Marković, Marko

[["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.firstpage","267"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","IEEE Transactions on Neural Systems and Rehabilitation Engineering"],["dc.bibliographiccitation.lastpage","276"],["dc.bibliographiccitation.volume","23"],["dc.contributor.author","Dosen, Strahinja"],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Hartmann, Cornelia"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T10:00:17Z"],["dc.date.available","2018-11-07T10:00:17Z"],["dc.date.issued","2015"],["dc.description.abstract","Closing the control loop by providing sensory feedback to the user of a prosthesis is an important challenge, with major impact on the future of prosthetics. Developing and comparing closed-loop systems is a difficult task, since there are many different methods and technologies that can be used to implement each component of the system. Here, we present a test bench developed in Matlab Simulink for configuring and testing the closed-loop human control system in standardized settings. The framework comprises a set of connected generic blocks with normalized inputs and outputs, which can be customized by selecting specific implementations from a library of predefined components. The framework is modular and extensible and it can be used to configure, compare and test different closed-loop system prototypes, thereby guiding the development towards an optimal system configuration. The use of the test bench was demonstrated by investigating two important aspects of closed-loop control: performance of different electrotactile feedback interfaces (spatial versus intensity coding) during a pendulum stabilization task and feedforward methods (joystick versus myocontrol) for force control. The first experiment demonstrated that in the case of trained subjects the intensity coding might be superior to spatial coding. In the second experiment, the control of force was rather poor even with a stable and precise control interface (joystick), demonstrating that inherent characteristics of the prosthesis can be an important limiting factor when considering the overall effectiveness of the closed-loop control. The presented test bench is an important instrument for investigating different aspects of human manual control with sensory feedback."],["dc.identifier.doi","10.1109/TNSRE.2014.2371238"],["dc.identifier.isi","000351365100013"],["dc.identifier.pmid","25420268"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/37769"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Ieee-inst Electrical Electronics Engineers Inc"],["dc.relation.issn","1558-0210"],["dc.relation.issn","1534-4320"],["dc.title","Sensory Feedback in Prosthetics: A Standardized Test Bench for Closed-Loop Control"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1298"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","IEEE Transactions on Robotics"],["dc.bibliographiccitation.lastpage","1312"],["dc.bibliographiccitation.volume","37"],["dc.contributor.author","Mouchoux, Jeremy"],["dc.contributor.author","Carisi, Stefano"],["dc.contributor.author","Dosen, Strahinja"],["dc.contributor.author","Farina, Dario"],["dc.contributor.author","Schilling, Arndt F."],["dc.contributor.author","Markovic, Marko"],["dc.date.accessioned","2021-09-01T06:42:04Z"],["dc.date.available","2021-09-01T06:42:04Z"],["dc.date.issued","2021"],["dc.identifier.doi","10.1109/TRO.2020.3047013"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/88973"],["dc.notes.intern","DOI-Import GROB-455"],["dc.relation.eissn","1941-0468"],["dc.relation.issn","1552-3098"],["dc.title","Artificial Perception and Semiautonomous Control in Myoelectric Hand Prostheses Increases Performance and Decreases Effort"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","066022"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Journal of Neural Engineering"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Dosen, Strahinja"],["dc.contributor.author","Popovic, Dejan"],["dc.contributor.author","Graimann, Bernhard"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:47:53Z"],["dc.date.available","2018-11-07T09:47:53Z"],["dc.date.issued","2015"],["dc.description.abstract","Objective. Myoelectric activity volitionally generated by the user is often used for controlling hand prostheses in order to replicate the synergistic actions of muscles in healthy humans during grasping. Muscle synergies in healthy humans are based on the integration of visual perception, heuristics and proprioception. Here, we demonstrate how sensor fusion that combines artificial vision and proprioceptive information with the high-level processing characteristics of biological systems can be effectively used in transradial prosthesis control. Approach. We developed a novel context-and user-aware prosthesis (CASP) controller integrating computer vision and inertial sensing with myoelectric activity in order to achieve semi-autonomous and reactive control of a prosthetic hand. The presented method semiautomatically provides simultaneous and proportional control of multiple degrees-of-freedom (DOFs), thus decreasing overall physical effort while retaining full user control. The system was compared against the major commercial state-of-the art myoelectric control system in ten able-bodied and one amputee subject. All subjects used transradial prosthesis with an active wrist to grasp objects typically associated with activities of daily living. Main results. The CASP significantly outperformed the myoelectric interface when controlling all of the prosthesis DOF. However, when tested with less complex prosthetic system (smaller number of DOF), the CASP was slower but resulted with reaching motions that contained less compensatory movements. Another important finding is that the CASP system required