TPress
1.
Schweisfurth, M. A.; Markovic, M.; Dosen, S.; Teich, F.; Graimann, B.; Farina, D.
Electrotactile EMG feedback improves the control of prosthesis grasping force Artikel
In: J. Neural Eng., Bd. 13, Nr. 5, 2016, ISSN: 1741-2560.
Abstract | Links | Schlagwörter: accuracy, adult, amputee, article, case report, controlled study, electromyography, electrotactile electromyography, feedback system, female, force, grip strength, hand prosthesis, human, Michaelangelo Hand, myoelectrically controlled prosthesis, priority journal, sensory feedback, task performance, young adult
@article{Schweisfurth2016,
title = {Electrotactile EMG feedback improves the control of prosthesis grasping force},
author = {M. A. Schweisfurth and M. Markovic and S. Dosen and F. Teich and B. Graimann and D. Farina},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L612465506&from=export},
doi = {10.1088/1741-2560/13/5/056010},
issn = {1741-2560},
year = {2016},
date = {2016-01-01},
journal = {J. Neural Eng.},
volume = {13},
number = {5},
address = {D. Farina, Institute for NeuroRehabilitation Systems, University Medical Center Göttingen, Georg-August University, Göttingen, Germany},
abstract = {Objective. A drawback of active prostheses is that they detach the subject from the produced forces, thereby preventing direct mechanical feedback. This can be compensated by providing somatosensory feedback to the user through mechanical or electrical stimulation, which in turn may improve the utility, sense of embodiment, and thereby increase the acceptance rate. Approach. In this study, we compared a novel approach to closing the loop, namely EMG feedback (emgFB), to classic force feedback (forceFB), using electrotactile interface in a realistic task setup. Eleven intact-bodied subjects and one transradial amputee performed a routine grasping task while receiving emgFB or forceFB. The two feedback types were delivered through the same electrotactile interface, using a mixed spatial/frequency coding to transmit 8 discrete levels of the feedback variable. In emgFB, the stimulation transmitted the amplitude of the processed myoelectric signal generated by the subject (prosthesis input), and in forceFB the generated grasping force (prosthesis output). The task comprised 150 trials of routine grasping at six forces, randomly presented in blocks of five trials (same force). Interquartile range and changes in the absolute error (AE) distribution (magnitude and dispersion) with respect to the target level were used to assess precision and overall performance, respectively. Main results. Relative to forceFB, emgFB significantly improved the precision of myoelectric commands (min/max of the significant levels) for 23%/36% as well as the precision of force control for 12%/32%, in intact-bodied subjects. Also, the magnitude and dispersion of the AE distribution were reduced. The results were similar in the amputee, showing considerable improvements. Significance. Using emgFB, the subjects therefore decreased the uncertainty of the forward pathway. Since there is a correspondence between the EMG and force, where the former anticipates the latter, the emgFB allowed for predictive control, as the subjects used the feedback to adjust the desired force even before the prosthesis contacted the object. In conclusion, the online emgFB was superior to the classic forceFB in realistic conditions that included electrotactile stimulation, limited feedback resolution (8 levels), cognitive processing delay, and time constraints (fast grasping).},
keywords = {accuracy, adult, amputee, article, case report, controlled study, electromyography, electrotactile electromyography, feedback system, female, force, grip strength, hand prosthesis, human, Michaelangelo Hand, myoelectrically controlled prosthesis, priority journal, sensory feedback, task performance, young adult},
pubstate = {published},
tppubtype = {article}
}
Objective. A drawback of active prostheses is that they detach the subject from the produced forces, thereby preventing direct mechanical feedback. This can be compensated by providing somatosensory feedback to the user through mechanical or electrical stimulation, which in turn may improve the utility, sense of embodiment, and thereby increase the acceptance rate. Approach. In this study, we compared a novel approach to closing the loop, namely EMG feedback (emgFB), to classic force feedback (forceFB), using electrotactile interface in a realistic task setup. Eleven intact-bodied subjects and one transradial amputee performed a routine grasping task while receiving emgFB or forceFB. The two feedback types were delivered through the same electrotactile interface, using a mixed spatial/frequency coding to transmit 8 discrete levels of the feedback variable. In emgFB, the stimulation transmitted the amplitude of the processed myoelectric signal generated by the subject (prosthesis input), and in forceFB the generated grasping force (prosthesis output). The task comprised 150 trials of routine grasping at six forces, randomly presented in blocks of five trials (same force). Interquartile range and changes in the absolute error (AE) distribution (magnitude and dispersion) with respect to the target level were used to assess precision and overall performance, respectively. Main results. Relative to forceFB, emgFB significantly improved the precision of myoelectric commands (min/max of the significant levels) for 23%/36% as well as the precision of force control for 12%/32%, in intact-bodied subjects. Also, the magnitude and dispersion of the AE distribution were reduced. The results were similar in the amputee, showing considerable improvements. Significance. Using emgFB, the subjects therefore decreased the uncertainty of the forward pathway. Since there is a correspondence between the EMG and force, where the former anticipates the latter, the emgFB allowed for predictive control, as the subjects used the feedback to adjust the desired force even before the prosthesis contacted the object. In conclusion, the online emgFB was superior to the classic forceFB in realistic conditions that included electrotactile stimulation, limited feedback resolution (8 levels), cognitive processing delay, and time constraints (fast grasping).
