W
Winnie Jensen
Researcher at Aalborg University
Publications - 157
Citations - 2768
Winnie Jensen is an academic researcher from Aalborg University. The author has contributed to research in topics: Stimulation & Medicine. The author has an hindex of 23, co-authored 145 publications receiving 2340 citations. Previous affiliations of Winnie Jensen include Indiana University – Purdue University Indianapolis.
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Journal ArticleDOI
Restoring Natural Sensory Feedback in Real-Time Bidirectional Hand Prostheses
Stanisa Raspopovic,Stanisa Raspopovic,Marco Capogrosso,Marco Capogrosso,Francesco Maria Petrini,Marco Bonizzato,Jacopo Rigosa,Giovanni Di Pino,Jacopo Carpaneto,Marco Controzzi,Tim Boretius,Eduardo Fernandez,Giuseppe Granata,Calogero Maria Oddo,Luca Citi,Anna Lisa Ciancio,Christian Cipriani,Maria Chiara Carrozza,Winnie Jensen,Eugenio Guglielmelli,Thomas Stieglitz,Paolo Maria Rossini,Silvestro Micera,Silvestro Micera +23 more
TL;DR: By stimulating the median and ulnar nerve fascicles using transversal multichannel intrafascicular electrodes, according to the information provided by the artificial sensors from a hand prosthesis, physiologically appropriate sensory information can be provided to an amputee during the real-time decoding of different grasping tasks to control a dexterous hand prosthetic.
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In-vivo implant mechanics of flexible, silicon-based ACREO microelectrode arrays in rat cerebral cortex
TL;DR: The findings suggest that reusable electrodes for acute animal experiments must not only be strong enough to survive a maximal force that exceeded the penetration force, but must also be able to withstand high tension forces during retraction.
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Acute peripheral nerve recording Characteristics of polymer-based longitudinal intrafascicular electrodes
TL;DR: Recordings of neural activity induced by manually elicited afferent neural activity showed that both polyLIFE versions performed comparably to PtIrLIFEs.
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Multiday Evaluation of Techniques for EMG-Based Classification of Hand Motions
Asim Waris,Imran Khan Niazi,Mohsin Jamil,Kevin Englehart,Winnie Jensen,Ernest Nlandu Kamavuako +5 more
TL;DR: Results indicate that within day performances of classifiers may be similar but over time, it may lead to a substantially different outcome, and training ANN on multiple days might allow capturing time-dependent variability in the EMG signals and thus minimizing the necessity for daily system recalibration.
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Relationship between grasping force and features of single-channel intramuscular EMG signals.
TL;DR: Investigating the capacity of selective single-channel iEMG recordings to represent the grasping force with respect to the use of sEMG indicates that a selective i EMG recording is representative of the applied grasping force and can be used for proportional control.