Schweisfurth, Meike Annika

[["dc.bibliographiccitation.firstpage","2547"],["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","Experimental Brain Research"],["dc.bibliographiccitation.lastpage","2559"],["dc.bibliographiccitation.volume","235"],["dc.contributor.author","De Nunzio, Alessandro Marco"],["dc.contributor.author","Dosen, Strahinja"],["dc.contributor.author","Lemling, Sabrina"],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Schweisfurth, Meike Annika"],["dc.contributor.author","Ge, Nan"],["dc.contributor.author","Graimann, Bernhard"],["dc.contributor.author","Falla, Deborah"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2019-07-09T11:44:27Z"],["dc.date.available","2019-07-09T11:44:27Z"],["dc.date.issued","2017"],["dc.description.abstract","Grasping is a complex task routinely performed in an anticipatory (feedforward) manner, where sensory feedback is responsible for learning and updating the internal model of grasp dynamics. This study aims at evaluating whether providing a proportional tactile force feedback during the myoelectric control of a prosthesis facilitates learning a stable internal model of the prosthesis force control. Ten able-bodied subjects controlled a sensorized myoelectric prosthesis performing four blocks of consecutive grasps at three levels of target force (30, 50, and 70%), repeatedly closing the fully opened hand. In the first and third block, the subjects received tactile and visual feedback, respectively, while during the second and fourth block, the feedback was removed. The subjects also performed an additional block with no feedback 1 day after the training (Retest). The median and interquartile range of the generated forces was computed to assess the accuracy and precision of force control. The results demonstrated that the feedback was indeed an effective instrument for the training of prosthesis control. After the training, the subjects were still able to accurately generate the desired force for the low and medium target (30 and 50% of maximum force available in a prosthesis), despite the feedback being removed within the session and during the retest (low target force). However, the training was substantially less successful for high forces (70% of prosthesis maximum force), where subjects exhibited a substantial loss of accuracy as soon as the feedback was removed. The precision of control decreased with higher forces and it was consistent across conditions, determined by an intrinsic variability of repeated myoelectric grasping. This study demonstrated that the subject could rely on the tactile feedback to adjust the motor command to the prosthesis across trials. The subjects adjusted the mean level of muscle activation (accuracy), whereas the precision could not be modulated as it depends on the intrinsic myoelectric variability. They were also able to maintain the feedforward command even after the feedback was removed, demonstrating thereby a stable learning, but the retention depended on the level of the target force. This is an important insight into the role of feedback as an instrument for learning of anticipatory prosthesis force control."],["dc.identifier.doi","10.1007/s00221-017-4991-7"],["dc.identifier.pmid","28550423"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/14765"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59015"],["dc.notes.intern","Merged from goescholar"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Tactile feedback is an effective instrument for the training of grasping with a prosthesis at low- and medium-force levels"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","498"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","IEEE Transactions on Neural Systems and Rehabilitation Engineering"],["dc.bibliographiccitation.lastpage","507"],["dc.bibliographiccitation.volume","28"],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Varel, Marc"],["dc.contributor.author","Schweisfurth, Meike A."],["dc.contributor.author","Schilling, Arndt F."],["dc.contributor.author","Dosen, Strahinja"],["dc.date.accessioned","2021-04-14T08:27:31Z"],["dc.date.available","2021-04-14T08:27:31Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1109/TNSRE.2019.2959714"],["dc.identifier.eissn","1558-0210"],["dc.identifier.issn","1534-4320"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/82316"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","1558-0210"],["dc.relation.issn","1534-4320"],["dc.title","Closed-Loop Multi-Amplitude Control for Robust and Dexterous Performance of Myoelectric Prosthesis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of NeuroEngineering and Rehabilitation"],["dc.bibliographiccitation.volume","15"],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Schweisfurth, Meike A."],["dc.contributor.author","Engels, Leonard F."],["dc.contributor.author","Bentz, Tashina"],["dc.contributor.author","Wüstefeld, Daniela"],["dc.contributor.author","Farina, Dario"],["dc.contributor.author","Dosen, Strahinja"],["dc.date.accessioned","2020-12-10T18:39:00Z"],["dc.date.available","2020-12-10T18:39:00Z"],["dc.date.issued","2018"],["dc.identifier.doi","10.1186/s12984-018-0371-1"],["dc.identifier.eissn","1743-0003"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15495"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/77510"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.notes.intern","Merged