Online Natural Myocontrol of Combined Hand and Wrist Actions Using Tactile Myography and the Biomechanics of Grasping

Despite numerous recent advances in the field of rehabilitation robotics, simultaneous, and proportional control of hand and/or wrist prostheses is still unsolved. In this work we concentrate on myocontrol of combined actions, for instance power grasping while rotating the wrist, by only using train...

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Published inFrontiers in neurorobotics Vol. 14; p. 11
Main Authors Connan, Mathilde, Kõiva, Risto, Castellini, Claudio
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Research Foundation 27.02.2020
Frontiers Media S.A
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Abstract Despite numerous recent advances in the field of rehabilitation robotics, simultaneous, and proportional control of hand and/or wrist prostheses is still unsolved. In this work we concentrate on myocontrol of combined actions, for instance power grasping while rotating the wrist, by only using training data gathered from single actions. This is highly desirable since gathering data for all possible combined actions would be unfeasibly long and demanding for the amputee. We first investigated physiologically feasible limits for muscle activation during combined actions. Using these limits we involved 12 intact participants and one amputee in a Target Achievement Control test, showing that tactile myography, i.e., high-density force myography, solves the problem of combined actions to a remarkable extent using simple linear regression. Since real-time usage of many sensors can be computationally demanding, we compare this approach with another one using a reduced feature set. These reduced features are obtained using a fast, spatial first-order approximation of the sensor values. By using the training data of single actions only, i.e., power grasp or wrist movements, subjects achieved an average success rate of 70.0% in the target achievement test using ridge regression. When combining wrist actions, e.g., pronating and flexing the wrist simultaneously, similar results were obtained with an average of 68.1%. If a power grasp is added to the pool of actions, combined actions are much more difficult to achieve (36.1%). To the best of our knowledge, for the first time, the effectiveness of tactile myography on single and combined actions is evaluated in a target achievement test. The present study includes 3 DoFs control instead of the two generally used in the literature. Additionally, we define a set of physiologically plausible muscle activation limits valid for most experiments of this kind.
AbstractList Objective: Despite numerous recent advances in the field of rehabilitation robotics, simultaneous, and proportional control of hand and/or wrist prostheses is still unsolved. In this work we concentrate on myocontrol of combined actions, for instance power grasping while rotating the wrist, by only using training data gathered from single actions. This is highly desirable since gathering data for all possible combined actions would be unfeasibly long and demanding for the amputee. Approach: We first investigated physiologically feasible limits for muscle activation during combined actions. Using these limits we involved 12 intact participants and one amputee in a Target Achievement Control test, showing that tactile myography, i.e., high-density force myography, solves the problem of combined actions to a remarkable extent using simple linear regression. Since real-time usage of many sensors can be computationally demanding, we compare this approach with another one using a reduced feature set. These reduced features are obtained using a fast, spatial first-order approximation of the sensor values. Main results: By using the training data of single actions only, i.e., power grasp or wrist movements, subjects achieved an average success rate of 70.0% in the target achievement test using ridge regression. When combining wrist actions, e.g., pronating and flexing the wrist simultaneously, similar results were obtained with an average of 68.1%. If a power grasp is added to the pool of actions, combined actions are much more difficult to achieve (36.1%). Significance: To the best of our knowledge, for the first time, the effectiveness of tactile myography on single and combined actions is evaluated in a target achievement test. The present study includes 3 DoFs control instead of the two generally used in the literature. Additionally, we define a set of physiologically plausible muscle activation limits valid for most experiments of this kind.
