World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
36
Citations
12066
World Ranking
8545
National Ranking
343

Philip A. Parker publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Philip A. Parker sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 117 publications — 14th percentile

14% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Philip A. Parker D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Philip A. Parker sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 36 D-Index — 13th percentile

13% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Artificial neural network

Artificial intelligence, Signal processing, Proportional myoelectric control, Signal and Artificial neural network are his primary areas of study. Much of his study explores Artificial intelligence relationship to Control system. His work is dedicated to discovering how Signal processing, Myoelectric signal are connected with Control engineering, Control, Artificial limbs and Prosthesis and other disciplines.

His Proportional myoelectric control research focuses on subjects like Upper limb, which are linked to Wrist, Biomechanics, Isometric exercise and Physical therapy. His study in Signal is interdisciplinary in nature, drawing from both Series, Time delay neural network, Hopfield network, Electromyography and Perceptron. His Artificial neural network research incorporates elements of Speech recognition, Cluster analysis and Pattern recognition.

His most cited work include:

  • A new strategy for multifunction myoelectric control (1413 citations)
  • Electromyography. Physiology, engineering and non invasive applications (852 citations)
  • A wavelet-based continuous classification scheme for multifunction myoelectric control (546 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of investigation include Signal processing, Signal, Artificial intelligence, Myoelectric signal and Electronic engineering. His Signal processing course of study focuses on Control theory and Signal-to-noise ratio and Electromyography. His work on Noise as part of general Signal research is frequently linked to Efferent, bridging the gap between disciplines.

In his study, Multilayer perceptron is inextricably linked to Pattern recognition, which falls within the broad field of Artificial intelligence. His Myoelectric signal research incorporates themes from Human physiology, Biomedical engineering, Artificial limbs and Anatomy. Philip A. Parker has included themes like Proportional myoelectric control, Speech recognition and Target acquisition in his Artificial neural network study.

He most often published in these fields:

  • Signal processing (25.61%)
  • Signal (23.17%)
  • Artificial intelligence (21.95%)

What were the highlights of his more recent work (between 2008-2014)?

  • Artificial intelligence (21.95%)
  • Artificial neural network (13.41%)
  • Proportional myoelectric control (10.98%)

In recent papers he was focusing on the following fields of study:

His main research concerns Artificial intelligence, Artificial neural network, Proportional myoelectric control, Signal and Speech recognition. His Artificial intelligence research is multidisciplinary, incorporating perspectives in State, Myoelectric signal and Pattern recognition. His Artificial neural network research includes themes of Electromyography and Target acquisition.

The Proportional myoelectric control study combines topics in areas such as Upper limb and Isometric exercise. His work in the fields of Signal, such as Signal processing, overlaps with other areas such as Efferent. His work deals with themes such as Electronic engineering, Bandwidth, Amplifier and CAN bus, which intersect with Signal processing.

Between 2008 and 2014, his most popular works were:

  • Extracting Simultaneous and Proportional Neural Control Information for Multiple-DOF Prostheses From the Surface Electromyographic Signal (306 citations)
  • Control of Upper Limb Prostheses: Terminology and Proportional Myoelectric Control—A Review (282 citations)
  • Simultaneous and Proportional Force Estimation for Multifunction Myoelectric Prostheses Using Mirrored Bilateral Training (171 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Electrical engineering

Philip A. Parker spends much of his time researching Proportional myoelectric control, Upper limb, Control system, Signal and Speech recognition. The study incorporates disciplines such as Prosthesis, Artificial intelligence, Pattern recognition and Electromyography in addition to Proportional myoelectric control. Philip A. Parker interconnects Training set and Human–computer interaction in the investigation of issues within Prosthesis.

His Pattern recognition research is within the category of Pattern recognition. His Electromyography research integrates issues from Physical therapy, Isometric exercise, Wrist and Biomechanics. Speech recognition is often connected to Artificial neural network in his work.

Best Publications

  • A new strategy for multifunction myoelectric control

    B. Hudgins;P. Parker;R.N. Scott

  • Electromyography. Physiology, engineering and non invasive applications

    Roberto Merletti;Philip Parker

  • A wavelet-based continuous classification scheme for multifunction myoelectric control

    K. Englehart;B. Hudgin;P.A. Parker

  • Classification of the myoelectric signal using time-frequency based representations

    K Englehart;B Hudgins;P.A Parker;M Stevenson

  • Myoelectric signal processing for control of powered limb prostheses.

    P. Parker;K. Englehart;B. Hudgins

  • Control of Upper Limb Prostheses: Terminology and Proportional Myoelectric Control—A Review

    A. Fougner;O. Stavdahl;P. J. Kyberd;Y. G. Losier

  • Fuzzy EMG classification for prosthesis control

    F.H.Y. Chan;Yong-Sheng Yang;F.K. Lam;Yuan-Ting Zhang

  • Extracting Simultaneous and Proportional Neural Control Information for Multiple-DOF Prostheses From the Surface Electromyographic Signal

    Ning Jiang;K.B. Englehart;P.A. Parker

  • The application of neural networks to myoelectric signal analysis: a preliminary study

    M.F. Kelly;P.A. Parker;R.N. Scott

  • Simultaneous and Proportional Force Estimation for Multifunction Myoelectric Prostheses Using Mirrored Bilateral Training

    Johnny L G Nielsen;S Holmgaard;Ning Jiang;K B Englehart

  • Myoelectric control of prostheses.

    P A Parker;R N Scott

  • Myoelectric Prostheses: state of the art

    R N Scott;P A Parker

  • Support Vector Regression for Improved Real-Time, Simultaneous Myoelectric Control

    Ali Ameri;Ernest N. Kamavuako;Erik J. Scheme;Kevin B. Englehart

  • Signal processing for the multistate myoelectric channel

    P.A. Parker;J.A. Stuller;R.N. Scott

  • The short-time Fourier transform and muscle fatigue assessment in dynamic contractions.

    Dawn MacIsaac;Philip A Parker;Robert N Scott

  • Signal representation for classification of the transient myoelectric signal

    K. Englehart;P. Parker;M. Stevenson

  • Basic Physiology and Biophysics of EMG Signal Generation

    Roberto Merletti;Philip Parker

  • Real-Time, Simultaneous Myoelectric Control Using Force and Position-Based Training Paradigms

    Ali Ameri;Erik J. Scheme;Ernest Nlandu Kamavuako;Kevin B. Englehart

  • Relation of intramuscular pressure to the force output and myoelectric signal of skeletal muscle.

    L. Körner;P. Parker;C. Almström;G. B. J. Andersson

  • Noise characteristics of stainless-steel surface electrodes.

    D. T. Godin;P. A. Parker;R. N. Scott

  • Statistics of the myoelectric signal from monopolar and bipolar electrodes

    P. A. Parker;R. N. Scott

Frequent Co-Authors

Kevin Englehart
Kevin Englehart University of New Brunswick
Ning Jiang
Ning Jiang University of Waterloo
Roberto Merletti
Roberto Merletti Polytechnic University of Turin
Yuan-Ting Zhang
Yuan-Ting Zhang City University of Hong Kong
Erik Scheme
Erik Scheme University of New Brunswick
Dario Farina
Dario Farina Imperial College London
Constantinos S. Pattichis
Constantinos S. Pattichis University of Cyprus

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Best Scientists Citing Philip A. Parker