D.F. Lovely

583 total citations
37 papers, 413 citations indexed

About

D.F. Lovely is a scholar working on Biomedical Engineering, Cellular and Molecular Neuroscience and Cognitive Neuroscience. According to data from OpenAlex, D.F. Lovely has authored 37 papers receiving a total of 413 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Biomedical Engineering, 14 papers in Cellular and Molecular Neuroscience and 12 papers in Cognitive Neuroscience. Recurrent topics in D.F. Lovely's work include Muscle activation and electromyography studies (16 papers), Neuroscience and Neural Engineering (14 papers) and EEG and Brain-Computer Interfaces (10 papers). D.F. Lovely is often cited by papers focused on Muscle activation and electromyography studies (16 papers), Neuroscience and Neural Engineering (14 papers) and EEG and Brain-Computer Interfaces (10 papers). D.F. Lovely collaborates with scholars based in Canada, United States and Cuba. D.F. Lovely's co-authors include Kevin Englehart, Adrian D. C. Chan, B. Hudgins, Robert N. Scott, P.A. Parker, Yves Losier, Adam Wilson, Stephenie Harrison, R. Doraiswami and J. E. Ross and has published in prestigious journals such as IEEE Transactions on Biomedical Engineering, Electronics Letters and IEEE Transactions on Instrumentation and Measurement.

In The Last Decade

D.F. Lovely

35 papers receiving 386 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D.F. Lovely Canada 12 258 159 114 77 72 37 413
Marie-Françoise Lucas France 9 326 1.3× 355 2.2× 104 0.9× 73 0.9× 77 1.1× 16 584
Takashi Nakamura United Kingdom 10 189 0.7× 334 2.1× 51 0.4× 50 0.6× 93 1.3× 19 534
D. N. Tibarewala India 10 109 0.4× 330 2.1× 70 0.6× 113 1.5× 49 0.7× 40 465
Necmettin Sezgın Türkiye 10 195 0.8× 247 1.6× 62 0.5× 52 0.7× 62 0.9× 23 490
Stephen Faul Ireland 8 241 0.9× 220 1.4× 97 0.9× 15 0.2× 53 0.7× 12 493
Thapanun Sudhawiyangkul Thailand 10 87 0.3× 281 1.8× 88 0.8× 57 0.7× 52 0.7× 24 485
Yaqi Chu China 11 172 0.7× 299 1.9× 38 0.3× 119 1.5× 46 0.6× 31 460
Michael Ungstrup United Kingdom 8 100 0.4× 451 2.8× 103 0.9× 54 0.7× 62 0.9× 10 554
Anwesha Khasnobish India 12 118 0.5× 353 2.2× 85 0.7× 88 1.1× 36 0.5× 54 496
Hongmiao Zhang China 8 199 0.8× 375 2.4× 77 0.7× 87 1.1× 32 0.4× 35 568

Countries citing papers authored by D.F. Lovely

Since Specialization
Citations

This map shows the geographic impact of D.F. Lovely'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 D.F. Lovely with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D.F. Lovely more than expected).

Fields of papers citing papers by D.F. Lovely

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D.F. Lovely. 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 D.F. Lovely. The network helps show where D.F. Lovely may publish in the future.

