• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

脑机接口 (BCI) 控制智能手机中的虚拟助手来管理消息应用程序。

Brain-Computer Interface (BCI) Control of a Virtual Assistant in a Smartphone to Manage Messaging Applications.

机构信息

Departamento de Tecnología Electrónica, Universidad de Málaga, 29071 Málaga, Spain.

出版信息

Sensors (Basel). 2021 May 26;21(11):3716. doi: 10.3390/s21113716.

DOI:10.3390/s21113716
PMID:34073602
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8199460/
Abstract

Brain-computer interfaces (BCI) are a type of assistive technology that uses the brain signals of users to establish a communication and control channel between them and an external device. BCI systems may be a suitable tool to restore communication skills in severely motor-disabled patients, as BCI do not rely on muscular control. The loss of communication is one of the most negative consequences reported by such patients. This paper presents a BCI system focused on the control of four mainstream messaging applications running in a smartphone: WhatsApp, Telegram, e-mail and short message service (SMS). The control of the BCI is achieved through the well-known visual P300 row-column paradigm (RCP), allowing the user to select control commands as well as spelling characters. For the control of the smartphone, the system sends synthesized voice commands that are interpreted by a virtual assistant running in the smartphone. Four tasks related to the four mentioned messaging services were tested with 15 healthy volunteers, most of whom were able to accomplish the tasks, which included sending free text e-mails to an address proposed by the subjects themselves. The online performance results obtained, as well as the results of subjective questionnaires, support the viability of the proposed system.

摘要

脑机接口(BCI)是一种辅助技术,它利用用户的脑信号在他们和外部设备之间建立一个通信和控制通道。BCI 系统可能是一种恢复严重运动障碍患者的交流技能的合适工具,因为 BCI 不依赖于肌肉控制。丧失交流能力是这些患者报告的最负面后果之一。本文提出了一个专注于控制智能手机中运行的四个主流消息应用程序的 BCI 系统:WhatsApp、Telegram、电子邮件和短信服务(SMS)。BCI 的控制是通过著名的视觉 P300 行-列范式(RCP)实现的,允许用户选择控制命令和拼写字符。对于智能手机的控制,系统会发送合成语音命令,由智能手机中运行的虚拟助手进行解释。该系统用 15 名健康志愿者测试了与上述四个消息服务相关的四个任务,其中大多数志愿者都能够完成任务,包括向用户自己提出的地址发送免费的电子邮件。所获得的在线性能结果以及主观问卷的结果支持了所提出的系统的可行性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/d18ca5906db5/sensors-21-03716-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/22c5dc183300/sensors-21-03716-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/f74966e7c384/sensors-21-03716-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/1b40a1777631/sensors-21-03716-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/a5cc2055b285/sensors-21-03716-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/778b6e9e97d2/sensors-21-03716-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/ce3c7445e113/sensors-21-03716-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/34bf32864e0e/sensors-21-03716-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/d18ca5906db5/sensors-21-03716-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/22c5dc183300/sensors-21-03716-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/f74966e7c384/sensors-21-03716-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/1b40a1777631/sensors-21-03716-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/a5cc2055b285/sensors-21-03716-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/778b6e9e97d2/sensors-21-03716-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/ce3c7445e113/sensors-21-03716-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/34bf32864e0e/sensors-21-03716-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a551/8199460/d18ca5906db5/sensors-21-03716-g008.jpg

相似文献

1
Brain-Computer Interface (BCI) Control of a Virtual Assistant in a Smartphone to Manage Messaging Applications.脑机接口 (BCI) 控制智能手机中的虚拟助手来管理消息应用程序。
Sensors (Basel). 2021 May 26;21(11):3716. doi: 10.3390/s21113716.
2
How many people are able to control a P300-based brain-computer interface (BCI)?有多少人能够操控基于P300的脑机接口(BCI)?
Neurosci Lett. 2009 Oct 2;462(1):94-8. doi: 10.1016/j.neulet.2009.06.045. Epub 2009 Jun 21.
3
Brain-computer interfaces for communication and control.用于通信和控制的脑机接口。
Clin Neurophysiol. 2002 Jun;113(6):767-91. doi: 10.1016/s1388-2457(02)00057-3.
4
Hybrid P300-based brain-computer interface to improve usability for people with severe motor disability: electromyographic signals for error correction during a spelling task.基于P300的混合式脑机接口,以提高重度运动障碍患者的可用性:拼写任务期间用于纠错的肌电信号。
Arch Phys Med Rehabil. 2015 Mar;96(3 Suppl):S54-61. doi: 10.1016/j.apmr.2014.05.029.
5
UMA-BCI Speller: An easily configurable P300 speller tool for end users.UMA-BCI Speller:面向终端用户的、易于配置的 P300 拼写工具。
Comput Methods Programs Biomed. 2019 Apr;172:127-138. doi: 10.1016/j.cmpb.2019.02.015. Epub 2019 Mar 1.
6
An Asynchronous P300-Based Brain-Computer Interface Web Browser for Severely Disabled People.一款面向严重残疾人士的基于异步P300的脑机接口网络浏览器。
IEEE Trans Neural Syst Rehabil Eng. 2017 Aug;25(8):1332-1342. doi: 10.1109/TNSRE.2016.2623381. Epub 2016 Oct 31.
7
A Symbols Based BCI Paradigm for Intelligent Home Control Using P300 Event-Related Potentials.基于符号的 P300 事件相关电位脑-机接口范式在智能家庭控制中的应用。
Sensors (Basel). 2022 Dec 19;22(24):10000. doi: 10.3390/s222410000.
8
A hybrid brain-computer interface-based mail client.基于混合脑机接口的邮件客户端。
Comput Math Methods Med. 2013;2013:750934. doi: 10.1155/2013/750934. Epub 2013 Apr 18.
9
A brain-computer interface controlled auditory event-related potential (p300) spelling system for locked-in patients.一种用于闭锁综合征患者的脑机接口控制听觉事件相关电位(P300)拼写系统。
Ann N Y Acad Sci. 2009 Mar;1157:90-100. doi: 10.1111/j.1749-6632.2008.04122.x.
10
P300 Brain-Computer Interface-Based Drone Control in Virtual and Augmented Reality.基于 P300 脑-机接口的虚拟现实和增强现实中的无人机控制。
Sensors (Basel). 2021 Aug 27;21(17):5765. doi: 10.3390/s21175765.

