TPress
1.
Dosen, S.; Markovic, M.; Strbac, M.; Belic, M.; Kojic, V.; Bijelic, G.; Keller, T.; Farina, D.
In: IEEE Trans. Neural Syst. Rehabil. Eng., Bd. 25, Nr. 3, S. 183–195, 2017, ISSN: 1534-4320.
Abstract | Links | Schlagwörter: article, electrode, electromyogram, frequency modulation, hand prosthesis, human, human experiment, Michelangelo hand, muscle isometric contraction, myoelectric control, psychometry, rehabilitation equipment, spatial discrimination, tactile feedback, visual feedback
@article{Dosen2017,
title = {Multichannel electrotactile feedback with spatial and mixed coding for closed-loop control of grasping force in hand prostheses},
author = {S. Dosen and M. Markovic and M. Strbac and M. Belic and V. Kojic and G. Bijelic and T. Keller and D. Farina},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L615004930&from=export},
doi = {10.1109/tnsre.2016.2550864},
issn = {1534-4320},
year = {2017},
date = {2017-01-01},
journal = {IEEE Trans. Neural Syst. Rehabil. Eng.},
volume = {25},
number = {3},
pages = {183–195},
abstract = {Providing somatosensory feedback to the user of a myoelectric prosthesis is an important goal since it can improve the utility as well as facilitate the embodiment of the assistive system. Most often, the grasping force was selected as the feedback variable and communicated through one or more individual single channel stimulation units (e.g., electrodes, vibration motors). In the present study, an integrated, compact, multichannel solution comprising an array electrode and a programmable stimulator was presented. Two coding schemes (15 levels), spatial and mixed (spatial and frequency) modulation, were tested in able-bodied subjects, psychometrically and in force control with routine grasping and force tracking using real and simulated prosthesis. The results demonstrated that mixed and spatial coding, although substantially different in psychometric tests, resulted in a similar performance during both force control tasks. Furthermore, the ideal, visual feedback was not better than the tactile feedback in routine grasping. To explain the observed results, a conceptual model was proposed emphasizing that the performance depends on multiple factors, including feedback uncertainty, nature of the task and the reliability of the feedforward control. The study outcomes, specific conclusions and the general model, are relevant for the design of closed-loop myoelectric prostheses utilizing tactile feedback.},
keywords = {article, electrode, electromyogram, frequency modulation, hand prosthesis, human, human experiment, Michelangelo hand, muscle isometric contraction, myoelectric control, psychometry, rehabilitation equipment, spatial discrimination, tactile feedback, visual feedback},
pubstate = {published},
tppubtype = {article}
}
Providing somatosensory feedback to the user of a myoelectric prosthesis is an important goal since it can improve the utility as well as facilitate the embodiment of the assistive system. Most often, the grasping force was selected as the feedback variable and communicated through one or more individual single channel stimulation units (e.g., electrodes, vibration motors). In the present study, an integrated, compact, multichannel solution comprising an array electrode and a programmable stimulator was presented. Two coding schemes (15 levels), spatial and mixed (spatial and frequency) modulation, were tested in able-bodied subjects, psychometrically and in force control with routine grasping and force tracking using real and simulated prosthesis. The results demonstrated that mixed and spatial coding, although substantially different in psychometric tests, resulted in a similar performance during both force control tasks. Furthermore, the ideal, visual feedback was not better than the tactile feedback in routine grasping. To explain the observed results, a conceptual model was proposed emphasizing that the performance depends on multiple factors, including feedback uncertainty, nature of the task and the reliability of the feedforward control. The study outcomes, specific conclusions and the general model, are relevant for the design of closed-loop myoelectric prostheses utilizing tactile feedback.
2.
Dosen, S.; Markovic, M.; Somer, K.; Graimann, B.; Farina, D.
EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis Artikel
In: J. NeuroEng. Rehabil., Bd. 12, Nr. 1, 2015, ISSN: 1743-0003.
