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Umeå University
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Staff photo Robin Rohlén

Robin Rohlén

I develop and use electrophysiological and ultrasonic methods to study the neural control of motor neurons

0000-0003-4328-5467

Contact

E-mail
robin.rohlen@umu.se
Phone

Works at

Affiliation
Postdoctoral fellow at Department of Diagnostics and Intervention
Location
5A, Målpunkt H62, Norrlands universitetssjukhus Umeå universitet, 901 85 Umeå
Affiliation
Affiliated as postdoctoral position at Department of Medical and Translational Biology
Location
hus H, Johan Bures väg 12, Biologihuset Umeå universitet, 901 87 Umeå
Assessing the impact of degree of fusion and muscle fibre twitch shape variation on the accuracy of motor unit discharge time identification from ultrasound images
Biomedical Signal Processing and Control, Elsevier 2025, Vol. 100
Rohlén, Robin; Lubel, Emma; Farina, Dario
Accurate identification of motoneuron discharges from ultrasound images across the full muscle cross-section
IEEE Transactions on Biomedical Engineering, IEEE 2024, Vol. 71, (5) : 1466-1477
Lubel, Emma; Rohlén, Robin; Sgambato, Bruno Grandi; et al.
Identifying motor unit spike trains in ultrasound images comprised of varying successive twitch-like shapes and degrees of fusion in isometric contractions
ISEK XXIV Abstract book
Rohlén, Robin; Lubel, Emma; Farina, Dario
[Neuromechanical characterisation of muscles and their functional units using ultrasound imaging methods] State-of-the-art and future perspectives
ISEK XXIV Abstract book
Rohlén, Robin; Lubel, Emma; Grönlund, Christer; et al.
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, Elsevier 2023, Vol. 73
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, Institute of Physics Publishing (IOPP) 2023, Vol. 20, (3)
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.
View publications in DiVA

Research projects

1 January 2016 until 31 December 2024
Pioneering ultrasound imaging methods for neuromuscular diagnostics