from goescholar"],["dc.notes.intern","In goescholar not merged with http://resolver.sub.uni-goettingen.de/purl?gs-1/15150 but duplicate"],["dc.relation","info:eu-repo/grantAgreement/EC/FP7/286208/EU//MYOSENS"],["dc.rights","CC BY 4.0"],["dc.rights.holder","The Author(s)."],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","The clinical relevance of advanced artificial feedback in the control of a multi-functional myoelectric prosthesis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","056010"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Journal of Neural Engineering"],["dc.bibliographiccitation.volume","13"],["dc.contributor.author","Schweisfurth, Meike A."],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Dosen, Strahinja"],["dc.contributor.author","Teich, Florian"],["dc.contributor.author","Graimann, Bernhard"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T10:08:08Z"],["dc.date.available","2018-11-07T10:08:08Z"],["dc.date.issued","2016"],["dc.description.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)."],["dc.description.sponsorship","European Commission under the MYOSENS [FP7-PEOPLE-2011-IAPP-286208]"],["dc.identifier.doi","10.1088/1741-2560/13/5/056010"],["dc.identifier.isi","000384023800003"],["dc.identifier.pmid","27547992"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/39414"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Iop Publishing Ltd"],["dc.relation.issn","1741-2552"],["dc.relation.issn","1741-2560"],["dc.title","Electrotactile EMG feedback improves the control of prosthesis grasping force"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","81"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of NeuroEngineering and Rehabilitation"],["dc.bibliographiccitation.volume","15"],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Schweisfurth, Meike A."],["dc.contributor.author","Engels, Leonard F."],["dc.contributor.author","Farina, Dario"],["dc.contributor.author","Dosen, Strahinja"],["dc.date.accessioned","2019-07-09T11:45:50Z"],["dc.date.available","2019-07-09T11:45:50Z"],["dc.date.issued","2018"],["dc.description.abstract","Abstract Background Sensory feedback is critical for grasping in able-bodied subjects. Consequently, closing the loop in upper-limb prosthetics by providing artificial sensory feedback to the amputee is expected to improve the prosthesis utility. Nevertheless, even though amputees rate the prospect of sensory feedback high, its benefits in daily life are still very much debated. We argue that in order to measure the potential functional benefit of artificial sensory feedback, the baseline open-loop performance needs to be established. Methods The myoelectric control of naïve able-bodied subjects was evaluated during modulation of electromyographic signals (EMG task), and grasping with a prosthesis (Prosthesis task). The subjects needed to activate the wrist flexor muscles and close the prosthesis to reach a randomly selected target level (routine grasping). To assess the baseline performance, the tasks were performed with a different extent of implicit feedback (proprioception, prosthesis motion and sound). Finally, the prosthesis task was repeated with explicit visual force feedback. The subjects’ ability to scale the prosthesis command/force was assessed by testing for a statistically significant increase in the median of the generated commands/forces between neighboring levels. The quality of control was evaluated by computing the median absolute error (MAE) with respect to the target. Results The subjects could successfully scale their motor commands and generated prosthesis forces across target levels in all tasks, even with the least amount of implicit feedback (only muscle proprioception, EMG task). In addition, the deviation of the generated commands/forces from the target levels decreased with additional feedback. However, the increase in implicit feedback, from proprioception to prosthesis motion and sound, seemed to have a more substantial effect than the final introduction of explicit feedback. Explicit feedback improved the performance mainly at the higher target-force levels. Conclusions The study establishes the baseline performance of myoelectric control and prosthesis grasping force. The results demonstrate that even without additional feedback, naïve subjects can effectively modulate force with good accuracy with respect to that achieved when increasing the amount of feedback information."],["dc.description.sponsorship","Open-Access Publikationsfonds 2018"],["dc.identifier.doi","10.1186/s12984-018-0422-7"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15324"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59317"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.intern","In goescholar not merged with http://resolver.sub.uni-goettingen.de/purl?gs-1/15926 but duplicate"],["dc.publisher","BioMed Central"],["dc.rights","CC BY 4.0"],["dc.rights.holder","The Author(s)."],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Myocontrol is closed-loop control: incidental feedback is sufficient for scaling the prosthesis force in routine grasping"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]