Ales Holobar
researcher
Facts
12 properties- Instance of
- human
- Country of citizenship
- Slovenia (1991–present), Socialist Federal Republic of Yugoslavia (?–1991)[2][3]
- Occupation
- researcher
- Employer
- University of Maribor (2009–present)[4]
- Educated at
- University of Maribor (2000–2004)[5]
- Doctoral student
- Lukas Wiedemann[7]
- Family name
- Holobar[8]
- Imported from
- wholeness_audit_2026-05-02
- On focus list of Wikimedia project
- NZThesisProject[11]
🏷️ Also known as
en Ales Holobar
en Aleš Holobar
🔖 Identifiers · 8
- ISNI
- 0000000421692050
- ORCID iD
- 0000-0001-8338-5978
- VIAF cluster ID
- 305617075
- OpenAlex ID
- A5073787663
- CONOR.SI ID
- 5045603
- NSK (VIAF) ID
- 000271869
- NSK ID
- 981005780611009366
- SICRIS researcher ID
- 21301
🔗 Connections
Author of 7
Analysis of motor unit spike trains estimated from high-density surface electromyography is highly reliable across operators,
Motor Unit-Driven Identification of Pathological Tremor in Electroencephalograms,
New Perspectives for Computer-Aided Discrimination of Parkinson’s Disease and Essential Tremor,
One central oscillatory drive is compatible with experimental motor unit behaviour in essential and Parkinsonian tremor,
Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition,
Public database for validation of follicle detection algorithms on 3D ultrasound images of ovaries,
Tutorial: Analysis of motor unit discharge characteristics from high-density surface EMG signals
← Authored by 7
Analysis of motor unit spike trains estimated from high-density surface electromyography is highly reliable across operators,
Motor Unit-Driven Identification of Pathological Tremor in Electroencephalograms,
New Perspectives for Computer-Aided Discrimination of Parkinson’s Disease and Essential Tremor,
One central oscillatory drive is compatible with experimental motor unit behaviour in essential and Parkinsonian tremor,
Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition,
Public database for validation of follicle detection algorithms on 3D ultrasound images of ovaries,
Tutorial: Analysis of motor unit discharge characteristics from high-density surface EMG signals
Affiliated with 1
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