camera. Journal of Biomechanics. 170. 112160–112160. 6 indexed citations
4.
Devaprakash, Daniel, et al.. (2023). Predicting Free Achilles Tendon Strain From Motion Capture Data Using Artificial Intelligence. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31. 3086–3094. 3 indexed citations
5.
Worsey, Matthew, et al.. (2023). Washable Garment-Embedded Textile Electrodes Can Measure High-Quality Surface EMG Data Across a Range of Motor Tasks. IEEE Sensors Journal. 23(17). 20150–20158. 10 indexed citations
6.
Davico, Giorgio, David G. Lloyd, Christopher P. Carty, et al.. (2022). Multi-level personalization of neuromusculoskeletal models to estimate physiologically plausible knee joint contact forces in children. Biomechanics and Modeling in Mechanobiology. 21(6). 1873–1886. 23 indexed citations
7.
Devaprakash, Daniel, David Graham, Rod Barrett, et al.. (2022). Free Achilles tendon strain during selected rehabilitation, locomotor, jumping, and landing tasks. Journal of Applied Physiology. 132(4). 956–965. 16 indexed citations
8.
Saxby, David J., et al.. (2022). Personalized digital humans for rehabilitation and assistive devices. Journal of science and medicine in sport. 25. S5–S6. 2 indexed citations
9.
Diamond, Laura E., Daniel Devaprakash, Melanie L. Plinsinga, et al.. (2021). Feasibility of personalised hip load modification using real-time biofeedback in hip osteoarthritis: A pilot study. SHILAP Revista de lepidopterología. 4(1). 100230–100230. 12 indexed citations
10.
Diamond, Laura E., Claudio Pizzolato, Bryce A. Killen, et al.. (2020). Development and validation of statistical shape models of the primary functional bone segments of the foot. PeerJ. 8. e8397–e8397. 34 indexed citations
11.
Devaprakash, Daniel, Steven J. Obst, David G. Lloyd, et al.. (2020). The Free Achilles Tendon Is Shorter, Stiffer, Has Larger Cross-Sectional Area and Longer T2* Relaxation Time in Trained Middle-Distance Runners Compared to Healthy Controls. Frontiers in Physiology. 11. 965–965. 17 indexed citations
12.
Rabbi, Mohammad Fazle, Claudio Pizzolato, David G. Lloyd, et al.. (2020). Non-negative matrix factorisation is the most appropriate method for extraction of muscle synergies in walking and running. Scientific Reports. 10(1). 8266–8266. 101 indexed citations
13.
Pizzolato, Claudio, Vickie Shim, David G. Lloyd, et al.. (2020). Targeted Achilles Tendon Training and Rehabilitation Using Personalized and Real-Time Multiscale Models of the Neuromusculoskeletal System. Frontiers in Bioengineering and Biotechnology. 8. 878–878. 32 indexed citations
14.
Saxby, David J., Bryce A. Killen, Claudio Pizzolato, et al.. (2020). Machine learning methods to support personalized neuromusculoskeletal modelling. Biomechanics and Modeling in Mechanobiology. 19(4). 1169–1185. 58 indexed citations
15.
Devaprakash, Daniel, David G. Lloyd, Rod Barrett, et al.. (2019). Magnetic Resonance Imaging and Freehand 3-D Ultrasound Provide Similar Estimates of Free Achilles Tendon Shape and 3-D Geometry. Ultrasound in Medicine & Biology. 45(11). 2898–2905. 18 indexed citations
16.
Weir, Gillian, Jacqueline Alderson, Bruce Elliott, et al.. (2019). A 2-yr Biomechanically Informed ACL Injury Prevention Training Intervention in Female Field Hockey Players. Translational Journal of the American College of Sports Medicine. 4(19). 206–214. 7 indexed citations
17.
McDonald, Kirsty A., Daniel Devaprakash, & Jonas Rubenson. (2019). Is conservation of center of mass mechanics a priority in human walking? Insights from leg-length asymmetry experiments. Journal of Experimental Biology. 222(Pt 9). 5 indexed citations
18.
Devaprakash, Daniel, Gillian Weir, James J. Dunne, Jacqueline Alderson, & Cyril J. Donnelly. (2016). The influence of digital filter type, amplitude normalisation method, and co-contraction algorithm on clinically relevant surface electromyography data during clinical movement assessments. Journal of Electromyography and Kinesiology. 31. 126–135. 27 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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