Objective: Despite numerous recent advances in the field of rehabilitation robotics, simultaneous, and proportional control of hand and/or wrist prostheses is still unsolved. In this work we concentrate on myocontrol of combined actions, for instance power grasping while rotating the wrist, by only using training data gathered from single actions. This is highly desirable since gathering data for all possible combined actions would be unfeasibly long and demanding for the amputee. Approach: We first investigated physiologically feasible limits for muscle activation during combined actions. Using these limits we involved 12 intact participants and one amputee in a Target Achievement Control test, showing that tactile myography, i.e., high-density force myography, solves the problem of combined actions to a remarkable extent using simple linear regression. Since real-time usage of many sensors can be computationally demanding, we compare this approach with another one using a reduced feature set. These reduced features are obtained using a fast, spatial first-order approximation of the sensor values. Main results: By using the training data of single actions only, i.e., power grasp or wrist movements, subjects achieved an average success rate of 70.0% in the target achievement test using ridge regression. When combining wrist actions, e.g., pronating and flexing the wrist simultaneously, similar results were obtained with an average of 68.1%. If a power grasp is added to the pool of actions, combined actions are much more difficult to achieve (36.1%). Significance: To the best of our knowledge, for the first time, the effectiveness of tactile myography on single and combined actions is evaluated in a target achievement test. The present study includes 3 DoFs control instead of the two generally used in the literature. Additionally, we define a set of physiologically plausible muscle activation limits valid for most experiments of this kind.Objective: Despite numerous recent advances in the field of rehabilitation robotics, simultaneous, and proportional control of hand and/or wrist prostheses is still unsolved. In this work we concentrate on myocontrol of combined actions, for instance power grasping while rotating the wrist, by only using training data gathered from single actions. This is highly desirable since gathering data for all possible combined actions would be unfeasibly long and demanding for the amputee. Approach: We first investigated physiologically feasible limits for muscle activation during combined actions. Using these limits we involved 12 intact participants and one amputee in a Target Achievement Control test, showing that tactile myography, i.e., high-density force myography, solves the problem of combined actions to a remarkable extent using simple linear regression. Since real-time usage of many sensors can be computationally demanding, we compare this approach with another one using a reduced feature set. These reduced features are obtained using a fast, spatial first-order approximation of the sensor values. Main results: By using the training data of single actions only, i.e., power grasp or wrist movements, subjects achieved an average success rate of 70.0% in the target achievement test using ridge regression. When combining wrist actions, e.g., pronating and flexing the wrist simultaneously, similar results were obtained with an average of 68.1%. If a power grasp is added to the pool of actions, combined actions are much more difficult to achieve (36.1%). Significance: To the best of our knowledge, for the first time, the effectiveness of tactile myography on single and combined actions is evaluated in a target achievement test. The present study includes 3 DoFs control instead of the two generally used in the literature. Additionally, we define a set of physiologically plausible muscle activation limits valid for most experiments of this kind.
Despite numerous recent advances in the field of rehabilitation robotics, simultaneous, and proportional control of hand and/or wrist prostheses is still unsolved. In this work we concentrate on myocontrol of combined actions, for instance power grasping while rotating the wrist, by only using training data gathered from single actions. This is highly desirable since gathering data for all possible combined actions would be unfeasibly long and demanding for the amputee. We first investigated physiologically feasible limits for muscle activation during combined actions. Using these limits we involved 12 intact participants and one amputee in a Target Achievement Control test, showing that tactile myography, i.e., high-density force myography, solves the problem of combined actions to a remarkable extent using simple linear regression. Since real-time usage of many sensors can be computationally demanding, we compare this approach with another one using a reduced feature set. These reduced features are obtained using a fast, spatial first-order approximation of the sensor values. By using the training data of single actions only, i.e., power grasp or wrist movements, subjects achieved an average success rate of 70.0% in the target achievement test using ridge regression. When combining wrist actions, e.g., pronating and flexing the wrist simultaneously, similar results were obtained with an average of 68.1%. If a power grasp is added to the pool of actions, combined actions are much more difficult to achieve (36.1%). To the best of our knowledge, for the first time, the effectiveness of tactile myography on single and combined actions is evaluated in a target achievement test. The present study includes 3 DoFs control instead of the two generally used in the literature. Additionally, we define a set of physiologically plausible muscle activation limits valid for most experiments of this kind.
