Robin Rohlén

I develop algorithms and methods based on biosignals of humans using ultrasound and electromyography for the purpose of understanding the neuromuscular control of movement.

https://rohlen.github.io/

0000-0003-4328-5467

Contact

robin.rohlen@umu.se

Works at

Postdoctoral fellow at Department of Diagnostics and Intervention

5A, Målpunkt H62, Norrlands universitetssjukhus Umeå universitet, 901 85 Umeå

Affiliated as postdoctoral position at Department of Medical and Translational Biology

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