Abstract | Links | Schlagwörter: adult, arm amputation, article, case report, computer interface, controlled study, EMG biofeedback, feedback system, grip strength, human, human computer interaction, Michelangelo hand, middle aged, muscle strength, myoelectric control, myoelectrically controlled prosthesis, online system, prediction, priority journal, Sensor Hand
@article{Dosen2015,
title = {EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis},
author = {S. Dosen and M. Markovic and K. Somer and B. Graimann and D. Farina},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L605002250&from=export},
doi = {10.1186/s12984-015-0047-z},
issn = {1743-0003},
year = {2015},
date = {2015-06-01},
journal = {J. NeuroEng. Rehabil.},
volume = {12},
number = {1},
publisher = {Springer Science and Business Media LLC},
address = {D. Farina, Department of Neurorehabilitation Engineering, University Medical Center Göttingen (UMG), Georg-August University, Göttingen, Germany},
abstract = {Background: Active hand prostheses controlled using electromyography (EMG) signals have been used for decades to restore the grasping function, lost after an amputation. Although myocontrol is a simple and intuitive interface, it is also imprecise due to the stochastic nature of the EMG recorded using surface electrodes. Furthermore, the sensory feedback from the prosthesis to the user is still missing. In this study, we present a novel concept to close the loop in myoelectric prostheses. In addition to conveying the grasping force (system output), we provided to the user the online information about the system input (EMG biofeedback). Methods: As a proof-of-concept, the EMG biofeedback was transmitted in the current study using a visual interface (ideal condition). Ten able-bodied subjects and two amputees controlled a state-of-the-art myoelectric prosthesis in routine grasping and force steering tasks using EMG and force feedback (novel approach) and force feedback only (classic approach). The outcome measures were the variability of the generated forces and absolute deviation from the target levels in the routine grasping task, and the root mean square tracking error and the number of sudden drops in the force steering task. Results: During the routine grasping, the novel method when used by able-bodied subjects decreased twofold the force dispersion as well as absolute deviations from the target force levels, and also resulted in a more accurate and stable tracking of the reference force profiles during the force steering. Furthermore, the force variability during routine grasping did not increase for the higher target forces with EMG biofeedback. The trend was similar in the two amputees. Conclusions: The study demonstrated that the subjects, including the two experienced users of a myoelectric prosthesis, were able to exploit the online EMG biofeedback to observe and modulate the myoelectric signals, generating thereby more consistent commands. This allowed them to control the force predictively (routine grasping) and with a finer resolution (force steering). The future step will be to implement this promising and simple approach using an electrotactile interface. A prosthesis with a reliable response, following faithfully user intentions, would improve the utility during daily-life use and also facilitate the embodiment of the assistive system.},
keywords = {adult, arm amputation, article, case report, computer interface, controlled study, EMG biofeedback, feedback system, grip strength, human, human computer interaction, Michelangelo hand, middle aged, muscle strength, myoelectric control, myoelectrically controlled prosthesis, online system, prediction, priority journal, Sensor Hand},
pubstate = {published},
tppubtype = {article}
}
Background: Active hand prostheses controlled using electromyography (EMG) signals have been used for decades to restore the grasping function, lost after an amputation. Although myocontrol is a simple and intuitive interface, it is also imprecise due to the stochastic nature of the EMG recorded using surface electrodes. Furthermore, the sensory feedback from the prosthesis to the user is still missing. In this study, we present a novel concept to close the loop in myoelectric prostheses. In addition to conveying the grasping force (system output), we provided to the user the online information about the system input (EMG biofeedback). Methods: As a proof-of-concept, the EMG biofeedback was transmitted in the current study using a visual interface (ideal condition). Ten able-bodied subjects and two amputees controlled a state-of-the-art myoelectric prosthesis in routine grasping and force steering tasks using EMG and force feedback (novel approach) and force feedback only (classic approach). The outcome measures were the variability of the generated forces and absolute deviation from the target levels in the routine grasping task, and the root mean square tracking error and the number of sudden drops in the force steering task. Results: During the routine grasping, the novel method when used by able-bodied subjects decreased twofold the force dispersion as well as absolute deviations from the target force levels, and also resulted in a more accurate and stable tracking of the reference force profiles during the force steering. Furthermore, the force variability during routine grasping did not increase for the higher target forces with EMG biofeedback. The trend was similar in the two amputees. Conclusions: The study demonstrated that the subjects, including the two experienced users of a myoelectric prosthesis, were able to exploit the online EMG biofeedback to observe and modulate the myoelectric signals, generating thereby more consistent commands. This allowed them to control the force predictively (routine grasping) and with a finer resolution (force steering). The future step will be to implement this promising and simple approach using an electrotactile interface. A prosthesis with a reliable response, following faithfully user intentions, would improve the utility during daily-life use and also facilitate the embodiment of the assistive system.
