Vujaklija, Ivan

[["dc.bibliographiccitation.artnumber","eaau2956"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Science Advances"],["dc.bibliographiccitation.lastpage","eaau2956"],["dc.bibliographiccitation.volume","5"],["dc.contributor.author","Bergmeister, Konstantin D."],["dc.contributor.author","Aman, Martin"],["dc.contributor.author","Muceli, Silvia"],["dc.contributor.author","Vujaklija, Ivan"],["dc.contributor.author","Manzano-Szalai, Krisztina"],["dc.contributor.author","Unger, Ewald"],["dc.contributor.author","Byrne, Ruth A."],["dc.contributor.author","Scheinecker, Clemens"],["dc.contributor.author","Riedl, Otto"],["dc.contributor.author","Salminger, Stefan"],["dc.contributor.author","Frommlet, Florian"],["dc.contributor.author","Borschel, Gregory H."],["dc.contributor.author","Farina, Dario"],["dc.contributor.author","Aszmann, Oskar C."],["dc.date.accessioned","2019-07-09T11:50:25Z"],["dc.date.available","2019-07-09T11:50:25Z"],["dc.date.issued","2019"],["dc.description.abstract","Selective nerve transfers surgically rewire motor neurons and are used in extremity reconstruction to restore muscle function or to facilitate intuitive prosthetic control. We investigated the neurophysiological effects of rewiring motor axons originating from spinal motor neuron pools into target muscles with lower innervation ratio in a rat model. Following reinnervation, the target muscle's force regenerated almost completely, with the motor unit population increasing to 116% in functional and 172% in histological assessments with subsequently smaller muscle units. Muscle fiber type populations transformed into the donor nerve's original muscles. We thus demonstrate that axons of alternative spinal origin can hyper-reinnervate target muscles without loss of muscle force regeneration, but with a donor-specific shift in muscle fiber type. These results explain the excellent clinical outcomes following nerve transfers in neuromuscular reconstruction. They indicate that reinnervated muscles can provide an accurate bioscreen to display neural information of lost body parts for high-fidelity prosthetic control."],["dc.identifier.doi","10.1126/sciadv.aau2956"],["dc.identifier.pmid","30613770"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15938"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59771"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation","info:eu-repo/grantAgreement/EC/FP7/267888/EU//DEMOVE"],["dc.relation.issn","2375-2548"],["dc.rights","CC BY-NC 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by-nc/4.0"],["dc.subject.ddc","610"],["dc.title","Peripheral nerve transfers change target muscle structure and function"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","47"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of NeuroEngineering and Rehabilitation"],["dc.bibliographiccitation.volume","16"],["dc.contributor.author","Kapelner, Tamás"],["dc.contributor.author","Vujaklija, Ivan"],["dc.contributor.author","Jiang, Ning"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Aszmann, Oskar C."],["dc.contributor.author","Principe, Jose"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2019-07-09T11:51:40Z"],["dc.date.available","2019-07-09T11:51:40Z"],["dc.date.issued","2019"],["dc.description.abstract","BACKGROUND: Current myoelectric control algorithms for active prostheses map time- and frequency-domain features of the interference EMG signal into prosthesis commands. With this approach, only a fraction of the available information content of the EMG is used and the resulting control fails to satisfy the majority of users. In this study, we predict joint angles of the three degrees of freedom of the wrist from motor unit discharge timings identified by decomposition of high-density surface EMG. METHODS: We recorded wrist kinematics and high-density surface EMG signals from six able-bodied individuals and one patient with limb deficiency while they performed movements of three degrees of freedom of the wrist at three different speeds. We compared the performance of linear regression to predict the observed individual wrist joint angles from, either traditional time domain features of the interference EMG or from motor unit discharge timings (which we termed neural features) obtained by EMG decomposition. In addition, we propose and test a simple model-based dimensionality reduction, based on the physiological notion that the discharge timings of motor units are partly correlated. RESULTS: The regression approach using neural features outperformed regression on classic global EMG features (average R2 for neural features 0.77 and 0.64, for able-bodied subjects and patients, respectively; for time-domain features 0.70 and 0.52). CONCLUSIONS: These results indicate that the use of neural information extracted from EMG decomposition can advance man-machine interfacing for prosthesis control."],["dc.identifier.doi","10.1186/s12984-019-0516-x"],["dc.identifier.pmid","30953528"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/16168"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59987"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation","info:eu-repo/grantAgreement/EC/FP7/267888/EU//DEMOVE"],["dc.relation","info:eu-repo/grantAgreement/EC/H2020/737570/EU//INTERSPINE"],["dc.relation","info:eu-repo/grantAgreement/EC/H2020/702491/EU//NeuralCon"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject.ddc","610"],["dc.title","Predicting wrist kinematics from motor unit discharge timings for the control of active prostheses"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","421"],["dc.bibliographiccitation.journal","Frontiers in Neuroscience"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Bergmeister, Konstantin D."],["dc.contributor.author","Vujaklija, Ivan"],["dc.contributor.author","Muceli, Silvia"],["dc.contributor.author","Sturma, Agnes"],["dc.contributor.author","Hruby, Laura A."],["dc.contributor.author","Prahm, Cosima"],["dc.contributor.author","Riedl, Otto"],["dc.contributor.author","Salminger, Stefan"],["dc.contributor.author","Manzano-Szalai, Krisztina"],["dc.contributor.author","Aman, Martin"],["dc.contributor.author","Russold, Michael-Friedrich"],["dc.contributor.author","Hofer, Christian"],["dc.contributor.author","Principe, Jose"],["dc.contributor.author","Farina, Dario"],["dc.contributor.author","Aszmann, Oskar C."],["dc.date.accessioned","2019-07-09T11:44:48Z"],["dc.date.available","2019-07-09T11:44:48Z"],["dc.date.issued","2017"],["dc.description.abstract","Modern robotic hands/upper limbs may replace multiple degrees of freedom of extremity function. However, their intuitive use requires a high number of control signals, which current man-machine interfaces do not provide. Here, we discuss a broadband control interface that combines targeted muscle reinnervation, implantable multichannel electromyographic sensors, and advanced decoding to address the increasing capabilities of modern robotic limbs. With targeted muscle reinnervation, nerves that have lost their targets due to an amputation are surgically transferred to residual stump muscles to increase the number of intuitive prosthetic control signals. This surgery re-establishes a nerve-muscle connection that is used for sensing nerve activity with myoelectric interfaces. Moreover, the nerve transfer determines neurophysiological effects, such as muscular hyper-reinnervation and cortical reafferentation that can be exploited by the myoelectric interface. Modern implantable multichannel EMG sensors provide signals from which it is possible to disentangle the behavior of single motor neurons. Recent studies have shown that the neural drive to muscles can be decoded from these signals and thereby the user’s intention can be reliably estimated. By combining these concepts in chronic implants and embedded electronics, we believe that it is in principle possible to establish a broadband man-machine interface, with specific applications in prosthesis control. This perspective illustrates this concept, based on combining advanced surgical techniques with recording hardware and processing algorithms. Here we describe the scientific evidence for this concept, current state of investigations, challenges, and alternative approaches to improve current prosthetic interfaces."],["dc.identifier.doi","10.3389/fnins.2017.00421"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/14912"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59101"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation","info:eu-repo/grantAgreement/EC/FP7/267888/EU//DEMOVE"],["dc.relation.issn","1662-453X"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject.ddc","610"],["dc.title","Broadband Prosthetic Interfaces: Combining Nerve Transfers and Implantable Multichannel EMG Technology to Decode Spinal Motor Neuron Activity"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]