已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

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
年少丶完成签到,获得积分10
3秒前
4秒前
热爱科研的小孩完成签到,获得积分10
5秒前
年少丶发布了新的文献求助10
6秒前
大模型应助负责真采纳,获得10
7秒前
9秒前
徐1完成签到 ,获得积分10
10秒前
BryanLo发布了新的文献求助10
11秒前
难过白易完成签到,获得积分10
16秒前
16秒前
CC完成签到,获得积分10
17秒前
18秒前
lixinglei应助江子川采纳,获得20
21秒前
VV2001发布了新的文献求助10
22秒前
111完成签到 ,获得积分10
23秒前
所所应助调皮的凝丹采纳,获得10
23秒前
24秒前
28秒前
00hello00发布了新的文献求助10
28秒前
朴实的懿轩完成签到,获得积分10
29秒前
zkl完成签到,获得积分10
29秒前
Leofar完成签到 ,获得积分10
29秒前
负责真发布了新的文献求助10
30秒前
30秒前
嘻嘻完成签到 ,获得积分20
32秒前
36秒前
所所应助科研通管家采纳,获得10
37秒前
灰雁应助科研通管家采纳,获得10
38秒前
斯文败类应助科研通管家采纳,获得10
38秒前
38秒前
38秒前
38秒前
慕青应助科研通管家采纳,获得10
38秒前
38秒前
38秒前
灰雁应助科研通管家采纳,获得10
38秒前
IMP完成签到 ,获得积分10
42秒前
47秒前
49秒前
Nodens完成签到,获得积分10
50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 5000
Pediatric Dermoscopy Trichoscopy & Onychoscopy 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
International Security Studies and Technology :Approaches, Assessments, and Frontiers 500
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 7571366
求助须知:如何正确求助?哪些是违规求助? 9150932
关于积分的说明 19572452
捐赠科研通 7156453
什么是DOI,文献DOI怎么找? 3264043
关于科研通互助平台的介绍 2429357
邀请新用户注册赠送积分活动 2254183