引用本文的文献

1
Paradigms and methods of noninvasive brain-computer interfaces in motor or communication assistance and rehabilitation: a systematic review.用于运动或交流辅助及康复的非侵入性脑机接口的范式与方法:一项系统综述
Med Biol Eng Comput. 2025 Mar 10. doi: 10.1007/s11517-025-03340-y.
2
Electroencephalogram-based adaptive closed-loop brain-computer interface in neurorehabilitation: a review.神经康复中基于脑电图的自适应闭环脑机接口:综述
Front Comput Neurosci. 2024 Sep 20;18:1431815. doi: 10.3389/fncom.2024.1431815. eCollection 2024.
3
State-of-the-Art on Brain-Computer Interface Technology.

本文引用的文献

1
Review of brain encoding and decoding mechanisms for EEG-based brain-computer interface.基于脑电图的脑机接口的脑编码与解码机制综述
Cogn Neurodyn. 2021 Aug;15(4):569-584. doi: 10.1007/s11571-021-09676-z. Epub 2021 Apr 10.
2
Effect of Static Posture on Online Performance of P300-Based BCIs for TV Control.静态姿势对基于 P300 的脑机接口用于电视控制的在线性能的影响。
Sensors (Basel). 2021 Mar 24;21(7):2278. doi: 10.3390/s21072278.
3
TeleBCI: remote user training, monitoring, and communication with an evoked-potential brain-computer interface.
脑机接口技术的最新进展。
Sensors (Basel). 2023 Jun 28;23(13):6001. doi: 10.3390/s23136001.
4
SSVEP detection assessment by combining visual stimuli paradigms and no-training detection methods.通过结合视觉刺激范式和无训练检测方法进行稳态视觉诱发电位检测评估
Front Neurosci. 2023 May 18;17:1142892. doi: 10.3389/fnins.2023.1142892. eCollection 2023.
5
Denoising Autoencoder-Based Feature Extraction to Robust SSVEP-Based BCIs.基于去噪自动编码器的特征提取在稳健基于 SSVEP 的脑机接口中的应用。
Sensors (Basel). 2021 Jul 23;21(15):5019. doi: 10.3390/s21155019.
远程脑机接口(TeleBCI):通过诱发电位脑机接口进行远程用户培训、监测和通信。
Brain Comput Interfaces (Abingdon). 2020;7(3-4):57-69. doi: 10.1080/2326263X.2020.1848134. Epub 2020 Nov 18.
4
Different effects of using pictures as stimuli in a P300 brain-computer interface under rapid serial visual presentation or row-column paradigm.在快速序列视觉呈现或行列范式下,使用图片作为刺激时 P300 脑机接口的不同效果。
Med Biol Eng Comput. 2021 Apr;59(4):869-881. doi: 10.1007/s11517-021-02340-y. Epub 2021 Mar 20.
5
P300-Based Brain-Computer Interface Speller: Usability Evaluation of Three Speller Sizes by Severely Motor-Disabled Patients.基于P300的脑机接口拼写器:重度运动功能障碍患者对三种拼写器尺寸的可用性评估
Front Hum Neurosci. 2020 Oct 29;14:583358. doi: 10.3389/fnhum.2020.583358. eCollection 2020.
6
Smart home and communication technology for people with disability: a scoping review.智能家居和通信技术在残疾人士中的应用:综述研究
Disabil Rehabil Assist Technol. 2022 Aug;17(6):624-644. doi: 10.1080/17483107.2020.1818138. Epub 2020 Sep 12.
7
Towards an Accessible Use of a Brain-Computer Interfaces-Based Home Care System through a Smartphone.通过智能手机实现对基于脑机接口的家庭护理系统的无障碍使用。
Comput Intell Neurosci. 2020 Aug 28;2020:1843269. doi: 10.1155/2020/1843269. eCollection 2020.
8
A comprehensive assessment of Brain Computer Interfaces: Recent trends and challenges.脑机接口的全面评估:最新趋势与挑战
J Neurosci Methods. 2020 Dec 1;346:108918. doi: 10.1016/j.jneumeth.2020.108918. Epub 2020 Aug 25.
9
Mainstream technology to support basic communication and leisure in people with neurological disorders, motor impairment and lack of speech.主流技术支持神经系统障碍、运动障碍和言语缺失人群的基本交流和休闲。
Brain Inj. 2020 Jun 6;34(7):921-927. doi: 10.1080/02699052.2020.1763462. Epub 2020 May 22.
10
A self-paced BCI prototype system based on the incorporation of an intelligent environment-understanding approach for rehabilitation hospital environmental control.一种基于融合智能环境理解方法的自定进度脑机接口原型系统,用于康复医院环境控制。
Comput Biol Med. 2020 Mar;118:103618. doi: 10.1016/j.compbiomed.2020.103618. Epub 2020 Jan 15.