Objective: Despite numerous recent advances in the field of rehabilitation robotics, simultaneous, and proportional control of hand and/or wrist prostheses is still unsolved. In this work we concentrate on myocontrol of combined actions, for instance power grasping while rotating the wrist, by only using training data gathered from single actions. This is highly desirable since gathering data for all possible combined actions would be unfeasibly long and demanding for the amputee.Approach: We first investigated physiologically feasible limits for muscle activation during combined actions. Using these limits we involved 12 intact participants and one amputee in a Target Achievement Control test, showing that tactile myography, i.e., high-density force myography, solves the problem of combined actions to a remarkable extent using simple linear regression. Since real-time usage of many sensors can be computationally demanding, we compare this approach with another one using a reduced feature set. These reduced features are obtained using a fast, spatial first-order approximation of the sensor values.Main results: By using the training data of single actions only, i.e., power grasp or wrist movements, subjects achieved an average success rate of 70.0% in the target achievement test using ridge regression. When combining wrist actions, e.g., pronating and flexing the wrist simultaneously, similar results were obtained with an average of 68.1%. If a power grasp is added to the pool of actions, combined actions are much more difficult to achieve (36.1%).Significance: To the best of our knowledge, for the first time, the effectiveness of tactile myography on single and combined actions is evaluated in a target achievement test. The present study includes 3 DoFs control instead of the two generally used in the literature. Additionally, we define a set of physiologically plausible muscle activation limits valid for most experiments of this kind.
Author Kõiva, Risto
Castellini, Claudio
Connan, Mathilde
AuthorAffiliation 2 Research Institute Cognitive Interaction Technology, Bielefeld University , Bielefeld , Germany
1 German Aerospace Center (DLR), Institute of Robotics and Mechatronics , Wessling , Germany
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Cites_doi 10.1016/0169-8141(95)00105-0
10.1016/0003-6870(94)00003-H
10.1109/TIE.2019.2898614
10.1038/nn1010
10.1016/0363-5023(90)90102-W
10.1177/154193127602000115
10.1109/TBME.2008.2007967
10.1109/IEMBS.2007.4353749
10.1682/JRRD.2015.03.0041
10.3389/fnbot.2013.00017
10.1080/0014013031000107595
10.1016/S0363-5023(85)80246-X
10.1016/j.compeleceng.2018.11.012
10.1109/TNSRE.2012.2207916
10.1109/MSP.2012.2203480
10.1682/JRRD.2010.08.0149
10.11183/jhe1972.25.115
10.1109/TNSRE.2013.2282898
10.1109/7333.918278
10.5014/ajot.55.2.212
10.1615/critrevbiomedeng.v38.i4.20
10.1073/pnas.91.16.7534
10.1109/TNSRE.2012.2196711
10.1371/journal.pone.0161678
10.3390/technologies5040064
10.5014/ajot.50.2.133
10.1177/154193129503901001
10.1109/TNSRE.2015.2417775
10.1080/00401706.1970.10488634
10.1109/ROBIO.2011.6181510
10.1109/ICORR.2015.7281192
10.3389/fnbot.2016.00017
10.1016/0169-8141(94)00108-1
10.1080/10803548.1998.11076388
10.1109/TBME.2017.2719400
10.1109/IEMBS.2011.6091938
10.3389/fbioe.2016.00018
10.1126/scirobotics.aat3630
10.1016/0363-5023(91)90006-W
10.1177/154193129203601033
10.1126/science.295.5557.1018
10.1109/JSEN.2015.2450211
10.1615/critrevbiomedeng.v38.i4.10
10.4103/0970-0358.81440
10.3389/fnbot.2014.00022
10.1038/s41551-016-0025
10.3390/technologies6020038
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Copyright © 2020 Connan, Kõiva and Castellini. 2020 Connan, Kõiva and Castellini
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– notice: Copyright © 2020 Connan, Kõiva and Castellini. 2020 Connan, Kõiva and Castellini
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Keywords high-density force myography (HD-FMG)
prosthetics
tactile myography
biomechanics of grasping
grip strength
combined actions
myocontrol
Language English
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References Muceli (B41) 2014; 22
Parvatikar (B52) 2009; 5
Austin (B2) 2005
Cho (B10) 2016; 4
De Smet (B17) 1998; 64
Nowak (B48) 2016; 11
