Determining sensor geometry and gain in a wearable MEG system

可穿戴计算机 几何学 计算机科学 物理 数学 嵌入式系统
作者
Ryan M. Hill,G. Rivero,Ashley J. Tyler,Holly Schofield,Cody Doyle,James Osborne,David Bobela,Lukas Rier,J. M. Gibson,Zoe Tanner,Elena Boto,Richard Bowtell,Matthew J. Brookes,Vishal Shah,Niall Holmes
出处
期刊:Cornell University - arXiv [Cornell University]
标识
DOI:10.48550/arxiv.2410.08718
摘要

Optically pumped magnetometers (OPMs) are compact and lightweight sensors that can measure magnetic fields generated by current flow in neuronal assemblies in the brain. Such sensors enable construction of magnetoencephalography (MEG) instrumentation, with significant advantages over conventional MEG devices including adaptability to head size, enhanced movement tolerance, lower complexity and improved data quality. However, realising the potential of OPMs depends on our ability to perform system calibration, which means finding sensor locations, orientations, and the relationship between the sensor output and magnetic field (termed sensor gain). Such calibration is complex in OPMMEG since, for example, OPM placement can change from subject to subject (unlike in conventional MEG where sensor locations or orientations are fixed). Here, we present two methods for calibration, both based on generating well-characterised magnetic fields across a sensor array. Our first device (the HALO) is a head mounted system that generates dipole like fields from a set of coils. Our second (the matrix coil (MC)) generates fields using coils embedded in the walls of a magnetically shielded room. Our results show that both methods offer an accurate means to calibrate an OPM array (e.g. sensor locations within 2 mm of the ground truth) and that the calibrations produced by the two methods agree strongly with each other. When applied to data from human MEG experiments, both methods offer improved signal to noise ratio after beamforming suggesting that they give calibration parameters closer to the ground truth than factory settings and presumed physical sensor coordinates and orientations. Both techniques are practical and easy to integrate into real world MEG applications. This advances the field significantly closer to the routine use of OPMs for MEG recording.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
闪闪荔枝关注了科研通微信公众号
1秒前
田李君完成签到,获得积分10
1秒前
gin完成签到,获得积分10
4秒前
在水一方应助cs采纳,获得10
6秒前
7秒前
7秒前
杨颜静完成签到,获得积分10
7秒前
7秒前
8秒前
9秒前
12秒前
wanci应助song采纳,获得10
12秒前
闪闪荔枝发布了新的文献求助30
13秒前
13秒前
LTT关注了科研通微信公众号
14秒前
外向的芙发布了新的文献求助10
14秒前
一一完成签到,获得积分10
17秒前
cs发布了新的文献求助10
18秒前
19秒前
19秒前
申子完成签到,获得积分20
19秒前
Nole应助慈祥的人生采纳,获得10
19秒前
tuotuo发布了新的文献求助10
19秒前
20秒前
大胆迎梅完成签到,获得积分10
21秒前
TEDDY发布了新的文献求助10
24秒前
Lucas应助秋秋大宝贝采纳,获得10
24秒前
搜集达人应助1111采纳,获得10
24秒前
25秒前
26秒前
温暖砖头完成签到,获得积分10
27秒前
精明的文涛应助甜甜冬寒采纳,获得10
28秒前
Nole应助tong采纳,获得10
30秒前
30秒前
LTT发布了新的文献求助10
31秒前
RNAPW发布了新的文献求助10
31秒前
Hello应助细腻的雅阳采纳,获得10
32秒前
整齐以亦发布了新的文献求助10
32秒前
33秒前
Function发布了新的文献求助10
34秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 2000
Advanced Weaponeering Fourth Edition, Volume 2 1000
Weaponeering: An Introduction Fourth Edition, Volume 1 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7554722
求助须知:如何正确求助?哪些是违规求助? 9137165
关于积分的说明 19529071
捐赠科研通 7146014
什么是DOI,文献DOI怎么找? 3260905
关于科研通互助平台的介绍 2427347
邀请新用户注册赠送积分活动 2249908