Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.
Assist Technol. 2013 Summer;25(2):99-110. doi: 10.1080/10400435.2012.723298.
Electroencephalography (EEG) is a non-invasive method for measuring brain activity and is a strong candidate for brain-computer interface (BCI) development. While BCIs can be used as a means of communication for individuals with severe disabilities, the majority of existing studies have reported BCI evaluations by able-bodied individuals. Considering the many differences in body functions and usage scenarios between individuals with disabilities and able-bodied individuals, involvement of the target population in BCI evaluation is necessary. In this review, 39 studies reporting EEG-oriented BCI assessment by individuals with disabilities were identified in the past decade. With respect to participant populations, a need for assessing BCI performance for the pediatric population with severe disabilities was identified as an important future direction. Acquiring a reliable communication pathway during early stages of development is crucial in avoiding learned helplessness in pediatric-onset disabilities. With respect to evaluation, augmenting traditional measures of system performance with those relating to contextual factors was recommended for realizing user-centered designs appropriate for integration in real-life. Considering indicators of user state and developing more effective training paradigms are recommended for future studies of BCI involving individuals with disabilities.
脑电图（EEG）是一种测量大脑活动的非侵入性方法，是脑机接口（BCI）开发的有力候选者。虽然 BCI 可以作为严重残疾个体的交流手段，但大多数现有研究都报告了健全个体的 BCI 评估。考虑到残疾个体和健全个体在身体功能和使用场景方面存在许多差异，因此需要目标人群参与 BCI 评估。在这篇综述中，确定了过去十年中报告由残疾个体进行的以脑电图为导向的 BCI 评估的 39 项研究。就参与者群体而言，需要评估患有严重残疾的儿科人群的 BCI 性能，这是一个重要的未来方向。在儿童发病残疾的早期阶段获得可靠的沟通途径对于避免习得性无助至关重要。在评估方面，建议将与上下文因素相关的传统系统性能指标与传统指标相结合，以实现适合真实生活集成的以用户为中心的设计。对于涉及残疾个体的 BCI 的未来研究，建议考虑用户状态的指标并开发更有效的训练范例。
