Ivan Vujaklija
Imperial College London
Publications 31
#1Tamás Kapelner (GAU: University of Göttingen)H-Index: 3
#2Ivan Vujaklija (Aalto University)
Last.Dario Farina (Imperial College London)H-Index: 70
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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...
#1Arash Andalib (UF: University of Florida)H-Index: 2
#2Dario FarinaH-Index: 70
Last.Jose C. PrincipeH-Index: 63
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The performance of upper-limb prostheses is currently limited by the relatively poor functionality of unintuitive control schemes. This paper proposes to extract, from multichannel electromyographic signals (EMG), motor neuron spike trains and project them into lower dimensional continuous signals, which are used as multichannel proportional inputs to control the prosthetic's actuators. These control signals are an estimation of the common synaptic input that the motor neurons receive. We use th...
#2Dario Farina (Imperial College London)H-Index: 70
Last.Ivan Vujaklija (Aalto University)H-Index: 9
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Conventional myoelectric controllers provide a mapping between electromyographic signals and prosthetic functions. However, due to a number of instabilities continuously challenging this process, an initial mapping may require an extended calibration phase with long periods of user-training in order to ensure satisfactory performance. Recently, studies on co-adaptation have highlighted the benefits of concurrent user learning and machine adaptation where systems can cope with deficiencies in the...
Apr 1, 2019 in ICRA (International Conference on Robotics and Automation)
#1Michele Barsotti (Sant'Anna School of Advanced Studies)H-Index: 6
#2Sigrid S. G. Dupan (Radboud University Nijmegen)
Last.Dario Farina (Imperial College London)H-Index: 70
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A hand impairment can have a profound impact on the quality of life. This has motivated the development of dexterous prosthetic and orthotic devices. However, their control with neuromuscular interfacing remains challenging. Moreover, existing myocontrol interfaces typically require an extensive calibration. We propose a minimally supervised, online myocontrol system for proportional and simultaneous finger force estimation based on ridge regression using only individual finger tasks for trainin...
#1Aidan D. RocheH-Index: 9
#2Ben Lakey (Imperial College London)
Last.Oskar C. Aszmann (Medical University of Vienna)H-Index: 24
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Purpose of Review This paper aims to summarise the development trends in upper limb bionics over the past 5 years.
ObjectiveThe aim of the study was to report normative outcome data of prosthetic hand function in below-elbow amputees using four different objective measurements closely related to activities of daily living.DesignSeventeen patients who underwent prosthetic fitting after unilateral below-elbow ampu
#1Konstantin D. Bergmeister (Medical University of Vienna)H-Index: 5
#2Martin Aman (Medical University of Vienna)H-Index: 3
Last.O. Riedl (Medical University of Vienna)H-Index: 12
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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 an...
#1Ivan Vujaklija (Imperial College London)H-Index: 9
#2Vahid Shalchyan (IUST: Iran University of Science and Technology)H-Index: 3
Last.Dario Farina (Imperial College London)H-Index: 70
view all 6 authors...
In this paper, we propose a nonlinear minimally supervised method based on autoencoding (AEN) of EMG for myocontrol. The proposed method was tested against the state-of-the-art (SOA) control scheme using a Fitts’ law approach. Seven able-bodied subjects performed a series of target acquisition myoelectric control tasks using the AEN and SOA algorithms for controlling two degrees-of-freedom (radial/ulnar deviation and flexion/extension of the wrist), and their online performance was characterized...