minimal user adaptation and training. Significance. The CASP constitutes a substantial improvement for the control of multi-DOF prostheses. The application of the CASP will have a significant impact when translated to real-life scenarious, particularly with respect to improving the usability and acceptance of highly complex systems (e.g., full prosthetic arms) by amputees."],["dc.identifier.doi","10.1088/1741-2560/12/6/066022"],["dc.identifier.isi","000374884100022"],["dc.identifier.pmid","26529274"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35190"],["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","Sensor fusion and computer vision for context-aware control of a multi degree-of-freedom prosthesis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","583"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","IEEE Transactions on Human-Machine Systems"],["dc.bibliographiccitation.lastpage","589"],["dc.bibliographiccitation.volume","47"],["dc.contributor.author","Clemente, Francesco"],["dc.contributor.author","Dosen, Strahinja"],["dc.contributor.author","Lonini, Luca"],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Farina, Dario"],["dc.contributor.author","Cipriani, Christian"],["dc.date.accessioned","2020-12-10T18:26:17Z"],["dc.date.available","2020-12-10T18:26:17Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1109/THMS.2016.2611998"],["dc.identifier.eissn","2168-2305"],["dc.identifier.issn","2168-2291"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/76024"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Humans Can Integrate Augmented Reality Feedback in Their Sensorimotor Control of a Robotic Hand"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","046001"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Journal of Neural Engineering"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Dosen, Strahinja"],["dc.contributor.author","Cipriani, Christian"],["dc.contributor.author","Popovic, Dejan"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:37:10Z"],["dc.date.available","2018-11-07T09:37:10Z"],["dc.date.issued","2014"],["dc.description.abstract","Objective. Technologically advanced assistive devices are nowadays available to restore grasping, but effective and effortless control integrating both feed-forward (commands) and feedback (sensory information) is still missing. The goal of this work was to develop a user friendly interface for the semi-automatic and closed-loop control of grasping and to test its feasibility. Approach. We developed a controller based on stereovision to automatically select grasp type and size and augmented reality (AR) to provide artificial proprioceptive feedback. The system was experimentally tested in healthy subjects using a dexterous hand prosthesis to grasp a set of daily objects. The subjects wore AR glasses with an integrated stereo-camera pair, and triggered the system via a simple myoelectric interface. Main results. The results demonstrated that the subjects got easily acquainted with the semi-autonomous control. The stereovision grasp decoder successfully estimated the grasp type and size in realistic, cluttered environments. When allowed (forced) to correct the automatic system decisions, the subjects successfully utilized the AR feedback and achieved close to ideal system performance. Significance. The new method implements a high level, low effort control of complex functions in addition to the low level closed-loop control. The latter is achieved by providing rich visual feedback, which is integrated into the real life environment. The proposed system is an effective interface applicable with small alterations for many advanced prosthetic and orthotic/therapeutic rehabilitation devices."],["dc.identifier.doi","10.1088/1741-2560/11/4/046001"],["dc.identifier.isi","000340046500001"],["dc.identifier.pmid","24891493"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/32777"],["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","Stereovision and augmented reality for closed-loop control of grasping in hand prostheses"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","046091"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Journal of Neural Engineering"],["dc.bibliographiccitation.volume","18"],["dc.contributor.author","Tchimino, Jack"],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Dideriksen, Jakob Lund"],["dc.contributor.author","Dosen, Strahinja"],["dc.date.accessioned","2021-08-12T07:45:11Z"],["dc.date.available","2021-08-12T07:45:11Z"],["dc.date.issued","2021"],["dc.identifier.doi","10.1088/1741-2552/ac07be"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/88392"],["dc.notes.intern","DOI Import GROB-448"],["dc.relation.eissn","1741-2552"],["dc.relation.issn","1741-2560"],["dc.title","The effect of calibration parameters on the control of a myoelectric hand prosthesis using EMG feedback"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","036007"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Journal of Neural Engineering"],["dc.bibliographiccitation.volume","14"],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Karnal, Hemanth"],["dc.contributor.author","Graimann, Bernhard"],["dc.contributor.author","Farina, Dario"],["dc.contributor.author","Dosen, Strahinja"],["dc.date.accessioned","2018-11-07T10:23:37Z"],["dc.date.available","2018-11-07T10:23:37Z"],["dc.date.issued","2017"],["dc.description.abstract","Objective. Providing sensory feedback to the user of the prosthesis is an important challenge. The common approach is to use tactile stimulation, which is easy to implement but requires training and has limited information bandwidth. In this study, we propose an alternative approach based on augmented reality. Approach. We have developed the GLIMPSE, a Google Glass application which connects to the prosthesis