EAGER: Adapting Multi-Modal BCI-Based Assistive Technologies for Patients with High Spinal Cord Injury
EAGER: Adapting Multi-Modal BCI-Based Assistive Technologies for Patients with High Spinal Cord Injury
批准号:
1841087
负责人:
Laleh Najafizadeh
金额:
$12.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-06-15 至 2022-05-31
中文摘要
本研究的目的是推动脑机接口(BCI)技术的发展,使该技术更接近于高度脊髓损伤(SCI)患者的需求。虽然基于脑接口的辅助技术通过使脊髓损伤患者能够独立进行日常生活的简单活动来改善他们的生活质量,但有几个因素阻碍了它们在实际和临床环境中的成功应用。造成这一问题的一个主要因素与由脊髓损伤引起的继发性健康状况(如慢性疼痛)有关,但在脑损伤研究中基本上被忽视了。疼痛的存在会对从脑机接口获得的控制信号产生负面影响,从而影响辅助装置的操作,从而增加患者的压力、不适和抑郁。通过创新的方法和实验,本研究旨在探讨疼痛的存在如何影响多模态脑机接口的操作,从而促进科学的进步。通过对疼痛的影响的理解,本研究的结果有望为开发有效的方法提供指导,以实现对脊髓损伤患者稳健和高性能的基于bci的辅助技术。该项目还将为STEM领域的非代表性研究人员提供教育和推广活动。本研究旨在推动无创多模态脑机接口(BCI)技术的发展,使该技术更贴近高位脊髓损伤(SCI)患者的需求。通过脑电图(EEG)和功能性近红外光谱(fNIRS)在两个不同的生理水平上收集大脑的信息,可以增加控制辅助设备所需的命令数量。采用创新的方法,该项目将研究疼痛的存在(不幸的是,大多数SCI患者都生活在疼痛中)如何影响多模式脑机接口的操作。考虑了不同类别的多模态脑机接口。该项目的研究结果有望为制定有效的策略和方法提供重要信息和指导,为真正需要的SCI患者实现基于bci的鲁棒性和高性能辅助技术。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The goal of this research is to advance the brain computer interface (BCI) technology by bringing the technology closer to the needs of patients with high spinal cord injury (SCI). While BCI-based assistive technologies hold a great promise to improve the quality of life of patients with SCI by enabling them to independently perform simple activities of their daily life, several factors have prevented their successful application in practical and clinical settings. A major contributing factor to this problem is related to the secondary health conditions (e.g. chronic pain) that are developed as a result of SCI, but have been largely ignored in BCI research. The presence of pain can negatively impact the control signals acquired from BCIs, and consequently, compromise the operation of the assistive device, thereby, adding to stress, discomfort, and depression for the patient. Using innovative approaches and experiments, this research aims to investigate how the presence of pain impacts the operation of multi-modal BCIs, thereby, promoting the progress of science. By providing an understanding of the effects that pain, the outcome of this work is expected to provide guidelines for developing effective methods for realizing robust and high-performance BCI-based assistive technologies for SCI patients. This project will also offer educational and outreach activities for the unrepresentative researches working in a STEM field.This research aims to advance the non-invasive multi-modal brain computer interface (BCI) technology by bringing the technology closer to the needs of patients with high spinal cord injury (SCI). By collecting information from the brain at two different physiological levels via electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS), the number of commands required for controlling assistive devices can be increased. Using innovative approaches, the project will investigate how the presence of pain, a condition that unfortunately most SCI patients live with, will influence the operation of multi-modal BCIs. Different classes of multi-modal BCIs are considered. The results from this project are expected to provide important information and guidelines for developing effective strategies and methods for realizing robust and high-performance BCI-based assistive technologies for SCI patients who are in real need of them.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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On the Effects of Pain on fNIRS Classification
疼痛对 fNIRS 分类的影响
DOI:
--
发表时间:
2020
期刊:
The OSA Biophotonics Congress
影响因子:
--
作者:
[Shamsi, F., Najafizadeh, L.]
通讯作者:
Najafizadeh, L.
On the Reliability of Frequency-Domain Features for fNIRS BCIs in the Presence of Pain
存在疼痛时 fNIRS BCI 频域特征的可靠性
DOI:
10.1109/spmb52430.2021.9672256
发表时间:
2021
期刊:
IEEE Signal Processing in Medicine and Biology Symposium (SPMB
影响因子:
--
作者:
[Subramanian, A., Shamsi, F., Najafizadeh, L.]
通讯作者:
Najafizadeh, L.
Recognizing Pain in Motor Imagery EEG Recordings Using Dynamic Functional Connectivity Graphs
使用动态功能连接图识别运动想象脑电图记录中的疼痛
DOI:
10.1109/embc44109.2020.9175627
发表时间:
2020
期刊:
42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC
影响因子:
--
作者:
[Shamsi, Foroogh, Haddad, Ali, Najafizadeh, Laleh]
通讯作者:
Najafizadeh, Laleh
DOI:
10.1109/spmb47826.2019.9037856
发表时间:
2019-12
期刊:
2019 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)
影响因子:
--
作者:
[F. Shamsi;L. Najafizadeh]
通讯作者:
F. Shamsi;L. Najafizadeh
NCS-FO: Uncovering Dynamics of Neural Activity of Subjective Estimation of Time
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批准号:2319518
-
项目类别:Continuing Grant
-
资助金额:$87.91万
-
财政年份:2023
-
负责人:Laleh Najafizadeh
-
依托单位:
Probing Neural Connectivity at Multiple Temporal Scales
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批准号:1605646
-
项目类别:Standard Grant
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资助金额:$36.33万
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财政年份:2016
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负责人:Laleh Najafizadeh
-
依托单位:
海外基金