Dosen, Strahinja

[["dc.bibliographiccitation.artnumber","114"],["dc.bibliographiccitation.journal","Frontiers in Computational Neuroscience"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Gonzalez-Vargas, Jose"],["dc.contributor.author","Sartori, Massimo"],["dc.contributor.author","Dosen, Strahinja"],["dc.contributor.author","Torricelli, Diego"],["dc.contributor.author","Pons, Jose L."],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:51:34Z"],["dc.date.available","2018-11-07T09:51:34Z"],["dc.date.issued","2015"],["dc.description.abstract","Humans can efficiently walk across a large variety of terrains and locomotion conditions with little or no mental effort. It has been hypothesized that the nervous system simplifies neuromuscular control by using muscle synergies, thus organizing multi-muscle activity into a small number of coordinative co-activation modules. In the present study we investigated how muscle modularity is structured across a large repertoire of locomotion conditions including five different speeds and five different ground elevations. For this we have used the non-negative matrix factorization technique in order to explain EMG experimental data with a low-dimensional set of four motor components. In this context each motor components is composed of a non-negative factor and the associated muscle weightings. Furthermore, we have investigated if the proposed descriptive analysis of muscle modularity could be translated into a predictive model that could: (1) Estimate how motor components modulate across locomotion speeds and ground elevations. This implies not only estimating the non-negative factors temporal characteristics, but also the associated muscle weighting variations. (2) Estimate how the resulting muscle excitations modulate across novel locomotion conditions and subjects. The results showed three major distinctive features of muscle modularity: (1) the number of motor components was preserved across all locomotion conditions, (2) the non negative factors were consistent in shape and timing across all locomotion conditions, and (3) the muscle weightings were modulated as distinctive functions of locomotion speed and ground elevation. Results also showed that the developed predictive model was able to reproduce well the muscle modularity of un-modeled data, i.e., novel subjects and conditions. Muscle weightings were reconstructed with a cross-correlation factor greater than 70% and a root mean square error less than 0.10. Furthermore, the generated muscle excitations matched well the experimental excitation with a cross correlation factor greater than 85% and a root mean square error less than 0.09. The ability of synthetizing the neuromuscular mechanisms underlying human locomotion across a variety of locomotion conditions will enable solutions in the field of neurorehabilitation technologies and control of bipedal artificial systems. Open access of the model implementation is provided for further analysis at https://simtk.org/home/p-mep/."],["dc.description.sponsorship","Open-Access Publikationsfonds 2015"],["dc.identifier.doi","10.3389/fncom.2015.00114"],["dc.identifier.isi","000361631700001"],["dc.identifier.pmid","26441624"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/12160"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35943"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Frontiers Media Sa"],["dc.relation.issn","1662-5188"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","A predictive model of muscle excitations based on muscle modularity for a large repertoire of human locomotion conditions"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e0127528"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","PLoS ONE"],["dc.bibliographiccitation.volume","10"],["dc.contributor.author","Gonzalez-Vargas, Jose"],["dc.contributor.author","Dosen, Strahinja"],["dc.contributor.author","Amsuess, Sebastian"],["dc.contributor.author","Yu, Wenwei"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:55:54Z"],["dc.date.available","2018-11-07T09:55:54Z"],["dc.date.issued","2015"],["dc.description.abstract","Modern assistive devices are very sophisticated systems with multiple degrees of freedom. However, an effective and user-friendly control of these systems is still an open problem since conventional human-machine interfaces (HMI) cannot easily accommodate the system's complexity. In HMIs, the user is responsible for generating unique patterns of command signals directly triggering the device functions. This approach can be difficult to implement when there are many functions (necessitating many command patterns) and/or the user has a considerable impairment (limited number of available signal sources). In this study, we propose a novel concept for a general-purpose HMI where the controller and the user communicate bidirectionally to select the desired function. The system first presents possible choices to the user via electro-tactile stimulation; the user then acknowledges the desired choice by generating a single command signal. Therefore, the proposed approach simplifies the user communication interface (one signal to generate), decoding (one signal to recognize), and allows selecting from a number of options. To demonstrate the new concept the method was used in one particular application, namely, to implement the control of all the relevant functions in a state of the art commercial prosthetic hand without using any myoelectric channels. We performed experiments in healthy subjects and with one amputee to test the feasibility of the novel approach. The results showed that the performance of the novel HMI concept was comparable or, for some outcome measures, better than the classic myoelectric interfaces. The presented approach has a general applicability and the obtained results point out that it could be used to operate various assistive systems (e.g., prosthesis vs. wheelchair), or it could be integrated into other control schemes (e.g., myoelectric control, brain-machine interfaces) in order to improve the usability of existing low-bandwidth HMIs."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2015"],["dc.identifier.doi","10.1371/journal.pone.0127528"],["dc.identifier.isi","000356327000009"],["dc.identifier.pmid","26069961"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/11958"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/36851"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Public Library Science"],["dc.relation.issn","1932-6203"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Human-Machine Interface for the Control of Multi-Function Systems Based on Electrocutaneous Menu: Application to Multi-Grasp Prosthetic Hands"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of NeuroEngineering and Rehabilitation"],["dc.bibliographiccitation.volume","16"],["dc.contributor.author","Volkmar, Robin"],["dc.contributor.author","Dosen, Strahinja"],["dc.contributor.author","Gonzalez-Vargas, Jose"],["dc.contributor.author","Baum, Marcus"],["dc.contributor.author","Markovic, Marko"],["dc.date.accessioned","2020-12-10T18:39:01Z"],["dc.date.available","2020-12-10T18:39:01Z"],["dc.date.issued","2019"],["dc.identifier.doi","10.1186/s12984-019-0617-6"],["dc.identifier.eissn","1743-0003"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/16682"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/77511"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.notes.intern","Merged from goescholar"],["dc.relation.orgunit","Fakultät für Mathematik und Informatik"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Improving bimanual interaction with a prosthesis using semi-autonomous control"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]