Boschmann (B5) 2014
Curcie (B14) 2001; 9
Claudon (B11) 1998; 4
Palmer (B51) 1985; 10
Hoerl (B28) 1970; 12
Marley (B37) 1992; 36
Kattel (B34) 1996; 18
Ortenzi (B49) 2015
Harris (B27) 1988
Sierra González (B57) 2013; 7
Betthauser (B3) 2018; 65
Ryu (B56) 1991; 16
de Freitas (B16) 2019; 73
Jaquier (B31) 2017; 5
Duque (B19) 1995; 26
Haralick (B26) 1992
Nissler (B44) 2017
Amsuss (B1) 2014
Jiang (B33) 2009; 56
Nowak (B46) 2016
Bhardwaj (B4) 2011; 44
Brand (B6) 1999
Richards (B54) 1996; 50
Hahne (B24) 2018; 3
Nagata (B43) 2011
Castellini (B8) 2018; 6
Yang (B60) 2020; 67
Fong (B22) 2001; 55
Hume (B29) 1990; 15
Mogk (B40) 2003; 46
B45
Merletti (B39); 38
Russ (B55) 1999
Halpern (B25) 1996; 25
Mussa-Ivaldi (B42) 1994; 91
Fang (B20) 2015; 15
Terrell (B59) 1976; 20
Zellers (B62) 1995; 39
Castellini (B7) 2014; 8
Jiang (B32) 2012; 29
Nowak (B47) 2015
Kõiva (B36) 2015
Simon (B58) 2011; 48
Yatsenko (B61) 2007
Dempsey (B18) 1996; 17
Farina (B21) 2017; 1
Merletti (B38); 38
Craelius (B13) 2002; 295
D'Avella (B15) 2003; 6
Fougner (B23) 2012; 20
Kent (B35) 2011
Ortiz-Catalan (B50) 2014
Ison (B30) 2016; 24
Connan (B12) 2016; 10
Castellini (B9) 2012; 20
Radmand (B53) 2016; 53
References_xml – volume: 18
  start-page: 423
  year: 1996
  ident: B34
  article-title: The effect of upper-extremity posture on maximum grip strength
  publication-title: Int. J. Industr. Ergon
  doi: 10.1016/0169-8141(95)00105-0
– volume: 26
  start-page: 61
  year: 1995
  ident: B19
  article-title: Evaluation of handgrip force from EMG measurements
  publication-title: Appl. Ergon
  doi: 10.1016/0003-6870(94)00003-H
– start-page: 132
  volume-title: Proceedings of RO-MAN - IEEE International Symposium on Robot and Human Interactive Communication
  year: 2016
  ident: B46
  article-title: Wrist and grasp myocontrol: online validation in a goal-reaching task
– start-page: 167
  volume-title: Proceedings of MEC - Myoelectric Control Symposium
  year: 2017
  ident: B44
  article-title: Online tactile myography for simultaneous and proportional hand and wrist myocontrol
– volume: 67
  start-page: 800
  year: 2020
  ident: B60
  article-title: A proportional pattern recognition control scheme for wearable a-mode ultrasound sensing
  publication-title: IEEE Trans. Indust. Electron
  doi: 10.1109/TIE.2019.2898614
– start-page: 2
  volume-title: Proceedings of MEC Myoelectric Control Symposium
  year: 2014
  ident: B1
  article-title: Simultaneous, proportional wrist and hand control for natural, dexterous movements of a physical prosthesis by amputees
– volume: 6
  start-page: 300
  year: 2003
  ident: B15
  article-title: Combinations of muscle synergies in the construction of a natural motor behavior
  publication-title: Nat. Neurosci.
  doi: 10.1038/nn1010
– volume: 15
  start-page: 240
  year: 1990
  ident: B29
  article-title: Functional range of motion of the joints of the hand
  publication-title: J. Hand Surg
  doi: 10.1016/0363-5023(90)90102-W
– ident: B45
– volume: 20
  start-page: 28
  year: 1976
  ident: B59
  article-title: The influence of forearm and wrist orientation on static grip strength as a design criterion for hand tools
  publication-title: Proc. Hum. Fact. Ergon. Soc. Ann. Meet
  doi: 10.1177/154193127602000115
– volume: 56
  start-page: 1070
  year: 2009
  ident: B33
  article-title: Extracting simultaneous and proportional neural control information for multiple degree of freedom prostheses from the surface electromyographic signal
  publication-title: IEEE Trans. Biomed. Eng
  doi: 10.1109/TBME.2008.2007967
– start-page: 6133
  volume-title: 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
  year: 2007
  ident: B61
  article-title: Simultaneous, proportional, multi-axis prosthesis control using multichannel surface emg
  doi: 10.1109/IEMBS.2007.4353749
– start-page: 168
  volume-title: Proceedings of Myoelectric Controls/Powered Prosthetics Symposium
  year: 2014
  ident: B50
  article-title: A permanent, bidirectional, osseointegrated interface for the natural control of artificial limbs
– volume: 53
  start-page: 443
  year: 2016
  ident: B53
  article-title: High-density force myography: a possible alternative for upper-limb prosthetic control
  publication-title: J. Rehabil. Res. Dev.
