TPress
1.
Hahne, J. M.; Wilke, M. A.; Koppe, M.; Farina, D.; Schilling, A. F.
Longitudinal Case Study of Regression-Based Hand Prosthesis Control in Daily Life Artikel
In: Front. Neurosci., Bd. 14, 2020, ISSN: 1662-4548.
Abstract | Links | Schlagwörter: adult, arm amputation, article, case study, clinical article, controlled study, electric hand, hand prosthesis, human, longitudinal study, male, middle aged, motor control, questionnaire, regression analysis, VariPlus Speed
@article{Hahne2020,
title = {Longitudinal Case Study of Regression-Based Hand Prosthesis Control in Daily Life},
author = {J. M. Hahne and M. A. Wilke and M. Koppe and D. Farina and A. F. Schilling},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L632229544&from=export},
doi = {10.3389/fnins.2020.00600},
issn = {1662-4548},
year = {2020},
date = {2020-01-01},
journal = {Front. Neurosci.},
volume = {14},
address = {J.M. Hahne, Applied Rehabilitation Technology Lab, Department of Trauma Surgery, Orthopedic Surgery and Hand Surgery, University Medical Center Göttingen, Göttingen, Germany},
abstract = {Hand prostheses are usually controlled by electromyographic (EMG) signals from the remnant muscles of the residual limb. Most prostheses used today are controlled with very simple techniques using only two EMG electrodes that allow to control a single prosthetic function at a time only. Recently, modern prosthesis controllers based on EMG classification, have become clinically available, which allow to directly access more functions, but still in a sequential manner only. We have recently shown in laboratory tests that a regression-based mapping from EMG signals into prosthetic control commands allows for a simultaneous activation of two functions and an independent control of their velocities with high reliability. Here we aimed to study how such regression-based control performs in daily life in a two-month case study. The performance is evaluated in functional tests and with a questionnaire at the beginning and the end of this phase and compared with the participant’s own prosthesis, controlled with a classical approach. Already 1 day after training of the regression model, the participant with transradial amputation outperformed the performance achieved with his own Michelangelo hand in two out of three functional metrics. No retraining of the model was required during the entire study duration. During the use of the system at home, the performance improved further and outperformed the conventional control in all three metrics. This study demonstrates that the high fidelity of linear regression-based prosthesis control is not restricted to a laboratory environment, but can be transferred to daily use.},
keywords = {adult, arm amputation, article, case study, clinical article, controlled study, electric hand, hand prosthesis, human, longitudinal study, male, middle aged, motor control, questionnaire, regression analysis, VariPlus Speed},
pubstate = {published},
tppubtype = {article}
}
Hand prostheses are usually controlled by electromyographic (EMG) signals from the remnant muscles of the residual limb. Most prostheses used today are controlled with very simple techniques using only two EMG electrodes that allow to control a single prosthetic function at a time only. Recently, modern prosthesis controllers based on EMG classification, have become clinically available, which allow to directly access more functions, but still in a sequential manner only. We have recently shown in laboratory tests that a regression-based mapping from EMG signals into prosthetic control commands allows for a simultaneous activation of two functions and an independent control of their velocities with high reliability. Here we aimed to study how such regression-based control performs in daily life in a two-month case study. The performance is evaluated in functional tests and with a questionnaire at the beginning and the end of this phase and compared with the participant’s own prosthesis, controlled with a classical approach. Already 1 day after training of the regression model, the participant with transradial amputation outperformed the performance achieved with his own Michelangelo hand in two out of three functional metrics. No retraining of the model was required during the entire study duration. During the use of the system at home, the performance improved further and outperformed the conventional control in all three metrics. This study demonstrates that the high fidelity of linear regression-based prosthesis control is not restricted to a laboratory environment, but can be transferred to daily use.
2.
Volkmar, R.; Dosen, S.; Gonzalez-Vargas, J.; Baum, M.; Markovic, M.
Improving bimanual interaction with a prosthesis using semi-autonomous control Artikel
In: J. NeuroEng. Rehabil., Bd. 16, Nr. 1, 2019, ISSN: 1743-0003.
