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
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
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
悦耳的黑米关注了科研通微信公众号
2秒前
2秒前
还在考虑完成签到,获得积分10
3秒前
3秒前
3秒前
zjspidany举报求助违规成功
4秒前
加菲丰丰举报求助违规成功
4秒前
Leif举报求助违规成功
4秒前
4秒前
Olivia完成签到 ,获得积分10
5秒前
Cast_Lappland发布了新的文献求助10
5秒前
Hello应助拓跋涵易采纳,获得10
5秒前
7秒前
赘婿应助Eskimo采纳,获得30
7秒前
七里香发布了新的文献求助10
7秒前
Augenstern发布了新的文献求助10
8秒前
三月聚粮应助健忘的初翠采纳,获得10
8秒前
理想三寻完成签到,获得积分10
9秒前
Cast_Lappland完成签到,获得积分10
10秒前
showmaker发布了新的文献求助10
10秒前
调研昵称发布了新的文献求助10
11秒前
科研通AI2S应助浅辰采纳,获得10
12秒前
zjspidany举报求助违规成功
15秒前
加菲丰丰举报求助违规成功
15秒前
Leif举报求助违规成功
15秒前
15秒前
16秒前
18秒前
充电宝应助苞米公主采纳,获得10
19秒前
20秒前
21秒前
23秒前
共享精神应助zhaoqiang采纳,获得10
25秒前
田様应助小鱼鱼采纳,获得10
26秒前
sissiarno应助科研通管家采纳,获得30
27秒前
英俊的铭应助科研通管家采纳,获得10
27秒前
领导范儿应助科研通管家采纳,获得10
27秒前
852应助科研通管家采纳,获得10
27秒前
8R60d8应助科研通管家采纳,获得10
27秒前
27秒前
高分求助中
Licensing Deals in Pharmaceuticals 2019-2024 3000
Cognitive Paradigms in Knowledge Organisation 2000
Introduction to Spectroscopic Ellipsometry of Thin Film Materials Instrumentation, Data Analysis, and Applications 1800
Natural History of Mantodea 螳螂的自然史 1000
A Photographic Guide to Mantis of China 常见螳螂野外识别手册 800
How Maoism Was Made: Reconstructing China, 1949-1965 800
Barge Mooring (Oilfield Seamanship Series Volume 6) 600
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3314062
求助须知:如何正确求助?哪些是违规求助? 2946490
关于积分的说明 8530274
捐赠科研通 2622160
什么是DOI,文献DOI怎么找? 1434341
科研通“疑难数据库(出版商)”最低求助积分说明 665242
邀请新用户注册赠送积分活动 650804