  doi: 10.1682/JRRD.2015.03.0041
– volume: 7
  start-page: 17
  year: 2013
  ident: B57
  article-title: A realistic implementation of ultrasound imaging as a human-machine interface for upper-limb amputees
  publication-title: Front. Neurorobot
  doi: 10.3389/fnbot.2013.00017
– volume: 46
  start-page: 956
  year: 2003
  ident: B40
  article-title: The effects of posture on forearm muscle loading during gripping
  publication-title: Ergonomics
  doi: 10.1080/0014013031000107595
– volume: 10
  start-page: 39
  year: 1985
  ident: B51
  article-title: Functional wrist motion: a biomechanical study
  publication-title: J. Hand Surg.
  doi: 10.1016/S0363-5023(85)80246-X
– volume: 73
  start-page: 167
  year: 2019
  ident: B16
  article-title: Electromyography-controlled car: A proof of concept based on surface electromyography, extreme learning machines and low-cost open hardware
  publication-title: Computers Elect. Eng
  doi: 10.1016/j.compeleceng.2018.11.012
– volume: 20
  start-page: 788
  year: 2012
  ident: B9
  article-title: Using ultrasound images of the forearm to predict finger positions
  publication-title: IEEE Trans. Neural Syst. Rehabil. Eng.
  doi: 10.1109/TNSRE.2012.2207916
– volume: 29
  start-page: 148
  year: 2012
  ident: B32
  article-title: Myoelectric control of artificial limbs - is there a need to change focus?
  publication-title: IEEE Signal. Process. Mag
  doi: 10.1109/MSP.2012.2203480
– volume: 48
  start-page: 619
  year: 2011
  ident: B58
  article-title: Target achievement control test: Evaluating real-time myoelectric pattern recognition control of multifunctional upper-limb prostheses
  publication-title: J. Rehabil. Res. Dev.
  doi: 10.1682/JRRD.2010.08.0149
– volume-title: The Image Processing Handbook, 3rd Edn.
  year: 1999
  ident: B55
– volume: 5
  start-page: 67
  year: 2009
  ident: B52
  article-title: Comparative study of grip strength in different positions of shoulder and elbow with wrist in neutral and extension positions
  publication-title: J. Exerc. Sci. Physiother
– volume: 25
  start-page: 115
  year: 1996
  ident: B25
  article-title: The effect of wrist and arm postures on peak pinch strength
  publication-title: J. Hum. Ergol
  doi: 10.11183/jhe1972.25.115
– start-page: 10
  volume-title: Alvey Vision Conference
  year: 1988
  ident: B27
  article-title: A combined corner and edge detector
– volume: 22
  start-page: 623
  year: 2014
  ident: B41
  article-title: Extracting signals robust to electrode number and shift for online simultaneous and proportional myoelectric control by factorization algorithms
  publication-title: IEEE Trans. Neural Syste. Rehabil. Eng
  doi: 10.1109/TNSRE.2013.2282898
– volume: 9
  start-page: 69
  year: 2001
  ident: B14
  article-title: Biomimetic finger control by filtering of distributed forelimb pressures
  publication-title: IEEE Trans. Neural Syst. Rehabil. Eng.
  doi: 10.1109/7333.918278
– volume: 55
  start-page: 212
  year: 2001
  ident: B22
  article-title: Effect of wrist positioning on the repeatability and strength of power grip
  publication-title: Am. J. Occupat. Therap.
  doi: 10.5014/ajot.55.2.212
– volume: 38
  start-page: 347
  ident: B39
  article-title: Advances in surface emg: recent progress in clinical research applications
  publication-title: Crit. Rev. Biomed. Eng
  doi: 10.1615/critrevbiomedeng.v38.i4.20
– volume: 91
  start-page: 7534
  year: 1994
  ident: B42
  article-title: Linear combinations of primitives in vertebrate motor control
  publication-title: Proc. Natl. Acad. Sci. U. S.A.
