Suppr超能文献

对健全人和运动功能障碍者中一种改良的费茨定律脑机接口目标获取任务的评估。

Evaluation of a modified Fitts law brain-computer interface target acquisition task in able and motor disabled individuals.

作者信息

Felton E A, Radwin R G, Wilson J A, Williams J C

机构信息

Department of Biomedical Engineering, University of Wisconsin-Madison, 53706, USA.

出版信息

J Neural Eng. 2009 Oct;6(5):056002. doi: 10.1088/1741-2560/6/5/056002. Epub 2009 Aug 21.

Abstract

A brain-computer interface (BCI) is a communication system that takes recorded brain signals and translates them into real-time actions, in this case movement of a cursor on a computer screen. This work applied Fitts' law to the evaluation of performance on a target acquisition task during sensorimotor rhythm-based BCI training. Fitts' law, which has been used as a predictor of movement time in studies of human movement, was used here to determine the information transfer rate, which was based on target acquisition time and target difficulty. The information transfer rate was used to make comparisons between control modalities and subject groups on the same task. Data were analyzed from eight able-bodied and five motor disabled participants who wore an electrode cap that recorded and translated their electroencephalogram (EEG) signals into computer cursor movements. Direct comparisons were made between able-bodied and disabled subjects, and between EEG and joystick cursor control in able-bodied subjects. Fitts' law aptly described the relationship between movement time and index of difficulty for each task movement direction when evaluated separately and averaged together. This study showed that Fitts' law can be successfully applied to computer cursor movement controlled by neural signals.

摘要

脑机接口(BCI)是一种通信系统,它获取记录的脑信号并将其转化为实时动作,在本案例中是计算机屏幕上光标的移动。这项工作将菲茨定律应用于基于感觉运动节律的脑机接口训练期间目标获取任务的性能评估。菲茨定律在人体运动研究中一直被用作运动时间的预测指标,在此用于确定基于目标获取时间和目标难度的信息传递速率。信息传递速率用于在相同任务上对控制方式和受试者组进行比较。分析了来自8名身体健全和5名运动功能障碍参与者的数据,这些参与者佩戴电极帽,将他们的脑电图(EEG)信号记录并转化为计算机光标移动。对身体健全和残疾受试者之间,以及身体健全受试者中脑电图和操纵杆光标控制之间进行了直接比较。当分别评估并求平均值时,菲茨定律恰当地描述了每个任务运动方向的运动时间与难度指数之间的关系。这项研究表明,菲茨定律可以成功应用于由神经信号控制的计算机光标移动。

相似文献

1
Evaluation of a modified Fitts law brain-computer interface target acquisition task in able and motor disabled individuals.
J Neural Eng. 2009 Oct;6(5):056002. doi: 10.1088/1741-2560/6/5/056002. Epub 2009 Aug 21.
3
Children with congenital spastic hemiplegia obey Fitts' Law in a visually guided tapping task.
Exp Brain Res. 2007 Mar;177(4):431-9. doi: 10.1007/s00221-006-0698-x. Epub 2006 Sep 22.
4
Hybrid EEG and eye movement interface to multi-directional target selection.
Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:763-6. doi: 10.1109/EMBC.2013.6609612.
5
Conversion of EEG activity into cursor movement by a brain-computer interface (BCI).
IEEE Trans Neural Syst Rehabil Eng. 2004 Sep;12(3):331-8. doi: 10.1109/TNSRE.2004.834627.
6
Cortical correlates of fitts' law.
Front Integr Neurosci. 2011 Dec 22;5:85. doi: 10.3389/fnint.2011.00085. eCollection 2011.
8
Mental workload during brain-computer interface training.
Ergonomics. 2012;55(5):526-37. doi: 10.1080/00140139.2012.662526. Epub 2012 Apr 16.
9
Brain-computer interface (BCI) operation: signal and noise during early training sessions.
Clin Neurophysiol. 2005 Jan;116(1):56-62. doi: 10.1016/j.clinph.2004.07.004.
10
Application of Fitts' law to individuals with cerebral palsy.
Percept Mot Skills. 2002 Jun;94(3 Pt 1):883-95. doi: 10.2466/pms.2002.94.3.883.

