Evidence map›Paper›PMID 42092090›Full record

ArticleScientific reports2026

Live magnetomyography and robotic-hand proxy control using a wearable triaxial optically pumped magnetometer.

Rach Dawson, Sohaila Safavi, Marcin S Mrozowski, Carolyn O'Dwyer, Dominic Hunter, Erling Riis, Paul F Griffin, Stuart Ingleby

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Rach DawsonDepartment of Physics, SUPA, University of Strathclyde, Glasgow, G4 0NG, United Kingdom. rach.dawson@ndcn.ox.ac.uk.ORCID http://orcid.org/0000-0003-4862-3066
Sohaila SafaviDepartment of Physics, SUPA, University of Strathclyde, Glasgow, G4 0NG, United Kingdom.ORCID https://orcid.org/0009-0007-9795-0852
Marcin S MrozowskiDepartment of Physics, SUPA, University of Strathclyde, Glasgow, G4 0NG, United Kingdom.ORCID http://orcid.org/0000-0001-9616-4058
Carolyn O'DwyerDepartment of Physics, SUPA, University of Strathclyde, Glasgow, G4 0NG, United Kingdom.ORCID http://orcid.org/0000-0003-1922-6504
Dominic HunterDepartment of Physics, SUPA, University of Strathclyde, Glasgow, G4 0NG, United Kingdom.ORCID http://orcid.org/0000-0003-4177-6027
Erling RiisDepartment of Physics, SUPA, University of Strathclyde, Glasgow, G4 0NG, United Kingdom.ORCID http://orcid.org/0000-0002-3225-5302
Paul F GriffinDepartment of Physics, SUPA, University of Strathclyde, Glasgow, G4 0NG, United Kingdom.ORCID http://orcid.org/0000-0002-0134-7554
Stuart InglebyDepartment of Physics, SUPA, University of Strathclyde, Glasgow, G4 0NG, United Kingdom.ORCID http://orcid.org/0000-0001-7473-9949

Funding

Engineering and Physical Sciences Research Council Vacation InternshipUK Research and Innovation EP/T001046/1
6 · The paper itself

Abstract

Zero-field optically pumped magnetometers (OPMs) represent a promising modality in biomagnetism research due to their ultra-sensitive capabilities contained within compact sensor packages that enable contactless biomagnetic measurements. In this study, we utilized a zero-field OPM to simultaneously measure three-axis components of biomagnetic fields produced by muscle activity in the human forearm caused through independent finger movements, with the goal of recognizing multiple gestures using only a single magnetic sensor. We recorded muscle activity caused by the opening and closing of each finger 60 times, triggered by an auditory tone, and trained a neural network to classify the different finger movements. We utilized the triaxial OPM and trained neural network in a live-testing mode to replicate the participant's hand gestures onto a robotic-hand proxy, with [Formula: see text]s delay, firstly for three fingers (little, middle, and thumb) and subsequently for all five fingers. Using a single OPM sensor, we captured, recognized, and replicated finger gestures from one participant in a controlled laboratory setting. In the three-gesture live test, all three finger movements were identified and replicated with ≥ 98% accuracy. In the five-gesture live test, four out of five fingers were identified and replicated with ≥ 90% accuracy, with the little finger being the most challenging to distinguish with a reduced 45% accuracy. These results demonstrate that a single zero-field OPM sensor in a triaxial measurement scheme can be effectively used for contactless recognition and replication of multiple finger movements, providing a proof-of-concept toward future wearable OPM-based magnetomyography systems.

Indexed as

HandMagnetometryRoboticsWearable Electronic DevicesFingersGesturesHumansMovementNeural Networks, ComputerHuman–machine interfaceMagnetomyographyNeural networkOPM

Identifiers

PMID42092090
PMCPMC13473132

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.