  doi: 10.1073/pnas.91.16.7534
– volume: 20
  start-page: 663
  year: 2012
  ident: B23
  article-title: Control of upper limb prostheses: terminology and proportional myoelectric control - a review
  publication-title: IEEE Trans. Neur. Syst. Rehab. Eng
  doi: 10.1109/TNSRE.2012.2196711
– volume: 11
  start-page: e0161678
  year: 2016
  ident: B48
  article-title: The LET procedure for prosthetic myocontrol: towards multi-DOF control using single-DOF activations
  publication-title: PLoS ONE
  doi: 10.1371/journal.pone.0161678
– volume: 5
  start-page: 64
  year: 2017
  ident: B31
  article-title: Combining electro- and tactile myography to improve hand and wrist activity detection in prostheses
  publication-title: MDPI Technol
  doi: 10.3390/technologies5040064
– volume: 50
  start-page: 133
  year: 1996
  ident: B54
  article-title: How forearm position affects grip strength
  publication-title: Am. J. Occupat. Therap.
  doi: 10.5014/ajot.50.2.133
– start-page: 1
  volume-title: Proceedings of ICORR - International Conference on Rehabilitation Robotics
  year: 2015
  ident: B49
  article-title: Ultrasound imaging for hand prosthesis control: a comparative study of features and classification methods
– volume: 39
  start-page: 543
  year: 1995
  ident: B62
  article-title: The effects of gender, wrist and forearm position on maximum isometric power grasp force, wrist force, and their interactions
  publication-title: Proc. Hum. Fact. Ergon. Soc. Ann. Meet
  doi: 10.1177/154193129503901001
– volume: 24
  start-page: 424
  year: 2016
  ident: B30
  article-title: High-density electromyography and motor skill learning for robust long-term control of a 7-dof robot arm
  publication-title: IEEE Trans. Neural Syst. Rehabil. Eng
  doi: 10.1109/TNSRE.2015.2417775
– volume: 12
  start-page: 55
  year: 1970
  ident: B28
  article-title: Ridge regression: Biased estimation for nonorthogonal problems
  publication-title: Technometrics
  doi: 10.1080/00401706.1970.10488634
– start-page: 1555
  volume-title: 2011 IEEE International Conference on Robotics and Biomimetics
  year: 2011
  ident: B35
  article-title: Biomimetic myoelectric control of a dexterous artificial hand for prosthetic applications
  doi: 10.1109/ROBIO.2011.6181510
– start-page: 157
  year: 2015
  ident: B36
  article-title: Shape conformable high spatial resolution tactile bracelet for detecting hand and wrist activity
  publication-title: Proceedings of ICORR - International Conference on Rehabilitation Robotics
  doi: 10.1109/ICORR.2015.7281192
– volume: 64
  start-page: 360
  year: 1998
  ident: B17
  article-title: Effect of forearm rotation on grip strength
  publication-title: Acta Orthop. Belg.
– volume-title: Clinical Mechanics of the Hand, Vol. 93
  year: 1999
  ident: B6
– volume: 10
  start-page: 17
  year: 2016
  ident: B12
  article-title: Assessment of a wearable force- and electromyography device and comparison of the related signals for myocontrol
  publication-title: Front. Neurorobot.
  doi: 10.3389/fnbot.2016.00017
– volume: 17
  start-page: 259
  year: 1996
  ident: B18
  article-title: The influence of gender, grasp type, pinch width and wrist position on sustained pinch strength
  publication-title: Int. J. Industr. Ergon
  doi: 10.1016/0169-8141(94)00108-1
– volume: 4
  start-page: 169
  year: 1998
  ident: B11
  article-title: Evaluation of grip force using electromyograms in isometric isotonic conditions
  publication-title: Int. J. Occupat. Saf. Ergon
  doi: 10.1080/10803548.1998.11076388
– volume: 65
  start-page: 770
  year: 2018
  ident: B3
  article-title: Limb position tolerant pattern recognition for myoelectric prosthesis control with adaptive sparse representations from extreme learning
  publication-title: IEEE Trans. Biomed. Eng
  doi: 10.1109/TBME.2017.2719400
– start-page: 7865
  volume-title: Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
  year: 2011
  ident: B43
  article-title: Basic study on combined motion estimation using multichannel surface emg signals
  doi: 10.1109/IEMBS.2011.6091938
– volume: 4
  start-page: 18
  year: 2016
  ident: B10
  article-title: Force myography to control robotic upper extremity prostheses: a feasibility study
  publication-title: Front. Bioeng. Biotechnol
  doi: 10.3389/fbioe.2016.00018
– volume: 3
  start-page: eaat3630
  year: 2018
  ident: B24
  article-title: Simultaneous control of multiple functions of bionic hand prostheses: performance and robustness in end users
  publication-title: Sci. Robot.