2017
Dosen, S.; Markovic, M.; Strbac, M.; Belic, M.; Kojic, V.; Bijelic, G.; Keller, T.; Farina, D.
In: IEEE Trans. Neural Syst. Rehabil. Eng., Bd. 25, Nr. 3, S. 183–195, 2017, ISSN: 1534-4320.
Abstract | Links | Schlagwörter: article, electrode, electromyogram, frequency modulation, hand prosthesis, human, human experiment, Michelangelo hand, muscle isometric contraction, myoelectric control, psychometry, rehabilitation equipment, spatial discrimination, tactile feedback, visual feedback
@article{Dosen2017,
title = {Multichannel electrotactile feedback with spatial and mixed coding for closed-loop control of grasping force in hand prostheses},
author = {S. Dosen and M. Markovic and M. Strbac and M. Belic and V. Kojic and G. Bijelic and T. Keller and D. Farina},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L615004930&from=export},
doi = {10.1109/tnsre.2016.2550864},
issn = {1534-4320},
year = {2017},
date = {2017-01-01},
journal = {IEEE Trans. Neural Syst. Rehabil. Eng.},
volume = {25},
number = {3},
pages = {183–195},
abstract = {Providing somatosensory feedback to the user of a myoelectric prosthesis is an important goal since it can improve the utility as well as facilitate the embodiment of the assistive system. Most often, the grasping force was selected as the feedback variable and communicated through one or more individual single channel stimulation units (e.g., electrodes, vibration motors). In the present study, an integrated, compact, multichannel solution comprising an array electrode and a programmable stimulator was presented. Two coding schemes (15 levels), spatial and mixed (spatial and frequency) modulation, were tested in able-bodied subjects, psychometrically and in force control with routine grasping and force tracking using real and simulated prosthesis. The results demonstrated that mixed and spatial coding, although substantially different in psychometric tests, resulted in a similar performance during both force control tasks. Furthermore, the ideal, visual feedback was not better than the tactile feedback in routine grasping. To explain the observed results, a conceptual model was proposed emphasizing that the performance depends on multiple factors, including feedback uncertainty, nature of the task and the reliability of the feedforward control. The study outcomes, specific conclusions and the general model, are relevant for the design of closed-loop myoelectric prostheses utilizing tactile feedback.},
keywords = {article, electrode, electromyogram, frequency modulation, hand prosthesis, human, human experiment, Michelangelo hand, muscle isometric contraction, myoelectric control, psychometry, rehabilitation equipment, spatial discrimination, tactile feedback, visual feedback},
pubstate = {published},
tppubtype = {article}
}
Providing somatosensory feedback to the user of a myoelectric prosthesis is an important goal since it can improve the utility as well as facilitate the embodiment of the assistive system. Most often, the grasping force was selected as the feedback variable and communicated through one or more individual single channel stimulation units (e.g., electrodes, vibration motors). In the present study, an integrated, compact, multichannel solution comprising an array electrode and a programmable stimulator was presented. Two coding schemes (15 levels), spatial and mixed (spatial and frequency) modulation, were tested in able-bodied subjects, psychometrically and in force control with routine grasping and force tracking using real and simulated prosthesis. The results demonstrated that mixed and spatial coding, although substantially different in psychometric tests, resulted in a similar performance during both force control tasks. Furthermore, the ideal, visual feedback was not better than the tactile feedback in routine grasping. To explain the observed results, a conceptual model was proposed emphasizing that the performance depends on multiple factors, including feedback uncertainty, nature of the task and the reliability of the feedforward control. The study outcomes, specific conclusions and the general model, are relevant for the design of closed-loop myoelectric prostheses utilizing tactile feedback.
2015
Dosen, S.; Markovic, M.; Somer, K.; Graimann, B.; Farina, D.
EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis Artikel
In: J. NeuroEng. Rehabil., Bd. 12, Nr. 1, 2015, ISSN: 1743-0003.
Abstract | Links | Schlagwörter: adult, arm amputation, article, case report, computer interface, controlled study, EMG biofeedback, feedback system, grip strength, human, human computer interaction, Michelangelo hand, middle aged, muscle strength, myoelectric control, myoelectrically controlled prosthesis, online system, prediction, priority journal, Sensor Hand
@article{Dosen2015,
title = {EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis},
author = {S. Dosen and M. Markovic and K. Somer and B. Graimann and D. Farina},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L605002250&from=export},
doi = {10.1186/s12984-015-0047-z},
issn = {1743-0003},
year = {2015},
date = {2015-06-01},
journal = {J. NeuroEng. Rehabil.},
volume = {12},
number = {1},
publisher = {Springer Science and Business Media LLC},
address = {D. Farina, Department of Neurorehabilitation Engineering, University Medical Center Göttingen (UMG), Georg-August University, Göttingen, Germany},
abstract = {Background: Active hand prostheses controlled using electromyography (EMG) signals have been used for decades to restore the grasping function, lost after an amputation. Although myocontrol is a simple and intuitive interface, it is also imprecise due to the stochastic nature of the EMG recorded using surface electrodes. Furthermore, the sensory feedback from the prosthesis to the user is still missing. In this study, we present a novel concept to close the loop in myoelectric prostheses. In addition to conveying the grasping force (system output), we provided to the user the online information about the system input (EMG biofeedback). Methods: As a proof-of-concept, the EMG biofeedback was transmitted in the current study using a visual interface (ideal condition). Ten able-bodied subjects and two amputees controlled a state-of-the-art myoelectric prosthesis in routine grasping and force steering tasks using EMG and force feedback (novel approach) and force feedback only (classic approach). The outcome measures were the variability of the generated forces and absolute deviation from the target levels in the routine grasping task, and the root mean square tracking error and the number of sudden drops in the force steering task. Results: During the routine grasping, the novel method when used by able-bodied subjects decreased twofold the force dispersion as well as absolute deviations from the target force levels, and also resulted in a more accurate and stable tracking of the reference force profiles during the force steering. Furthermore, the force variability during routine grasping did not increase for the higher target forces with EMG biofeedback. The trend was similar in the two amputees. Conclusions: The study demonstrated that the subjects, including the two experienced users of a myoelectric prosthesis, were able to exploit the online EMG biofeedback to observe and modulate the myoelectric signals, generating thereby more consistent commands. This allowed them to control the force predictively (routine grasping) and with a finer resolution (force steering). The future step will be to implement this promising and simple approach using an electrotactile interface. A prosthesis with a reliable response, following faithfully user intentions, would improve the utility during daily-life use and also facilitate the embodiment of the assistive system.},
keywords = {adult, arm amputation, article, case report, computer interface, controlled study, EMG biofeedback, feedback system, grip strength, human, human computer interaction, Michelangelo hand, middle aged, muscle strength, myoelectric control, myoelectrically controlled prosthesis, online system, prediction, priority journal, Sensor Hand},
pubstate = {published},
tppubtype = {article}
}
Background: Active hand prostheses controlled using electromyography (EMG) signals have been used for decades to restore the grasping function, lost after an amputation. Although myocontrol is a simple and intuitive interface, it is also imprecise due to the stochastic nature of the EMG recorded using surface electrodes. Furthermore, the sensory feedback from the prosthesis to the user is still missing. In this study, we present a novel concept to close the loop in myoelectric prostheses. In addition to conveying the grasping force (system output), we provided to the user the online information about the system input (EMG biofeedback). Methods: As a proof-of-concept, the EMG biofeedback was transmitted in the current study using a visual interface (ideal condition). Ten able-bodied subjects and two amputees controlled a state-of-the-art myoelectric prosthesis in routine grasping and force steering tasks using EMG and force feedback (novel approach) and force feedback only (classic approach). The outcome measures were the variability of the generated forces and absolute deviation from the target levels in the routine grasping task, and the root mean square tracking error and the number of sudden drops in the force steering task. Results: During the routine grasping, the novel method when used by able-bodied subjects decreased twofold the force dispersion as well as absolute deviations from the target force levels, and also resulted in a more accurate and stable tracking of the reference force profiles during the force steering. Furthermore, the force variability during routine grasping did not increase for the higher target forces with EMG biofeedback. The trend was similar in the two amputees. Conclusions: The study demonstrated that the subjects, including the two experienced users of a myoelectric prosthesis, were able to exploit the online EMG biofeedback to observe and modulate the myoelectric signals, generating thereby more consistent commands. This allowed them to control the force predictively (routine grasping) and with a finer resolution (force steering). The future step will be to implement this promising and simple approach using an electrotactile interface. A prosthesis with a reliable response, following faithfully user intentions, would improve the utility during daily-life use and also facilitate the embodiment of the assistive system.
