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Umeå universitet
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Huvudmenyn dold.

Robin Rohlén

Jag utvecklar algoritmer och metoder baserade på biosignaler från människor med ultraljud och elektromyografi i syfte att förstå den neuromuskulära kontrollen av rörelse.

https://rohlen.github.io/

0000-0003-4328-5467

Kontakt

E-post
robin.rohlen@umu.se
Telefon

Verksam vid

Anknytning
Anknuten som övrig/annan befattning till Institutionen för strålningsvetenskaper
Plats
10c, Målpunkt E03, Norrlands universitetssjukhus Umeå universitet, 901 87 Umeå
Combining high-density electromyography and ultrafast ultrasound to assess individual motor unit properties in vivo
Convegno nazionale di bioingegneria: eight national congress of bioengineering: Proceedings, Patron Editore S.r.l. 2023 : 1-4
Carbonaro, M.; Rohlén, Robin; Seoni, S.; et al.
Ultrafast ultrasound imaging can be used to access single motor units in deep muscles, but the underlying biomechanical source remains to be understood
Journal of Electromyography & Kinesiology, Elsevier 2023, Vol. 71
Grönlund, Christer; Rohlén, Robin
Non-linearity in motor unit velocity twitch dynamics: Implications for ultrafast ultrasound source separation
IEEE transactions on neural systems and rehabilitation engineering
Lubel, Emma; Sgambato, Bruno Grandi; Rohlén, Robin; et al.
Quantifying the spatial distribution of individual muscle units using high-density surface EMG and ultrafast ultrasound
ECSS Paris 2023 Oral presentations: Biomechanics & Motor control
Rohlén, Robin; Carbonaro, Marco; Botter, Alberto; et al.
Spatially repeatable components from ultrafast ultrasound are associated with motor unit activity in human isometric contractions
Journal of Neural Engineering, Institute of Physics (IOP) 2023, Vol. 20, (4) : 046016-
Rohlén, Robin; Carbonaro, Marco; Cerone, Giacinto Luigi; et al.
Interframe Echo Intensity Variation of Subregions and Whole Plaque in Two-Dimensional Carotid Ultrasonography: Simulations and in Vivo Observations
Journal of ultrasound in medicine, John Wiley & Sons 2023, Vol. 42, (5) : 1033-1046
Rohlén, Robin; Jiang, Biao; Nyman, Emma; et al.
Spatial decomposition of ultrafast ultrasound images to identify motor unit activity: a comparative study with intramuscular and surface EMG
Journal of Electromyography & Kinesiology
Rohlén, Robin; Lubel, Emma; Grandi Sgambato, Bruno; et al.
Estimating the neural spike train from an unfused tetanic signal of low-threshold motor units using convolutive blind source separation
Biomedical engineering online, BioMed Central (BMC) 2023, Vol. 22
Rohlén, Robin; Lundsberg, Jonathan; Antfolk, Christian
A fast blind source separation algorithm for decomposing ultrafast ultrasound images into spatiotemporal muscle unit kinematics
Journal of Neural Engineering
Rohlén, Robin; Lundsberg, Jonathan; Malesevic, Nebojsa; et al.
Modelling intra-muscular contraction dynamics using in silico to in vivo domain translation
Biomedical engineering online, BioMed Central (BMC) 2022, Vol. 21, (1)
Ali, Hazrat; Umander, Johannes; Rohlén, Robin; et al.
Identification of motor units using ultrasound – From muscle to neural interface
RehabWeek, Rotterdam,The Netherlands, July 25-29, 2022
Rohlén, Robin
Optimization and comparison of two methods for spike train estimation in an unfused tetanic contraction of low threshold motor units
Journal of Electromyography & Kinesiology, Elsevier 2022, Vol. 67
Rohlén, Robin; Antfolk, Christian; Grönlund, Christer
Estimation of contractile parameters of successive twitches in unfused tetanic contractions of single motor units – A proof-of-concept study using ultrafast ultrasound imaging in vivo
Journal of Electromyography & Kinesiology, Elsevier 2022, Vol. 67
Rohlén, Robin; Raikova, Rositsa; Stålberg, Erik; et al.
Comparison of decomposition algorithms for identification of single motor units in ultrafast ultrasound image sequences of low force voluntary skeletal muscle contractions
BMC Research Notes
Rohlén, Robin; Yu, Jun; Grönlund, Christer
Identification of single motor units in ultrafast ultrasound image sequences of voluntary skeletal muscle contractions
Umeå University medical dissertations, 2127
Rohlén, Robin
A Deep Learning Pipeline for Identification of Motor Units in Musculoskeletal Ultrasound
IEEE Access, IEEE 2020, Vol. 8 : 170595-170608
Ali, Hazrat; Umander, Johannes; Rohlén, Robin; et al.
Identification of single motor units in skeletal muscle under low force isometric voluntary contractions using ultrafast ultrasound
Scientific Reports, Springer Nature 2020, Vol. 10
Rohlén, Robin; Stålberg, Erik; Grönlund, Christer
A Method for Identification of Mechanical Response of Motor Units in Skeletal Muscle Voluntary Contractions using Ultrafast Ultrasound Imaging: Simulations and Experimental Tests
IEEE Access, IEEE 2020, Vol. 8 : 50299-50311
Rohlén, Robin; Stålberg, Erik; Stoverud, Karen-Helene; et al.
Imaging recruitment of motor units in voluntary skeletal muscle contractions using decomposition and ultrafast ultrasound imaging: A pilot study
2020 ISEK Virtual Congress Poster Abstract Booklet, International Society of Electrophysiology and Kinesiology 2020 : 141-142
Rohlén, Robin; Stålberg, Erik; Yu, Jun; et al.
Ultrafast Ultrasound Imaging of Motor Units in Skeletal Muscle during Voluntary Contractions – A Pilot Validation Study by using Needle-EMG
41st International Engineering in Medicine and Biology Conference, Berlin, Germany, July 23-27, 2019
Rohlén, Robin; Stålberg, Erik; Grönlund, Christer
Ultrasound-based Imaging of Motor Units in Skeletal Muscle Tissue
Medicinteknikdagarna 2018, 9-10 oktober, Umeå
Rohlén, Robin; Stålberg, Erik; Stoverud, Karen-Helene; et al.
Segmentation of Motor Unit Territories in Ultrasound Image Sequences of Contracting Skeletal Muscle Tissue
Medicinteknikdagarna 2017, 10-11 oktober, Västerås
Rohlén, Robin; Stoverud, Karen-Helene; Yu, Jun; et al.
Segmentation of motor units in ultrasound image sequences
Rohlén, Robin
A Statistical Analysis of Muscle Fiber Area
Rohlén, Robin
Optimization and comparison of two methods for spike train estimation in an unfused tetanic contraction of low threshold motor units
Rohlén, Robin; Antfolk, Christian; Grönlund, Christer
Estimating the neural spike train from an unfused tetanic signal of low threshold motor units using convolutive blind source separation
Rohlén, Robin; Lundsberg, Jonathan; Antfolk, Christian
A fast blind source separation algorithm for decomposing ultrafast ultrasound images into spatiotemporal muscle unit kinematics
Rohlén, Robin; Lundsberg, Jonathan; Malesevic, Nebojsa; et al.
Estimation of motor unit contractile properties in voluntary contractions of a skeletal muscle obtained by ultrafast ultrasound
Rohlén, Robin; Raikova, Rositsa; Stålberg, Erik; et al.
Visa publikationer i DiVA

Forskningsprojekt

1 januari 2016 till 31 december 2024
Utveckling av metoder för ultraljudsavbildning för neuromuskulär diagnostik