2016
Schweisfurth, M. A.; Markovic, M.; Dosen, S.; Teich, F.; Graimann, B.; Farina, D.
Electrotactile EMG feedback improves the control of prosthesis grasping force Artikel
In: J. Neural Eng., Bd. 13, Nr. 5, 2016, ISSN: 1741-2560.
Abstract | Links | Schlagwörter: accuracy, adult, amputee, article, case report, controlled study, electromyography, electrotactile electromyography, feedback system, female, force, grip strength, hand prosthesis, human, Michaelangelo Hand, myoelectrically controlled prosthesis, priority journal, sensory feedback, task performance, young adult
@article{Schweisfurth2016,
title = {Electrotactile EMG feedback improves the control of prosthesis grasping force},
author = {M. A. Schweisfurth and M. Markovic and S. Dosen and F. Teich and B. Graimann and D. Farina},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L612465506&from=export},
doi = {10.1088/1741-2560/13/5/056010},
issn = {1741-2560},
year = {2016},
date = {2016-01-01},
journal = {J. Neural Eng.},
volume = {13},
number = {5},
address = {D. Farina, Institute for NeuroRehabilitation Systems, University Medical Center Göttingen, Georg-August University, Göttingen, Germany},
abstract = {Objective. A drawback of active prostheses is that they detach the subject from the produced forces, thereby preventing direct mechanical feedback. This can be compensated by providing somatosensory feedback to the user through mechanical or electrical stimulation, which in turn may improve the utility, sense of embodiment, and thereby increase the acceptance rate. Approach. In this study, we compared a novel approach to closing the loop, namely EMG feedback (emgFB), to classic force feedback (forceFB), using electrotactile interface in a realistic task setup. Eleven intact-bodied subjects and one transradial amputee performed a routine grasping task while receiving emgFB or forceFB. The two feedback types were delivered through the same electrotactile interface, using a mixed spatial/frequency coding to transmit 8 discrete levels of the feedback variable. In emgFB, the stimulation transmitted the amplitude of the processed myoelectric signal generated by the subject (prosthesis input), and in forceFB the generated grasping force (prosthesis output). The task comprised 150 trials of routine grasping at six forces, randomly presented in blocks of five trials (same force). Interquartile range and changes in the absolute error (AE) distribution (magnitude and dispersion) with respect to the target level were used to assess precision and overall performance, respectively. Main results. Relative to forceFB, emgFB significantly improved the precision of myoelectric commands (min/max of the significant levels) for 23%/36% as well as the precision of force control for 12%/32%, in intact-bodied subjects. Also, the magnitude and dispersion of the AE distribution were reduced. The results were similar in the amputee, showing considerable improvements. Significance. Using emgFB, the subjects therefore decreased the uncertainty of the forward pathway. Since there is a correspondence between the EMG and force, where the former anticipates the latter, the emgFB allowed for predictive control, as the subjects used the feedback to adjust the desired force even before the prosthesis contacted the object. In conclusion, the online emgFB was superior to the classic forceFB in realistic conditions that included electrotactile stimulation, limited feedback resolution (8 levels), cognitive processing delay, and time constraints (fast grasping).},
keywords = {accuracy, adult, amputee, article, case report, controlled study, electromyography, electrotactile electromyography, feedback system, female, force, grip strength, hand prosthesis, human, Michaelangelo Hand, myoelectrically controlled prosthesis, priority journal, sensory feedback, task performance, young adult},
pubstate = {published},
tppubtype = {article}
}
Objective. A drawback of active prostheses is that they detach the subject from the produced forces, thereby preventing direct mechanical feedback. This can be compensated by providing somatosensory feedback to the user through mechanical or electrical stimulation, which in turn may improve the utility, sense of embodiment, and thereby increase the acceptance rate. Approach. In this study, we compared a novel approach to closing the loop, namely EMG feedback (emgFB), to classic force feedback (forceFB), using electrotactile interface in a realistic task setup. Eleven intact-bodied subjects and one transradial amputee performed a routine grasping task while receiving emgFB or forceFB. The two feedback types were delivered through the same electrotactile interface, using a mixed spatial/frequency coding to transmit 8 discrete levels of the feedback variable. In emgFB, the stimulation transmitted the amplitude of the processed myoelectric signal generated by the subject (prosthesis input), and in forceFB the generated grasping force (prosthesis output). The task comprised 150 trials of routine grasping at six forces, randomly presented in blocks of five trials (same force). Interquartile range and changes in the absolute error (AE) distribution (magnitude and dispersion) with respect to the target level were used to assess precision and overall performance, respectively. Main results. Relative to forceFB, emgFB significantly improved the precision of myoelectric commands (min/max of the significant levels) for 23%/36% as well as the precision of force control for 12%/32%, in intact-bodied subjects. Also, the magnitude and dispersion of the AE distribution were reduced. The results were similar in the amputee, showing considerable improvements. Significance. Using emgFB, the subjects therefore decreased the uncertainty of the forward pathway. Since there is a correspondence between the EMG and force, where the former anticipates the latter, the emgFB allowed for predictive control, as the subjects used the feedback to adjust the desired force even before the prosthesis contacted the object. In conclusion, the online emgFB was superior to the classic forceFB in realistic conditions that included electrotactile stimulation, limited feedback resolution (8 levels), cognitive processing delay, and time constraints (fast grasping).