2017
Dosen, S.; Markovic, M.; Strbac, M.; Belic, M.; Kojic, V.; Bijelic, G.; Keller, T.; Farina, D.
In: IEEE Trans. Neural Syst. Rehabil. Eng., Bd. 25, Nr. 3, S. 183–195, 2017, ISSN: 1534-4320.
@article{Dosen2017,
title = {Multichannel electrotactile feedback with spatial and mixed coding for closed-loop control of grasping force in hand prostheses},
author = {S. Dosen and M. Markovic and M. Strbac and M. Belic and V. Kojic and G. Bijelic and T. Keller and D. Farina},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L615004930&from=export},
doi = {10.1109/tnsre.2016.2550864},
issn = {1534-4320},
year = {2017},
date = {2017-01-01},
journal = {IEEE Trans. Neural Syst. Rehabil. Eng.},
volume = {25},
number = {3},
pages = {183–195},
abstract = {Providing somatosensory feedback to the user of a myoelectric prosthesis is an important goal since it can improve the utility as well as facilitate the embodiment of the assistive system. Most often, the grasping force was selected as the feedback variable and communicated through one or more individual single channel stimulation units (e.g., electrodes, vibration motors). In the present study, an integrated, compact, multichannel solution comprising an array electrode and a programmable stimulator was presented. Two coding schemes (15 levels), spatial and mixed (spatial and frequency) modulation, were tested in able-bodied subjects, psychometrically and in force control with routine grasping and force tracking using real and simulated prosthesis. The results demonstrated that mixed and spatial coding, although substantially different in psychometric tests, resulted in a similar performance during both force control tasks. Furthermore, the ideal, visual feedback was not better than the tactile feedback in routine grasping. To explain the observed results, a conceptual model was proposed emphasizing that the performance depends on multiple factors, including feedback uncertainty, nature of the task and the reliability of the feedforward control. The study outcomes, specific conclusions and the general model, are relevant for the design of closed-loop myoelectric prostheses utilizing tactile feedback.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Providing somatosensory feedback to the user of a myoelectric prosthesis is an important goal since it can improve the utility as well as facilitate the embodiment of the assistive system. Most often, the grasping force was selected as the feedback variable and communicated through one or more individual single channel stimulation units (e.g., electrodes, vibration motors). In the present study, an integrated, compact, multichannel solution comprising an array electrode and a programmable stimulator was presented. Two coding schemes (15 levels), spatial and mixed (spatial and frequency) modulation, were tested in able-bodied subjects, psychometrically and in force control with routine grasping and force tracking using real and simulated prosthesis. The results demonstrated that mixed and spatial coding, although substantially different in psychometric tests, resulted in a similar performance during both force control tasks. Furthermore, the ideal, visual feedback was not better than the tactile feedback in routine grasping. To explain the observed results, a conceptual model was proposed emphasizing that the performance depends on multiple factors, including feedback uncertainty, nature of the task and the reliability of the feedforward control. The study outcomes, specific conclusions and the general model, are relevant for the design of closed-loop myoelectric prostheses utilizing tactile feedback.
2015
Dosen, S.; Markovic, M.; Somer, K.; Graimann, B.; Farina, D.
EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis Artikel
In: J. NeuroEng. Rehabil., Bd. 12, Nr. 1, 2015, ISSN: 1743-0003.
