55 citations · 123 across the 8 of their papers we have counts for
9 papers
Miniature biplanar coils for alkali-metal-vapor magnetometry
Michael C. D. Tayler, Kostas Mouloudakis, Rasmus Zetter +5
Atomic spin sensors offer precision measurements using compact, microfabricated packages, placing them in a competitive position for both market and research applications. Performa…
Calibration and localization of optically pumped magnetometers using electromagnetic coils
Joonas Iivanainen, Amir Borna, Rasmus Zetter +6
In this paper, we propose a method to estimate the position, orientation and gain of a magnetic field sensor using a set of (large) electromagnetic coils. We apply the method for c…
A general method for computing thermal magnetic noise arising from thin conducting objects
Joonas Iivanainen, Antti J. Mäkinen, Rasmus Zetter +3
Thermal motion of charge carriers in a conducting object causes magnetic field noise that interferes with sensitive measurements nearby the conductor. In this paper, we describe a…
Spatial sampling of MEG and EEG revisited: From spatial-frequency spectra to model-informed sampling
Joonas Iivanainen, Antti J. Mäkinen, Rasmus Zetter +3
In this paper, we analyze spatial sampling of electro- (EEG) magnetoencephalography (MEG), where the electric or magnetic field is typically sampled on a curved surface such as the…
Magnetic-field modeling with surface currents: Physical and computational principles of bfieldtools
Antti J. Mäkinen, Rasmus Zetter, Joonas Iivanainen +3
Surface currents provide a general way to model static magnetic fields in source-free volumes. To facilitate the use of surface currents in magneto-quasistatic problems, we have im…
Magnetic-field modeling with surface currents: Implementation and usage of bfieldtools
Rasmus Zetter, Antti J. Mäkinen, Joonas Iivanainen +3
We present a novel open-source Python software package, bfieldtools, for magneto-quasistatic calculations with current densities on surfaces of arbitrary shape. The core functional…
Sampling theory for spatial field sensing: Application to electro- and magnetoencephalography
Joonas Iivanainen, Antti Mäkinen, Rasmus Zetter +3
We present a theoretical framework for analyzing spatial sampling of fields in three-dimensional space. The framework bridges Shannon's sampling and information theory to Bayesian…
Autoencoding sensory substitution
Viktor Tóth, Lauri Parkkonen
Tens of millions of people live blind, and their number is ever increasing. Visual-to-auditory sensory substitution (SS) encompasses a family of cheap, generic solutions to assist…
Adaptive neural network classifier for decoding MEG signals
Ivan Zubarev, Rasmus Zetter, Hanna-Leena Halme +1
Convolutional Neural Networks (CNN) outperform traditional classification methods in many domains. Recently these methods have gained attention in neuroscience and particularly in…