Co-authorship network of co-authors of D.F. Lovely

This figure shows the co-authorship network connecting the top 25 collaborators of D.F. Lovely. A scholar is included among the top collaborators of D.F. Lovely 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 D.F. Lovely. D.F. Lovely is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wilson, Adam, Yves Losier, P.A. Parker, & D.F. Lovely. (2010). A bus-based smart myoelectric electrode/amplifier. 5 indexed citations
2.
Ye, Hua, D.F. Lovely, & R. Doraiswami. (2006). Factors affecting the stimulus artifact tail in surface-recorded somatosensory-evoked potentials. Medical & Biological Engineering & Computing. 44(3). 226–241. 5 indexed citations
3.
Chan, Adrian D. C., et al.. (2006). Multiexpert Automatic Speech Recognition Using Acoustic and Myoelectric Signals. IEEE Transactions on Biomedical Engineering. 53(4). 676–685. 25 indexed citations
4.
Lovely, D.F., et al.. (2004). A low-voltage current-mode instrumentation amplifier designed in a 0.18-micron CMOS technology. 1777–1780. 22 indexed citations
5.
Dupuis, J. Christian, Bruce G. Colpitts, Brent R. Petersen, D.F. Lovely, & Karl E. Butler. (2003). OPTIMIZATION OF A 3-AXIS INDUCTION MAGNETOMETER FOR AIRBORNE GEOPHYSICAL EXPLORATION. 3 indexed citations
6.
Chan, Adrian D. C., Kevin Englehart, B. Hudgins, & D.F. Lovely. (2002). Hidden Markov model classification of myoelectric signals in speech. IEEE Engineering in Medicine and Biology Magazine. 21(5). 143–146. 45 indexed citations
7.
Smith, David B. & D.F. Lovely. (2002). A neural network based approach to whitening biological noise for somatosensory evoked potential detection. 1. 803–804. 1 indexed citations
8.
Hudgins, B., et al.. (2002). Classification of raw myoelectric signals using finite impulse response neural networks. 4. 1474–1475. 1 indexed citations
9.
Ross, J. E., D.F. Lovely, & P.A. Parker. (2002). Design of a PC controlled constant current stimulator for evoked potential studies. 4. 2594–2596. 6 indexed citations
10.
Chan, Adrian D. C., Kevin Englehart, B. Hudgins, & D.F. Lovely. (2001). Myo-electric signals to augment speech recognition. Medical & Biological Engineering & Computing. 39(4). 500–504. 61 indexed citations
11.
Lorenzo‐Ginori, Juan V., et al.. (1999). Adaptive line enhancing plus modified signalaveraging for ventricular late potential detection. Electronics Letters. 35(16). 1293–1295. 4 indexed citations
12.
Chan, Adrian D. C., D.F. Lovely, & B. Hudgins. (1998). Errors associated with the use of adaptive differential pulse code modulation in the compression of isometric and dynamic myo-electric signals. Medical & Biological Engineering & Computing. 36(2). 215–219. 7 indexed citations
13.
Biden, E., et al.. (1997). An Investigation Into The Effectiveness Of Fitting Powered Upper Limb Prostheses: "The UNB Experience". DukeSpace (Duke University). 2 indexed citations
14.
Lovely, D.F., et al.. (1995). Real-time compression of myoelectric data utilising adaptive differential pulse code modulation. Medical & Biological Engineering & Computing. 33(5). 629–635. 27 indexed citations
15.
Harrison, Stephenie & D.F. Lovely. (1995). Identification of noise sources in surface recording of spinal somatosensory evoked potentials. Medical & Biological Engineering & Computing. 33(3). 299–305. 12 indexed citations
16.
Tremblay, Mark S., et al.. (1994). Modifications to Hydra-Gym Equipment Provide for Clinically Useful Strength Measurements. Journal of Orthopaedic and Sports Physical Therapy. 19(4). 205–211. 6 indexed citations
17.
Scott, Robert N., et al.. (1990). Operator performance in myoelectric control of a multifunction prosthesis stimulator. The Journal of Rehabilitation Research and Development. 27(1). 9–9. 4 indexed citations
18.
Lovely, D.F., et al.. (1988). Computer aided myoelectric training. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 12. 1560–1561 vol.4. 1 indexed citations
19.
Lovely, D.F., et al.. (1987). A biphasic pulse burst generator for afferent nerve stimulation. Medical & Biological Engineering & Computing. 25(1). 77–80. 3 indexed citations
20.
Lovely, D.F., et al.. (1986). Epoxy moulding system for the encapsulation of microelectronic devices suitable for implantation. Medical & Biological Engineering & Computing. 24(2). 206–208. 3 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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