  doi: 10.1126/scirobotics.aat3630
– volume: 16
  start-page: 409
  year: 1991
  ident: B56
  article-title: Functional ranges of motion of the wrist joint
  publication-title: J. Hand Surg
  doi: 10.1016/0363-5023(91)90006-W
– volume: 36
  start-page: 791
  year: 1992
  ident: B37
  article-title: Grip strength as a function of forearm rotation and elbow posture
  publication-title: Hum. Fact. Ergon. Soc. Ann. Meet.
  doi: 10.1177/154193129203601033
– volume: 295
  start-page: 1018
  year: 2002
  ident: B13
  article-title: The bionic man: restoring mobility
  publication-title: Science
  doi: 10.1126/science.295.5557.1018
– volume: 15
  start-page: 6065
  year: 2015
  ident: B20
  article-title: Multi-modal sensing techniques for interfacing hand prostheses: A review
  publication-title: IEEE Sens. J
  doi: 10.1109/JSEN.2015.2450211
– start-page: 339
  volume-title: Proceedings of ICORR - International Conference on Rehabilitation Robotics
  year: 2015
  ident: B47
  article-title: Wrist and grasp myocontrol: simplifying the training phase
– volume: 38
  start-page: 305
  ident: B38
  article-title: Advances in surface emg: recent progress in detection and processing techniques
  publication-title: Crit. Rev. Biomed. Eng
  doi: 10.1615/critrevbiomedeng.v38.i4.10
– start-page: 305
  volume-title: Joint Structure and Function: a Comprehensive Analysis
  year: 2005
  ident: B2
  article-title: The wrist and hand complex
– start-page: 36
  volume-title: Proceedings of MyoElectric Controls Symposium (MEC)
  year: 2014
  ident: B5
  article-title: A computer vision-based approach to high density emg pattern recognition using structural similarity
– volume: 44
  start-page: 55
  year: 2011
  ident: B4
  article-title: Effect of static wrist position on grip strength
  publication-title: Indian J. Plastic Surg
  doi: 10.4103/0970-0358.81440
– volume: 8
  start-page: 22
  year: 2014
  ident: B7
  article-title: Proceedings of the first workshop on peripheral machine interfaces: going beyond traditional surface electromyography
  publication-title: Front. Neurorobot.
  doi: 10.3389/fnbot.2014.00022
– volume-title: Computer and Robot vision
  year: 1992
  ident: B26
– volume: 1
  start-page: 0025
  year: 2017
  ident: B21
  article-title: Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation
  publication-title: Nat. Biomed. Eng.
  doi: 10.1038/s41551-016-0025
– volume: 6
  start-page: 38
  year: 2018
  ident: B8
  article-title: Tactile myography: an off-line assessment on able-bodied subjects and one upper-limb amputee
  publication-title: MDPI Technol.
  doi: 10.3390/technologies6020038
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Snippet Despite numerous recent advances in the field of rehabilitation robotics, simultaneous, and proportional control of hand and/or wrist prostheses is still...
Objective: Despite numerous recent advances in the field of rehabilitation robotics, simultaneous and proportional control of hand and/or wrist prostheses is...
Objective: Despite numerous recent advances in the field of rehabilitation robotics, simultaneous, and proportional control of hand and/or wrist prostheses is...
Objective: Despite numerous recent advances in the field of rehabilitation robotics, simultaneous, and proportional control of hand and/or wrist prostheses is...
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StartPage 11
SubjectTerms Algorithms
Amputation
Biomechanics
combined actions
Decomposition
Electromyography
Experiments
Force
Grasping
grip strength
high-density force myography (HD-FMG)
Muscle contraction
myocontrol
Neuroscience
Principal components analysis
Prostheses
Prosthetics
Regression analysis
Rehabilitation
Sensors
tactile myography
Wrist
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Title Online Natural Myocontrol of Combined Hand and Wrist Actions Using Tactile Myography and the Biomechanics of Grasping
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Volume 14
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