Marković, Marko

[["dc.bibliographiccitation.artnumber","55"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of NeuroEngineering and Rehabilitation"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Dosen, Strahinja"],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Somer, Kelef"],["dc.contributor.author","Graimann, Bernhard"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2019-07-09T11:41:46Z"],["dc.date.available","2019-07-09T11:41:46Z"],["dc.date.issued","2015"],["dc.description.abstract","Background Active hand prostheses controlled using electromyography (EMG) signals have been used for decades to restore the grasping function, lost after an amputation. Although myocontrol is a simple and intuitive interface, it is also imprecise due to the stochastic nature of the EMG recorded using surface electrodes. Furthermore, the sensory feedback from the prosthesis to the user is still missing. In this study, we present a novel concept to close the loop in myoelectric prostheses. In addition to conveying the grasping force (system output), we provided to the user the online information about the system input (EMG biofeedback). Methods As a proof-of-concept, the EMG biofeedback was transmitted in the current study using a visual interface (ideal condition). Ten able-bodied subjects and two amputees controlled a state-of-the-art myoelectric prosthesis in routine grasping and force steering tasks using EMG and force feedback (novel approach) and force feedback only (classic approach). The outcome measures were the variability of the generated forces and absolute deviation from the target levels in the routine grasping task, and the root mean square tracking error and the number of sudden drops in the force steering task. Results During the routine grasping, the novel method when used by able-bodied subjects decreased twofold the force dispersion as well as absolute deviations from the target force levels, and also resulted in a more accurate and stable tracking of the reference force profiles during the force steering. Furthermore, the force variability during routine grasping did not increase for the higher target forces with EMG biofeedback. The trend was similar in the two amputees. Conclusions The study demonstrated that the subjects, including the two experienced users of a myoelectric prosthesis, were able to exploit the online EMG biofeedback to observe and modulate the myoelectric signals, generating thereby more consistent commands. This allowed them to control the force predictively (routine grasping) and with a finer resolution (force steering). The future step will be to implement this promising and simple approach using an electrotactile interface. A prosthesis with a reliable response, following faithfully user intentions, would improve the utility during daily-life use and also facilitate the embodiment of the assistive system."],["dc.identifier.doi","10.1186/s12984-015-0047-z"],["dc.identifier.pmid","26088323"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/12335"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/58507"],["dc.language.iso","en"],["dc.relation","info:eu-repo/grantAgreement/EC/FP7/286208/EU//MYOSENS"],["dc.relation.euproject","MYOSENS"],["dc.rights.access","openAccess"],["dc.rights.holder","Dosen et al."],["dc.title","EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["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"]]