Abstract | Links | Schlagwörter: adult, analytical equipment, article, bimanual interaction, controlled study, female, hand prosthesis, human, human experiment, inertial sensor, limb movement, male, motor control, motor performance, outcome assessment, priority journal, prosthesis, prosthesis design, semi autonomous control, sensor, task performance, vibrotactor, workload
@article{Volkmar2019,
title = {Improving bimanual interaction with a prosthesis using semi-autonomous control},
author = {R. Volkmar and S. Dosen and J. Gonzalez-Vargas and M. Baum and M. Markovic},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L629849607&from=export},
doi = {10.1186/s12984-019-0617-6},
issn = {1743-0003},
year = {2019},
date = {2019-01-01},
journal = {J. NeuroEng. Rehabil.},
volume = {16},
number = {1},
address = {M. Markovic, Department of Trauma Surgery Orthopedics and Plastic Surgery, University Medical Center Göttingen, Von-Siebold-Str. 3, Göttingen, Germany},
abstract = {Background: The loss of a hand is a traumatic experience that substantially compromises an individual's capability to interact with his environment. The myoelectric prostheses are state-of-the-art (SoA) functional replacements for the lost limbs. Their overall mechanical design and dexterity have improved over the last few decades, but the users have not been able to fully exploit these advances because of the lack of effective and intuitive control. Bimanual tasks are particularly challenging for an amputee since prosthesis control needs to be coordinated with the movement of the sound limb. So far, the bimanual activities have been often neglected by the prosthetic research community. Methods: We present a novel method to prosthesis control, which uses a semi-autonomous approach in order to simplify bimanual interactions. The approach supplements the commercial SoA two-channel myoelectric control with two additional sensors. Two inertial measurement units were attached to the prosthesis and the sound hand to detect the movement of both limbs. Once a bimanual interaction is detected, the system mimics the coordination strategies of able-bodied subjects to automatically adjust the prosthesis wrist rotation (pronation, supination) and grip type (lateral, palmar) to assist the sound hand during a bimanual task. The system has been evaluated in eight able-bodied subjects performing functional uni- A nd bi-manual tasks using the novel method and SoA two-channel myocontrol. The outcome measures were time to accomplish the task, semi-autonomous system misclassification rate, subjective rating of intuitiveness, and perceived workload (NASA TLX). Results: The results demonstrated that the novel control interface substantially outperformed the SoA myoelectric control. While using the semi-autonomous control the time to accomplish the task and the perceived workload decreased for 25 and 27%, respectively, while the subjects rated the system as more intuitive then SoA myocontrol. Conclusions: The novel system uses minimal additional hardware (two inertial sensors) and simple processing and it is therefore convenient for practical implementation. By using the proposed control scheme, the prosthesis assists the user's sound hand in performing bimanual interactions while decreasing cognitive burden.},
keywords = {adult, analytical equipment, article, bimanual interaction, controlled study, female, hand prosthesis, human, human experiment, inertial sensor, limb movement, male, motor control, motor performance, outcome assessment, priority journal, prosthesis, prosthesis design, semi autonomous control, sensor, task performance, vibrotactor, workload},
pubstate = {published},
tppubtype = {article}
}
Background: The loss of a hand is a traumatic experience that substantially compromises an individual's capability to interact with his environment. The myoelectric prostheses are state-of-the-art (SoA) functional replacements for the lost limbs. Their overall mechanical design and dexterity have improved over the last few decades, but the users have not been able to fully exploit these advances because of the lack of effective and intuitive control. Bimanual tasks are particularly challenging for an amputee since prosthesis control needs to be coordinated with the movement of the sound limb. So far, the bimanual activities have been often neglected by the prosthetic research community. Methods: We present a novel method to prosthesis control, which uses a semi-autonomous approach in order to simplify bimanual interactions. The approach supplements the commercial SoA two-channel myoelectric control with two additional sensors. Two inertial measurement units were attached to the prosthesis and the sound hand to detect the movement of both limbs. Once a bimanual interaction is detected, the system mimics the coordination strategies of able-bodied subjects to automatically adjust the prosthesis wrist rotation (pronation, supination) and grip type (lateral, palmar) to assist the sound hand during a bimanual task. The system has been evaluated in eight able-bodied subjects performing functional uni- A nd bi-manual tasks using the novel method and SoA two-channel myocontrol. The outcome measures were time to accomplish the task, semi-autonomous system misclassification rate, subjective rating of intuitiveness, and perceived workload (NASA TLX). Results: The results demonstrated that the novel control interface substantially outperformed the SoA myoelectric control. While using the semi-autonomous control the time to accomplish the task and the perceived workload decreased for 25 and 27%, respectively, while the subjects rated the system as more intuitive then SoA myocontrol. Conclusions: The novel system uses minimal additional hardware (two inertial sensors) and simple processing and it is therefore convenient for practical implementation. By using the proposed control scheme, the prosthesis assists the user's sound hand in performing bimanual interactions while decreasing cognitive burden.
