Patel, Gauravkumar Kiritbhai

[["dc.bibliographiccitation.artnumber","056015"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Journal of Neural Engineering"],["dc.bibliographiccitation.volume","13"],["dc.contributor.author","Patel, Gauravkumar K."],["dc.contributor.author","Dosen, Strahinja"],["dc.contributor.author","Castellini, Claudio"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T10:07:51Z"],["dc.date.available","2018-11-07T10:07:51Z"],["dc.date.issued","2016"],["dc.description.abstract","Objective. Closing the loop in myoelectric prostheses by providing artificial somatosensory feedback to the user is an important need for prosthetic users. Previous studies investigated feedback strategies in combination with the control of one degree of freedom of simple grippers. Modern hands, however, are sophisticated multifunction systems. In this study, we assessed multichannel electrotactile feedback integrated with an advanced method for the simultaneous and proportional control of individual fingers of a dexterous hand. Approach. The feedback used spatial and frequency coding to provide information on the finger positions (normalized flexion angles). A comprehensive set of conditions have been investigated in 28 able-bodied subjects, including feedback modalities (visual, electrotactile and no feedback), control tasks (fingers and grasps), systems (virtual and real hand), control methods (ideal and realistic) and range of motion (low and high). The task for the subjects was to operate the hand using closed-loop myoelectric control and generate the desired movement (e.g., selected finger or grasp at a specific level of closure). Main results. The subjects could perceive the multichannel and multivariable electrotactile feedback and effectively exploit it to improve the control performance with respect to open-loop grasping. The improvement however depended on the reliability of the feedforward control, with less consistent control exhibiting performance trends that were more complex across the conditions. Significance. The results are promising for the potential application of advanced feedback to close the control loop in sophisticated prosthetic systems."],["dc.identifier.doi","10.1088/1741-2560/13/5/056015"],["dc.identifier.isi","000385493200002"],["dc.identifier.pmid","27618968"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/39358"],["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","Multichannel electrotactile feedback for simultaneous and proportional myoelectric control"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","967"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","IEEE Transactions on Neural Systems and Rehabilitation Engineering"],["dc.bibliographiccitation.lastpage","975"],["dc.bibliographiccitation.volume","25"],["dc.contributor.author","Patel, Gauravkumar K."],["dc.contributor.author","Nowak, Markus"],["dc.contributor.author","Castellini, Claudio"],["dc.date.accessioned","2020-12-10T18:26:21Z"],["dc.date.available","2020-12-10T18:26:21Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1109/TNSRE.2017.2676467"],["dc.identifier.eissn","1558-0210"],["dc.identifier.issn","1534-4320"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/76051"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Exploiting Knowledge Composition to Improve Real-Life Hand Prosthetic Control"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","056016"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Journal of Neural Engineering"],["dc.bibliographiccitation.volume","14"],["dc.contributor.author","Patel, Gauravkumar K"],["dc.contributor.author","Hahne, Janne M"],["dc.contributor.author","Castellini, Claudio"],["dc.contributor.author","Farina, Dario"],["dc.contributor.author","Dosen, Strahinja"],["dc.date.accessioned","2020-12-10T18:15:50Z"],["dc.date.available","2020-12-10T18:15:50Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1088/1741-2552/aa7e82"],["dc.identifier.eissn","1741-2552"],["dc.identifier.issn","1741-2560"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/74970"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Context-dependent adaptation improves robustness of myoelectric control for upper-limb prostheses"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1745"],["dc.bibliographiccitation.issue","9"],["dc.bibliographiccitation.journal","IEEE Transactions on Neural Systems and Rehabilitation Engineering"],["dc.bibliographiccitation.lastpage","1755"],["dc.bibliographiccitation.volume","26"],["dc.contributor.author","Patel, Gauravkumar K."],["dc.contributor.author","Castellini, Claudio"],["dc.contributor.author","Hahne, Janne M."],["dc.contributor.author","Farina, Dario"],["dc.contributor.author","Dosen, Strahinja"],["dc.date.accessioned","2020-12-10T18:26:21Z"],["dc.date.available","2020-12-10T18:26:21Z"],["dc.date.issued","2018"],["dc.description.abstract","Dexterous upper limb myoelectric prostheses can, to some extent, restore the motor functions lost after an amputation. However, ensuring the reliability of myoelectric control is still an open challenge. In this paper, we propose a classification method that exploits the regularity in muscle activation patterns (uniform scaling) across different force levels within a given movement class. This assumption leads to a simple training procedure, using training data collected at single contraction intensity for each movement class. The proposed method was compared to the widely accepted benchmark [linear discriminant analysis (LDA) classifier] using off-line and online evaluation. The off-line classification errors obtained with the new method were either lower or higher than LDA depending upon the chosen feature set. In the online evaluation, the new classification method was operated using amplitude-EMG features and compared to the state-of-the-art LDA classifier combined with the time domain feature set. The online evaluation was performed in 11 able-bodied and one amputee subject using a set of four functional tasks mimicking daily-life activities. The tasks assessed the dexterity (e.g., switching between functions) and robustness of control (e.g., handling heavy objects). With the new classification scheme, the amputee performed better in all functional tasks, whereas the able-bodied subjects performed significantly better in three out of four functional tasks. Overall, the novel method outperformed the state-of-the-art approach (LDA) while utilizing less training data and a smaller feature set. The proposed method is, therefore, a simple but effective and robust classification scheme, convenient for online implementation and clinical use."],["dc.identifier.doi","10.1109/TNSRE.2018.2861774"],["dc.identifier.eissn","1558-0210"],["dc.identifier.issn","1534-4320"],["dc.identifier.pmid","30072332"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/76054"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.notes.status","final"],["dc.relation.eissn","1558-0210"],["dc.title","A Classification Method for Myoelectric Control of Hand Prostheses Inspired by Muscle Coordination"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]