引用本文的文献

1
Visual tracking brain-computer interface.
iScience. 2024 Mar 2;27(4):109376. doi: 10.1016/j.isci.2024.109376. eCollection 2024 Apr 19.
2
Using principles of motor control to analyze performance of human machine interfaces.
Sci Rep. 2023 Aug 15;13(1):13273. doi: 10.1038/s41598-023-40446-5.
3
Using Principles of Motor Control to Analyze Performance of Human Machine Interfaces.
Res Sq. 2023 May 16:rs.3.rs-2763325. doi: 10.21203/rs.3.rs-2763325/v1.
4
Use of functional magnetic resonance imaging to assess cognition and consciousness in severe Guillain-Barré syndrome.
Int J Clin Health Psychol. 2023 Apr-Jun;23(2):100347. doi: 10.1016/j.ijchp.2022.100347. Epub 2022 Nov 11.
5
fMRI Brain Decoding and Its Applications in Brain-Computer Interface: A Survey.
Brain Sci. 2022 Feb 7;12(2):228. doi: 10.3390/brainsci12020228.
6
Controlling a Mouse Pointer with a Single-Channel EEG Sensor.
Sensors (Basel). 2021 Aug 14;21(16):5481. doi: 10.3390/s21165481.
9
Advancing brain-machine interfaces: moving beyond linear state space models.
Front Syst Neurosci. 2015 Jul 28;9:108. doi: 10.3389/fnsys.2015.00108. eCollection 2015.
10
Upper Body-Based Power Wheelchair Control Interface for Individuals With Tetraplegia.
IEEE Trans Neural Syst Rehabil Eng. 2016 Feb;24(2):249-60. doi: 10.1109/TNSRE.2015.2439240. Epub 2015 Jun 1.

本文引用的文献

1
Impairments in arm control in subjects with left and right hemisphere stroke.
NeuroRehabilitation. 1997;9(1):71-87. doi: 10.3233/NRE-1997-9107.
3
Impaired motor imagery in right hemiparetic cerebral palsy.
Neuropsychologia. 2007 Mar 2;45(4):853-9. doi: 10.1016/j.neuropsychologia.2006.08.020. Epub 2006 Oct 13.
4
Neuronal ensemble control of prosthetic devices by a human with tetraplegia.
Nature. 2006 Jul 13;442(7099):164-71. doi: 10.1038/nature04970.
5
Imagery of motor actions: differential effects of kinesthetic and visual-motor mode of imagery in single-trial EEG.
Brain Res Cogn Brain Res. 2005 Dec;25(3):668-77. doi: 10.1016/j.cogbrainres.2005.08.014. Epub 2005 Oct 19.
6
Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface.
Neurology. 2005 May 24;64(10):1775-7. doi: 10.1212/01.WNL.0000158616.43002.6D.
7
A brain-computer interface using electrocorticographic signals in humans.
J Neural Eng. 2004 Jun;1(2):63-71. doi: 10.1088/1741-2560/1/2/001. Epub 2004 Jun 14.
8
Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans.
Proc Natl Acad Sci U S A. 2004 Dec 21;101(51):17849-54. doi: 10.1073/pnas.0403504101. Epub 2004 Dec 7.
9
BCI2000: a general-purpose brain-computer interface (BCI) system.
IEEE Trans Biomed Eng. 2004 Jun;51(6):1034-43. doi: 10.1109/TBME.2004.827072.
10
Fitts' Law in two dimensions with hand and head movements.
J Mot Behav. 1985 Mar;17(1):77-95. doi: 10.1080/00222895.1985.10735338.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验