3.
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.
4.
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).
2020
Hahne, J. M.; Wilke, M. A.; Koppe, M.; Farina, D.; Schilling, A. F.
Longitudinal Case Study of Regression-Based Hand Prosthesis Control in Daily Life Artikel
In: Front. Neurosci., Bd. 14, 2020, ISSN: 1662-4548.
Abstract | Links | Schlagwörter: adult, arm amputation, article, case study, clinical article, controlled study, electric hand, hand prosthesis, human, longitudinal study, male, middle aged, motor control, questionnaire, regression analysis, VariPlus Speed
@article{Hahne2020,
title = {Longitudinal Case Study of Regression-Based Hand Prosthesis Control in Daily Life},
author = {J. M. Hahne and M. A. Wilke and M. Koppe and D. Farina and A. F. Schilling},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L632229544&from=export},
doi = {10.3389/fnins.2020.00600},
issn = {1662-4548},
year = {2020},
date = {2020-01-01},
journal = {Front. Neurosci.},
volume = {14},
address = {J.M. Hahne, Applied Rehabilitation Technology Lab, Department of Trauma Surgery, Orthopedic Surgery and Hand Surgery, University Medical Center Göttingen, Göttingen, Germany},
abstract = {Hand prostheses are usually controlled by electromyographic (EMG) signals from the remnant muscles of the residual limb. Most prostheses used today are controlled with very simple techniques using only two EMG electrodes that allow to control a single prosthetic function at a time only. Recently, modern prosthesis controllers based on EMG classification, have become clinically available, which allow to directly access more functions, but still in a sequential manner only. We have recently shown in laboratory tests that a regression-based mapping from EMG signals into prosthetic control commands allows for a simultaneous activation of two functions and an independent control of their velocities with high reliability. Here we aimed to study how such regression-based control performs in daily life in a two-month case study. The performance is evaluated in functional tests and with a questionnaire at the beginning and the end of this phase and compared with the participant’s own prosthesis, controlled with a classical approach. Already 1 day after training of the regression model, the participant with transradial amputation outperformed the performance achieved with his own Michelangelo hand in two out of three functional metrics. No retraining of the model was required during the entire study duration. During the use of the system at home, the performance improved further and outperformed the conventional control in all three metrics. This study demonstrates that the high fidelity of linear regression-based prosthesis control is not restricted to a laboratory environment, but can be transferred to daily use.},
keywords = {adult, arm amputation, article, case study, clinical article, controlled study, electric hand, hand prosthesis, human, longitudinal study, male, middle aged, motor control, questionnaire, regression analysis, VariPlus Speed},
pubstate = {published},
tppubtype = {article}
}
Hand prostheses are usually controlled by electromyographic (EMG) signals from the remnant muscles of the residual limb. Most prostheses used today are controlled with very simple techniques using only two EMG electrodes that allow to control a single prosthetic function at a time only. Recently, modern prosthesis controllers based on EMG classification, have become clinically available, which allow to directly access more functions, but still in a sequential manner only. We have recently shown in laboratory tests that a regression-based mapping from EMG signals into prosthetic control commands allows for a simultaneous activation of two functions and an independent control of their velocities with high reliability. Here we aimed to study how such regression-based control performs in daily life in a two-month case study. The performance is evaluated in functional tests and with a questionnaire at the beginning and the end of this phase and compared with the participant’s own prosthesis, controlled with a classical approach. Already 1 day after training of the regression model, the participant with transradial amputation outperformed the performance achieved with his own Michelangelo hand in two out of three functional metrics. No retraining of the model was required during the entire study duration. During the use of the system at home, the performance improved further and outperformed the conventional control in all three metrics. This study demonstrates that the high fidelity of linear regression-based prosthesis control is not restricted to a laboratory environment, but can be transferred to daily use.
2019
Volkmar, R.; Dosen, S.; Gonzalez-Vargas, J.; Baum, M.; Markovic, M.
