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ORCIDAles Holobar
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2020 – today
- 2024
[j23]Le Trung Thanh
, Karim Abed-Meraim, Philippe Ravier, Olivier Buttelli, Ales Holobar:
Tensor decomposition meets blind source separation. Signal Process. 221: 109483 (2024)- [c23]Le Trung Thanh, Karim Abed-Meraim, Philippe Ravier, Olivier Buttelli, Ales Holobar:
Joint INDSCAL Decomposition Meets Blind Source Separation. ICASSP 2024: 5570-5574 - [c22]Le Trung Thanh, Karim Abed-Meraim, Philippe Ravier, Olivier Buttelli, Ales Holobar:
Tensorial Convolutive Blind Source Separation. ICASSP 2024: 5575-5579 - 2023
- [j22]Milos Kalc, Jakob Skarabot, Matjaz Divjak, Filip Urh, Matej Kramberger, Matjaz Vogrin, Ales Holobar:
Motor Unit Identification in the M Waves Recorded by High-Density Electromyogram. IEEE Trans. Biomed. Eng. 70(5): 1662-1672 (2023) - 2021
- [j21]Martin Savc, Ales Holobar:
Non-Negative Matrix Factorization of Simulated High Density Surface Electromyograms Reflects Both Muscle Excitation and Muscle Shortening. IEEE Access 9: 70548-70555 (2021) - [j20]Matej Kramberger, Ales Holobar:
On the Prediction of Motor Unit Filter Changes in Blind Source Separation of High-Density Surface Electromyograms During Dynamic Muscle Contractions. IEEE Access 9: 103533-103540 (2021) - [j19]Aljaz Francic, Ales Holobar:
On the Reuse of Motor Unit Filters in High Density Surface Electromyograms Recorded at Different Contraction Levels. IEEE Access 9: 115227-115236 (2021) - [j18]Yuichi Nishikawa, Kohei Watanabe, Ales Holobar, Tetsuya Takahashi, Noriaki Maeda, Hirofumi Maruyama, Shinobu Tanaka, Allison S. Hyngstrom:
Association between the Degree of Pre-Synaptic Dopaminergic Pathway Degeneration and Motor Unit Firing Behavior in Parkinson's Disease Patients. Sensors 21(19): 6615 (2021) - [j17]Ales Holobar, Dario Farina:
Noninvasive Neural Interfacing With Wearable Muscle Sensors: Combining Convolutive Blind Source Separation Methods and Deep Learning Techniques for Neural Decoding. IEEE Signal Process. Mag. 38(4): 103-118 (2021) - [j16]Alexander Kenneth Clarke, Seyed Farokh Atashzar, Alessandro Del Vecchio, Deren Y. Barsakcioglu, Silvia Muceli, Paul Bentley, Filip Urh, Ales Holobar, Dario Farina:
Deep Learning for Robust Decomposition of High-Density Surface EMG Signals. IEEE Trans. Biomed. Eng. 68(2): 526-534 (2021) - [j15]Deren Y. Barsakcioglu, Mario Bräcklein, Ales Holobar, Dario Farina:
Control of Spinal Motoneurons by Feedback From a Non-Invasive Real-Time Interface. IEEE Trans. Biomed. Eng. 68(3): 926-935 (2021) - 2020
- [j14]Bozidar Potocnik, Jurij Munda, Milan Reljic, Ksenija Rakic, Jure Knez, Veljko Vlaisavljevic, Gasper Sedej, Boris Cigale, Ales Holobar, Damjan Zazula:
Public database for validation of follicle detection algorithms on 3D ultrasound images of ovaries. Comput. Methods Programs Biomed. 196: 105621 (2020) - [c21]Filip Urh, Damjan Strnad, Alex Clarke, Dario Farina, Ales Holobar:
On the Selection of Neural Network Architecture for Supervised Motor Unit Identification from High-Density Surface EMG. EMBC 2020: 736-739 - [c20]Ales Holobar, Aljaz Francic:
Motor unit filter prelearning strategies for decomposition of compound muscle action potentials in high-density surface electromyograms. EMBC 2020: 3465-3468
2010 – 2019
- 2019
- [j13]MohammadReza Mohebbian, Hamid R. Marateb, Saeed Karimimehr, Miquel Angel Mañanas, Jernej Kranjec, Ales Holobar:
Non-invasive Decoding of the Motoneurons: A Guided Source Separation Method Based on Convolution Kernel Compensation With Clustered Initial Points. Frontiers Comput. Neurosci. 13: 14 (2019) - 2018
- [c19]M. Savc, Vojko Glaser, Ales Holobar:
On the Impact of Muscle Shortening on Non-Negative Matrix Factorization of Dynamic Surface Electromyograms. EMBC 2018: 5970-5973 - 2017
- [j12]Bozidar Potocnik, Ales Holobar:
A new optical flow model for motor unit conduction velocity estimation in multichannel surface EMG. Comput. Biol. Medicine 83: 59-68 (2017) - [j11]Petra Povalej Brzan, Juan Alvaro Gallego, Juan Pablo Romero, Vojko Glaser, Eduardo Rocon, Julián Benito-León, F. Bermejo-Pareja, I. J. Posada, Ales Holobar:
New Perspectives for Computer-Aided Discrimination of Parkinson's Disease and Essential Tremor. Complex. 2017: 4327175:1-4327175:17 (2017) - [c18]M. Savc, Vojko Glaser, Ales Holobar, Imre Cikajlo, Zlatko Matjacic:
Comparison of non-negative matrix factorization and convolution kernel compensation in surface electromyograms of forearm muscles. CISP-BMEI 2017: 1-5 - [c17]Vojko Glaser, Ales Holobar:
On the impact of spike segmentation on motor unit identification in dynamic surface electromyograms. EMBC 2017: 430-433 - [c16]Vojko Glaser, Dario Farina, Ales Holobar:
Simulations of high-density surface electromyograms in dynamic muscle contractions. EMBC 2017: 3453-3456 - [c15]Vojko Glaser, Ales Holobar:
Impact of motor unit action potential components on the motor unit identification from dynamic high-density surface electromyograms. NER 2017: 90-93 - 2016
- [j10]Dario Farina, Ales Holobar:
Characterization of Human Motor Units From Surface EMG Decomposition. Proc. IEEE 104(2): 353-373 (2016) - 2015
- [j9]Dario Farina, Ales Holobar:
Human-Machine Interfacing by Decoding the Surface Electromyogram [Life Sciences]. IEEE Signal Process. Mag. 32(1): 115-120 (2015) - [j8]Xiaoyan Li, Ales Holobar, Marco Gazzoni, Roberto Merletti, William Zev Rymer, Ping Zhou:
Examination of Poststroke Alteration in Motor Unit Firing Behavior Using High-Density Surface EMG Decomposition. IEEE Trans. Biomed. Eng. 62(5): 1242-1252 (2015) - [c14]Tamas Kapelner, Ning Jiang, Ivan Vujaklija, Oskar C. Aszmann, Ales Holobar, Dario Farina:
Classification of motor unit activity following targeted muscle reinnervation. NER 2015: 652-654 - 2013
- [c13]Sebastijan Sprager, Ales Holobar, Damjan Zazula:
Feasibility Study of Heartbeat Detection from Optical Interferometric Signal by using Convolution Kernel Compensation. BIOSIGNALS 2013: 396-400 - [c12]Rok Istenic, Francesco Negro, Ales Holobar, Damjan Zazula, Dario Farina:
Surface EMG pre-processing techniques for the detection of common input to motor neuron populations. BMEI 2013: 256-259 - [c11]Petra Povalej Brzan, Vojko Glaser, Simon Zelic, Juan Alvaro Gallego, Juan Pablo Romero Muñoz, Ales Holobar:
On the Impact of Pathological Tremor Intensity on Noninvasive Characterization of Motor Unit Discharge Properties. NEUROTECHNIX 2013: 126-132 - [c10]Juan Alvaro Gallego, Jakob Lund Dideriksen, Ales Holobar, Juan Pablo Romero, José Luis Pons, Eduardo Rocon, Dario Farina:
Motor Unit Properties and Underlying Determinants in Pathological Tremor. NEUROTECHNIX 2013: 133-138 - 2011
- [c9]Juan Alvaro Gallego, Jakob Lund Dideriksen, Dario Farina, Eduardo Rocon, Ales Holobar, José Luis Pons:
A modelling study on transmission of the central oscillator in tremor by a motor neuron pool. EMBC 2011: 2037-2040 - [c8]Matjaz Divjak, Damjan Zazula, Ales Holobar:
Assessment of artefact suppression by ICA and spatial filtering on reduced sets of EEG signals. EMBC 2011: 4422-4425 - [c7]Ales Holobar, Vojko Glaser, Juan Alvaro Gallego, Jakob Lund Dideriksen, Dario Farina:
Noninvasive analysis of motor unit behavior in pathological tremor. EMBC 2011: 7512-7515
2000 – 2009
- 2007
- [j7]Ales Holobar, Matjaz Divjak, Dean Korosec, Damjan Zazula:
Training scenario prototyping for VR-based simulation of neonatal decision-making. Comput. Appl. Eng. Educ. 15(4): 317-328 (2007) - [j6]Ales Holobar, Matjaz Divjak, Iztok Prelog, Dean Korosec, Damjan Zazula:
A distributed virtual reality-based system for neonatal decision-making training. Comput. Appl. Eng. Educ. 15(4): 329-339 (2007) - [j5]Ales Holobar, Damjan Zazula:
Multichannel Blind Source Separation Using Convolution Kernel Compensation. IEEE Trans. Signal Process. 55(9): 4487-4496 (2007) - [c6]Ales Holobar, Damjan Zazula:
Gradient Convolution Kernel Compensation Applied to Surface Electromyograms. ICA 2007: 617-624 - 2006
- [j4]Ales Holobar, Milan Ojstersek, Damjan Zazula:
Distributed Jacobi Joint Diagonalization on Clusters of Personal Computers. Int. J. Parallel Program. 34(6): 509-530 (2006) - [c5]Damjan Zazula, Ales Holobar, Matjaz Divjak:
Convolution Kernel Compensation Applied to 1D and 2D Blind Source Separation. SIGMAP 2006: 126-133 - 2005
- [j3]Damjan Zazula, Ales Holobar:
An approach to surface EMG decomposition based on higher-order cumulants. Comput. Methods Programs Biomed. 80(Supplement-1): S51-S60 (2005) - [j2]D. Korocsec, Ales Holobar, Matjaz Divjak, Damjan Zazula:
Building interactive virtual environments for simulated training in medicine using VRML and Java/JavaScript. Comput. Methods Programs Biomed. 80(Supplement-1): S61-S70 (2005) - 2004
- [c4]Ales Holobar, Damjan Zazula:
A novel approach to convolutive blind separation of close-to-orthogonal pulse sources using second-order statistics. EUSIPCO 2004: 381-384 - [c3]Ales Holobar, Damjan Zazula:
Blind Deconvolution of Close-to-Orthogonal Pulse Sources Applied to Surface Electromyograms. ICA 2004: 1056-1063 - 2003
- [j1]Zvonko Fazarinc, Sasa Divjak, Dean Korosec, Ales Holobar, Matjaz Divjak, Damjan Zazula:
Quest for effective use of computer technology in education: From natural sciences to medicine. Comput. Appl. Eng. Educ. 11(3): 116-131 (2003) - 2002
- [c2]Dean Korosec, Ales Holobar, Matjaz Divjak, Damjan Zazula:
Dynamic VRML for Simulated Training in Medicine. CBMS 2002: 205- - [c1]Ales Holobar, Cédric Févotte, Christian Doncarli, Damjan Zazula:
Single autoterms selection for blind source separation in time-frequency plane. EUSIPCO 2002: 1-4
Coauthor Index
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