2016
Schweisfurth, M. A.; Markovic, M.; Dosen, S.; Teich, F.; Graimann, B.; Farina, D.
Electrotactile EMG feedback improves the control of prosthesis grasping force Artikel
In: J. Neural Eng., Bd. 13, Nr. 5, 2016, ISSN: 1741-2560.
@article{Schweisfurth2016,
title = {Electrotactile EMG feedback improves the control of prosthesis grasping force},
author = {M. A. Schweisfurth and M. Markovic and S. Dosen and F. Teich and B. Graimann and D. Farina},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L612465506&from=export},
doi = {10.1088/1741-2560/13/5/056010},
issn = {1741-2560},
year = {2016},
date = {2016-01-01},
journal = {J. Neural Eng.},
volume = {13},
number = {5},
address = {D. Farina, Institute for NeuroRehabilitation Systems, University Medical Center Göttingen, Georg-August University, Göttingen, Germany},
abstract = {Objective. A drawback of active prostheses is that they detach the subject from the produced forces, thereby preventing direct mechanical feedback. This can be compensated by providing somatosensory feedback to the user through mechanical or electrical stimulation, which in turn may improve the utility, sense of embodiment, and thereby increase the acceptance rate. Approach. In this study, we compared a novel approach to closing the loop, namely EMG feedback (emgFB), to classic force feedback (forceFB), using electrotactile interface in a realistic task setup. Eleven intact-bodied subjects and one transradial amputee performed a routine grasping task while receiving emgFB or forceFB. The two feedback types were delivered through the same electrotactile interface, using a mixed spatial/frequency coding to transmit 8 discrete levels of the feedback variable. In emgFB, the stimulation transmitted the amplitude of the processed myoelectric signal generated by the subject (prosthesis input), and in forceFB the generated grasping force (prosthesis output). The task comprised 150 trials of routine grasping at six forces, randomly presented in blocks of five trials (same force). Interquartile range and changes in the absolute error (AE) distribution (magnitude and dispersion) with respect to the target level were used to assess precision and overall performance, respectively. Main results. Relative to forceFB, emgFB significantly improved the precision of myoelectric commands (min/max of the significant levels) for 23%/36% as well as the precision of force control for 12%/32%, in intact-bodied subjects. Also, the magnitude and dispersion of the AE distribution were reduced. The results were similar in the amputee, showing considerable improvements. Significance. Using emgFB, the subjects therefore decreased the uncertainty of the forward pathway. Since there is a correspondence between the EMG and force, where the former anticipates the latter, the emgFB allowed for predictive control, as the subjects used the feedback to adjust the desired force even before the prosthesis contacted the object. In conclusion, the online emgFB was superior to the classic forceFB in realistic conditions that included electrotactile stimulation, limited feedback resolution (8 levels), cognitive processing delay, and time constraints (fast grasping).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Objective. A drawback of active prostheses is that they detach the subject from the produced forces, thereby preventing direct mechanical feedback. This can be compensated by providing somatosensory feedback to the user through mechanical or electrical stimulation, which in turn may improve the utility, sense of embodiment, and thereby increase the acceptance rate. Approach. In this study, we compared a novel approach to closing the loop, namely EMG feedback (emgFB), to classic force feedback (forceFB), using electrotactile interface in a realistic task setup. Eleven intact-bodied subjects and one transradial amputee performed a routine grasping task while receiving emgFB or forceFB. The two feedback types were delivered through the same electrotactile interface, using a mixed spatial/frequency coding to transmit 8 discrete levels of the feedback variable. In emgFB, the stimulation transmitted the amplitude of the processed myoelectric signal generated by the subject (prosthesis input), and in forceFB the generated grasping force (prosthesis output). The task comprised 150 trials of routine grasping at six forces, randomly presented in blocks of five trials (same force). Interquartile range and changes in the absolute error (AE) distribution (magnitude and dispersion) with respect to the target level were used to assess precision and overall performance, respectively. Main results. Relative to forceFB, emgFB significantly improved the precision of myoelectric commands (min/max of the significant levels) for 23%/36% as well as the precision of force control for 12%/32%, in intact-bodied subjects. Also, the magnitude and dispersion of the AE distribution were reduced. The results were similar in the amputee, showing considerable improvements. Significance. Using emgFB, the subjects therefore decreased the uncertainty of the forward pathway. Since there is a correspondence between the EMG and force, where the former anticipates the latter, the emgFB allowed for predictive control, as the subjects used the feedback to adjust the desired force even before the prosthesis contacted the object. In conclusion, the online emgFB was superior to the classic forceFB in realistic conditions that included electrotactile stimulation, limited feedback resolution (8 levels), cognitive processing delay, and time constraints (fast grasping).