Improving bimanual interaction with a prosthesis using semi-autonomous control Artikel
In: J. NeuroEng. Rehabil., Bd. 16, Nr. 1, 2019, ISSN: 1743-0003.
Abstract | Links | Schlagwörter: adult, analytical equipment, article, bimanual interaction, controlled study, female, hand prosthesis, human, human experiment, inertial sensor, limb movement, male, motor control, motor performance, outcome assessment, priority journal, prosthesis, prosthesis design, semi autonomous control, sensor, task performance, vibrotactor, workload
@article{Volkmar2019,
title = {Improving bimanual interaction with a prosthesis using semi-autonomous control},
author = {R. Volkmar and S. Dosen and J. Gonzalez-Vargas and M. Baum and M. Markovic},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L629849607&from=export},
doi = {10.1186/s12984-019-0617-6},
issn = {1743-0003},
year = {2019},
date = {2019-01-01},
journal = {J. NeuroEng. Rehabil.},
volume = {16},
number = {1},
address = {M. Markovic, Department of Trauma Surgery Orthopedics and Plastic Surgery, University Medical Center Göttingen, Von-Siebold-Str. 3, Göttingen, Germany},
abstract = {Background: The loss of a hand is a traumatic experience that substantially compromises an individual's capability to interact with his environment. The myoelectric prostheses are state-of-the-art (SoA) functional replacements for the lost limbs. Their overall mechanical design and dexterity have improved over the last few decades, but the users have not been able to fully exploit these advances because of the lack of effective and intuitive control. Bimanual tasks are particularly challenging for an amputee since prosthesis control needs to be coordinated with the movement of the sound limb. So far, the bimanual activities have been often neglected by the prosthetic research community. Methods: We present a novel method to prosthesis control, which uses a semi-autonomous approach in order to simplify bimanual interactions. The approach supplements the commercial SoA two-channel myoelectric control with two additional sensors. Two inertial measurement units were attached to the prosthesis and the sound hand to detect the movement of both limbs. Once a bimanual interaction is detected, the system mimics the coordination strategies of able-bodied subjects to automatically adjust the prosthesis wrist rotation (pronation, supination) and grip type (lateral, palmar) to assist the sound hand during a bimanual task. The system has been evaluated in eight able-bodied subjects performing functional uni- A nd bi-manual tasks using the novel method and SoA two-channel myocontrol. The outcome measures were time to accomplish the task, semi-autonomous system misclassification rate, subjective rating of intuitiveness, and perceived workload (NASA TLX). Results: The results demonstrated that the novel control interface substantially outperformed the SoA myoelectric control. While using the semi-autonomous control the time to accomplish the task and the perceived workload decreased for 25 and 27%, respectively, while the subjects rated the system as more intuitive then SoA myocontrol. Conclusions: The novel system uses minimal additional hardware (two inertial sensors) and simple processing and it is therefore convenient for practical implementation. By using the proposed control scheme, the prosthesis assists the user's sound hand in performing bimanual interactions while decreasing cognitive burden.},
keywords = {adult, analytical equipment, article, bimanual interaction, controlled study, female, hand prosthesis, human, human experiment, inertial sensor, limb movement, male, motor control, motor performance, outcome assessment, priority journal, prosthesis, prosthesis design, semi autonomous control, sensor, task performance, vibrotactor, workload},
pubstate = {published},
tppubtype = {article}
}
Background: The loss of a hand is a traumatic experience that substantially compromises an individual's capability to interact with his environment. The myoelectric prostheses are state-of-the-art (SoA) functional replacements for the lost limbs. Their overall mechanical design and dexterity have improved over the last few decades, but the users have not been able to fully exploit these advances because of the lack of effective and intuitive control. Bimanual tasks are particularly challenging for an amputee since prosthesis control needs to be coordinated with the movement of the sound limb. So far, the bimanual activities have been often neglected by the prosthetic research community. Methods: We present a novel method to prosthesis control, which uses a semi-autonomous approach in order to simplify bimanual interactions. The approach supplements the commercial SoA two-channel myoelectric control with two additional sensors. Two inertial measurement units were attached to the prosthesis and the sound hand to detect the movement of both limbs. Once a bimanual interaction is detected, the system mimics the coordination strategies of able-bodied subjects to automatically adjust the prosthesis wrist rotation (pronation, supination) and grip type (lateral, palmar) to assist the sound hand during a bimanual task. The system has been evaluated in eight able-bodied subjects performing functional uni- A nd bi-manual tasks using the novel method and SoA two-channel myocontrol. The outcome measures were time to accomplish the task, semi-autonomous system misclassification rate, subjective rating of intuitiveness, and perceived workload (NASA TLX). Results: The results demonstrated that the novel control interface substantially outperformed the SoA myoelectric control. While using the semi-autonomous control the time to accomplish the task and the perceived workload decreased for 25 and 27%, respectively, while the subjects rated the system as more intuitive then SoA myocontrol. Conclusions: The novel system uses minimal additional hardware (two inertial sensors) and simple processing and it is therefore convenient for practical implementation. By using the proposed control scheme, the prosthesis assists the user's sound hand in performing bimanual interactions while decreasing cognitive burden.