via a Bluetooth interface and renders the prosthesis states (EMG signals, aperture, force and contact) using augmented reality (seethrough display) and sound (bone conduction transducer). The interface was tested in healthy subjects that used the prosthesis with (FB group) and without (NFB group) feedback during a modified clothespins test that allowed us to vary the difficulty of the task. The outcome measures were the number of unsuccessful trials, the time to accomplish the task, and the subjective ratings of the relevance of the feedback. Main results. There was no difference in performance between FB and NFB groups in the case of a simple task (basic, same-color clothespins test), but the feedback significantly improved the performance in a more complex task (pins of different resistances). Importantly, the GLIMPSE feedback did not increase the time to accomplish the task. Therefore, the supplemental feedback might be useful in the tasks which are more demanding, and thereby less likely to benefit from learning and feedforward control. The subjects integrated the supplemental feedback with the intrinsic sources (vision and muscle proprioception), developing their own idiosyncratic strategies to accomplish the task. Significance. The present study demonstrates a novel self-contained, ready-to-deploy, wearable feedback interface. The interface was successfully tested and was proven to be feasible and functionally beneficial. The GLIMPSE can be used as a practical solution but also as a general and flexible instrument to investigate closed-loop prosthesis control."],["dc.identifier.doi","10.1088/1741-2552/aa620a"],["dc.identifier.isi","000398154200001"],["dc.identifier.pmid","28355147"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/42496"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","Iop Publishing Ltd"],["dc.relation.issn","1741-2552"],["dc.relation.issn","1741-2560"],["dc.title","GLIMPSE: Google Glass interface for sensory feedback in myoelectric hand prostheses"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","19505"],["dc.bibliographiccitation.issue","17"],["dc.bibliographiccitation.journal","IEEE Sensors Journal"],["dc.bibliographiccitation.lastpage","19515"],["dc.bibliographiccitation.volume","21"],["dc.contributor.author","Hahne, Janne M."],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Pardo, Luis A."],["dc.contributor.author","Kusche, Roman"],["dc.contributor.author","Ryschka, Martin"],["dc.contributor.author","Schilling, Arndt F."],["dc.date.accessioned","2021-10-01T09:57:56Z"],["dc.date.available","2021-10-01T09:57:56Z"],["dc.date.issued","2021"],["dc.identifier.doi","10.1109/JSEN.2021.3090949"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/89950"],["dc.notes.intern","DOI Import GROB-469"],["dc.relation.eissn","1558-1748"],["dc.relation.eissn","2379-9153"],["dc.relation.issn","1530-437X"],["dc.title","On the Utility of Bioimpedance in the Context of Myoelectric Control"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1855"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Experimental Brain Research"],["dc.bibliographiccitation.lastpage","1865"],["dc.bibliographiccitation.volume","233"],["dc.contributor.author","Dosen, Strahinja"],["dc.contributor.author","Markovic, Marko"],["dc.contributor.author","Wille, Nicola"],["dc.contributor.author","Henkel, Markus"],["dc.contributor.author","Koppe, Mario"],["dc.contributor.author","Ninu, Andrei"],["dc.contributor.author","Froemmel, Cornelius"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:56:48Z"],["dc.date.available","2018-11-07T09:56:48Z"],["dc.date.issued","2015"],["dc.description.abstract","Prosthesis users usually agree that myoelectric prostheses should be equipped with somatosensory feedback. However, the exact role of feedback and potential benefits are still elusive. The current study investigates the nature of human control processes within a specific context of routine grasping. Although the latter includes a fast feedforward control of the grasping force, the assumption was that the feedback would still be useful; it would communicate the outcome of the grasping trial, which the subjects could use to learn an internal model of feedforward control. Nine able-bodied subjects produced repeatedly a desired level of grasping force using different control configurations: feedback versus no-feedback, virtual versus real prosthetic hand, and joystick versus myocontrol. The outcome measures were the median and dispersion of the relative force errors. The results demonstrated that the feedback was successful in limiting the variability of the routine grasping due to uncertainties in the system and/or the command interface. The internal models of feedforward control could be employed by the subjects to control the prosthesis without the loss of performance even after the force feedback was removed. The models were, however, unstable over time, especially with myocontrol. Overall, the study demonstrates that the prosthesis system can be learned by the subjects using feedback. The feedback is also essential to maintain the model, and it could be delivered intermittently. This approach has practical advantages, but the level to which this mechanism can be truly exploited in practice depends directly on the consistency of the prosthesis control interface."],["dc.identifier.doi","10.1007/s00221-015-4257-1"],["dc.identifier.isi","000354731200016"],["dc.identifier.pmid","25804864"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/37038"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Springer"],["dc.relation.issn","1432-1106"],["dc.relation.issn","0014-4819"],["dc.title","Building an internal model of a myoelectric prosthesis via closed-loop control for consistent and routine grasping"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]