@article{Dosen2015,
title = {EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis},
author = {S. Dosen and M. Markovic and K. Somer and B. Graimann and D. Farina},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L605002250&from=export},
doi = {10.1186/s12984-015-0047-z},
issn = {1743-0003},
year = {2015},
date = {2015-06-01},
journal = {J. NeuroEng. Rehabil.},
volume = {12},
number = {1},
publisher = {Springer Science and Business Media LLC},
address = {D. Farina, Department of Neurorehabilitation Engineering, University Medical Center Göttingen (UMG), Georg-August University, Göttingen, Germany},
abstract = {Background: Active hand prostheses controlled using electromyography (EMG) signals have been used for decades to restore the grasping function, lost after an amputation. Although myocontrol is a simple and intuitive interface, it is also imprecise due to the stochastic nature of the EMG recorded using surface electrodes. Furthermore, the sensory feedback from the prosthesis to the user is still missing. In this study, we present a novel concept to close the loop in myoelectric prostheses. In addition to conveying the grasping force (system output), we provided to the user the online information about the system input (EMG biofeedback). Methods: As a proof-of-concept, the EMG biofeedback was transmitted in the current study using a visual interface (ideal condition). Ten able-bodied subjects and two amputees controlled a state-of-the-art myoelectric prosthesis in routine grasping and force steering tasks using EMG and force feedback (novel approach) and force feedback only (classic approach). The outcome measures were the variability of the generated forces and absolute deviation from the target levels in the routine grasping task, and the root mean square tracking error and the number of sudden drops in the force steering task. Results: During the routine grasping, the novel method when used by able-bodied subjects decreased twofold the force dispersion as well as absolute deviations from the target force levels, and also resulted in a more accurate and stable tracking of the reference force profiles during the force steering. Furthermore, the force variability during routine grasping did not increase for the higher target forces with EMG biofeedback. The trend was similar in the two amputees. Conclusions: The study demonstrated that the subjects, including the two experienced users of a myoelectric prosthesis, were able to exploit the online EMG biofeedback to observe and modulate the myoelectric signals, generating thereby more consistent commands. This allowed them to control the force predictively (routine grasping) and with a finer resolution (force steering). The future step will be to implement this promising and simple approach using an electrotactile interface. A prosthesis with a reliable response, following faithfully user intentions, would improve the utility during daily-life use and also facilitate the embodiment of the assistive system.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background: Active hand prostheses controlled using electromyography (EMG) signals have been used for decades to restore the grasping function, lost after an amputation. Although myocontrol is a simple and intuitive interface, it is also imprecise due to the stochastic nature of the EMG recorded using surface electrodes. Furthermore, the sensory feedback from the prosthesis to the user is still missing. In this study, we present a novel concept to close the loop in myoelectric prostheses. In addition to conveying the grasping force (system output), we provided to the user the online information about the system input (EMG biofeedback). Methods: As a proof-of-concept, the EMG biofeedback was transmitted in the current study using a visual interface (ideal condition). Ten able-bodied subjects and two amputees controlled a state-of-the-art myoelectric prosthesis in routine grasping and force steering tasks using EMG and force feedback (novel approach) and force feedback only (classic approach). The outcome measures were the variability of the generated forces and absolute deviation from the target levels in the routine grasping task, and the root mean square tracking error and the number of sudden drops in the force steering task. Results: During the routine grasping, the novel method when used by able-bodied subjects decreased twofold the force dispersion as well as absolute deviations from the target force levels, and also resulted in a more accurate and stable tracking of the reference force profiles during the force steering. Furthermore, the force variability during routine grasping did not increase for the higher target forces with EMG biofeedback. The trend was similar in the two amputees. Conclusions: The study demonstrated that the subjects, including the two experienced users of a myoelectric prosthesis, were able to exploit the online EMG biofeedback to observe and modulate the myoelectric signals, generating thereby more consistent commands. This allowed them to control the force predictively (routine grasping) and with a finer resolution (force steering). The future step will be to implement this promising and simple approach using an electrotactile interface. A prosthesis with a reliable response, following faithfully user intentions, would improve the utility during daily-life use and also facilitate the embodiment of the assistive system.