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.
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).
2020
Hahne, J. M.; Wilke, M. A.; Koppe, M.; Farina, D.; Schilling, A. F.
Longitudinal Case Study of Regression-Based Hand Prosthesis Control in Daily Life Artikel
In: Front. Neurosci., Bd. 14, 2020, ISSN: 1662-4548.
@article{Hahne2020,
title = {Longitudinal Case Study of Regression-Based Hand Prosthesis Control in Daily Life},
author = {J. M. Hahne and M. A. Wilke and M. Koppe and D. Farina and A. F. Schilling},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L632229544&from=export},
doi = {10.3389/fnins.2020.00600},
issn = {1662-4548},
year = {2020},
date = {2020-01-01},
journal = {Front. Neurosci.},
volume = {14},
address = {J.M. Hahne, Applied Rehabilitation Technology Lab, Department of Trauma Surgery, Orthopedic Surgery and Hand Surgery, University Medical Center Göttingen, Göttingen, Germany},
abstract = {Hand prostheses are usually controlled by electromyographic (EMG) signals from the remnant muscles of the residual limb. Most prostheses used today are controlled with very simple techniques using only two EMG electrodes that allow to control a single prosthetic function at a time only. Recently, modern prosthesis controllers based on EMG classification, have become clinically available, which allow to directly access more functions, but still in a sequential manner only. We have recently shown in laboratory tests that a regression-based mapping from EMG signals into prosthetic control commands allows for a simultaneous activation of two functions and an independent control of their velocities with high reliability. Here we aimed to study how such regression-based control performs in daily life in a two-month case study. The performance is evaluated in functional tests and with a questionnaire at the beginning and the end of this phase and compared with the participant’s own prosthesis, controlled with a classical approach. Already 1 day after training of the regression model, the participant with transradial amputation outperformed the performance achieved with his own Michelangelo hand in two out of three functional metrics. No retraining of the model was required during the entire study duration. During the use of the system at home, the performance improved further and outperformed the conventional control in all three metrics. This study demonstrates that the high fidelity of linear regression-based prosthesis control is not restricted to a laboratory environment, but can be transferred to daily use.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hand prostheses are usually controlled by electromyographic (EMG) signals from the remnant muscles of the residual limb. Most prostheses used today are controlled with very simple techniques using only two EMG electrodes that allow to control a single prosthetic function at a time only. Recently, modern prosthesis controllers based on EMG classification, have become clinically available, which allow to directly access more functions, but still in a sequential manner only. We have recently shown in laboratory tests that a regression-based mapping from EMG signals into prosthetic control commands allows for a simultaneous activation of two functions and an independent control of their velocities with high reliability. Here we aimed to study how such regression-based control performs in daily life in a two-month case study. The performance is evaluated in functional tests and with a questionnaire at the beginning and the end of this phase and compared with the participant’s own prosthesis, controlled with a classical approach. Already 1 day after training of the regression model, the participant with transradial amputation outperformed the performance achieved with his own Michelangelo hand in two out of three functional metrics. No retraining of the model was required during the entire study duration. During the use of the system at home, the performance improved further and outperformed the conventional control in all three metrics. This study demonstrates that the high fidelity of linear regression-based prosthesis control is not restricted to a laboratory environment, but can be transferred to daily use.
2019
Volkmar, R.; Dosen, S.; Gonzalez-Vargas, J.; Baum, M.; Markovic, M.
Improving bimanual interaction with a prosthesis using semi-autonomous control Artikel
In: J. NeuroEng. Rehabil., Bd. 16, Nr. 1, 2019, ISSN: 1743-0003.
@article{Volkmar2019,
title = {Improving bimanual interaction with a prosthesis using semi-autonomous control},
author = {R. Volkmar and S. Dosen and J. Gonzalez-Vargas and M. Baum and M. Markovic},
url = {https://www.embase.com/search/results?subaction=viewrecord&id=L629849607&from=export},
doi = {10.1186/s12984-019-0617-6},
issn = {1743-0003},
year = {2019},
date = {2019-01-01},
journal = {J. NeuroEng. Rehabil.},
volume = {16},
number = {1},
address = {M. Markovic, Department of Trauma Surgery Orthopedics and Plastic Surgery, University Medical Center Göttingen, Von-Siebold-Str. 3, Göttingen, Germany},
abstract = {Background: The loss of a hand is a traumatic experience that substantially compromises an individual's capability to interact with his environment. The myoelectric prostheses are state-of-the-art (SoA) functional replacements for the lost limbs. Their overall mechanical design and dexterity have improved over the last few decades, but the users have not been able to fully exploit these advances because of the lack of effective and intuitive control. Bimanual tasks are particularly challenging for an amputee since prosthesis control needs to be coordinated with the movement of the sound limb. So far, the bimanual activities have been often neglected by the prosthetic research community. Methods: We present a novel method to prosthesis control, which uses a semi-autonomous approach in order to simplify bimanual interactions. The approach supplements the commercial SoA two-channel myoelectric control with two additional sensors. Two inertial measurement units were attached to the prosthesis and the sound hand to detect the movement of both limbs. Once a bimanual interaction is detected, the system mimics the coordination strategies of able-bodied subjects to automatically adjust the prosthesis wrist rotation (pronation, supination) and grip type (lateral, palmar) to assist the sound hand during a bimanual task. The system has been evaluated in eight able-bodied subjects performing functional uni- A nd bi-manual tasks using the novel method and SoA two-channel myocontrol. The outcome measures were time to accomplish the task, semi-autonomous system misclassification rate, subjective rating of intuitiveness, and perceived workload (NASA TLX). Results: The results demonstrated that the novel control interface substantially outperformed the SoA myoelectric control. While using the semi-autonomous control the time to accomplish the task and the perceived workload decreased for 25 and 27%, respectively, while the subjects rated the system as more intuitive then SoA myocontrol. Conclusions: The novel system uses minimal additional hardware (two inertial sensors) and simple processing and it is therefore convenient for practical implementation. By using the proposed control scheme, the prosthesis assists the user's sound hand in performing bimanual interactions while decreasing cognitive burden.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background: The loss of a hand is a traumatic experience that substantially compromises an individual's capability to interact with his environment. The myoelectric prostheses are state-of-the-art (SoA) functional replacements for the lost limbs. Their overall mechanical design and dexterity have improved over the last few decades, but the users have not been able to fully exploit these advances because of the lack of effective and intuitive control. Bimanual tasks are particularly challenging for an amputee since prosthesis control needs to be coordinated with the movement of the sound limb. So far, the bimanual activities have been often neglected by the prosthetic research community. Methods: We present a novel method to prosthesis control, which uses a semi-autonomous approach in order to simplify bimanual interactions. The approach supplements the commercial SoA two-channel myoelectric control with two additional sensors. Two inertial measurement units were attached to the prosthesis and the sound hand to detect the movement of both limbs. Once a bimanual interaction is detected, the system mimics the coordination strategies of able-bodied subjects to automatically adjust the prosthesis wrist rotation (pronation, supination) and grip type (lateral, palmar) to assist the sound hand during a bimanual task. The system has been evaluated in eight able-bodied subjects performing functional uni- A nd bi-manual tasks using the novel method and SoA two-channel myocontrol. The outcome measures were time to accomplish the task, semi-autonomous system misclassification rate, subjective rating of intuitiveness, and perceived workload (NASA TLX). Results: The results demonstrated that the novel control interface substantially outperformed the SoA myoelectric control. While using the semi-autonomous control the time to accomplish the task and the perceived workload decreased for 25 and 27%, respectively, while the subjects rated the system as more intuitive then SoA myocontrol. Conclusions: The novel system uses minimal additional hardware (two inertial sensors) and simple processing and it is therefore convenient for practical implementation. By using the proposed control scheme, the prosthesis assists the user's sound hand in performing bimanual interactions while decreasing cognitive burden.
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.
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).