Imagined Speech Datasets Applying Traditional and Gamified Acquisition Paradigms

Recent computational advances have benefited brain-computer interfaces, but human factors have been continuously overlooked. Paradigm design directly impacts users' emotional state, thus impacting brain signal quality. This dataset provides electroencephalographic (EEG) data of 15 participants while performing imagined speech. Each participant performed two paradigms: a traditional paradigm, based on conventional design; and an experimental (gamified) paradigm, based on a video game. All files were pre-processed using EEGLAB. Raw and pre-processed data are provided. Additionally, a set of questionnaires was applied to allow the study of the effects of each paradigm on each participant. First, age and sex were registered. Participants then answered the Internal Representations Questionnaire, which provides individual propensities to different kinds of internal representations. The measured representations are visual imagery, internal verbalization, and orthographic imagery. This questionnaire also provides a self-rating on manipulating mental representations. Participants also answered a Self-Assessment Manikin test before and after each paradigm, to establish emotional state, and a User Experience Questionnaire after each paradigm, to evaluate each paradigm across attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty. The Experimental Paradigm includes vocalized speech after every imagined speech instance. Each vocalized word was registered on a spreadsheet. Instances that contain errors are not recommended for training classification models. Possible applications of this dataset include, but are not limited to: classifying between up to four different imagined speech words, identifying the differences between imagined speech and vocalized speech, and researching the impact of the acquisition paradigm on brain signals quality.近年来计算技术的进步为脑机接口 (brain-computer interface) 领域带来了诸多裨益，但人类因素却长期遭到忽视。范式设计直接影响使用者的情绪状态，进而影响脑信号质量。本数据集收录了15名参与者在完成想象语音任务时的脑电图 (electroencephalogram, EEG) 数据。每名参与者均需完成两种范式任务：一种是基于常规设计的传统范式，另一种是依托电子游戏的实验性（游戏化）范式。所有文件均通过EEGLAB工具完成了预处理，数据集同时提供原始数据与预处理后的数据。此外，本研究还配套了一系列问卷，用于探究不同范式对每名参与者的影响。首先记录了参与者的年龄与性别信息；随后要求参与者填写《内部表征问卷》 (Internal Representations Questionnaire)，该问卷可评估个体对不同类型内部表征的倾向程度。本次评估的表征类型涵盖视觉表象、内部言语表达以及正字法表象。该问卷还包含针对心理表征操控能力的自评条目。每名参与者还需在每种范式任务前后完成《自我评估模拟人量表》 (Self-Assessment Manikin, SAM)，以明确其情绪状态；并在每种范式任务结束后填写《用户体验问卷》 (User Experience Questionnaire, UEQ)，从吸引力、清晰度、效率、可靠性、激励性与新颖性六个维度对该范式进行评价。实验性（游戏化）范式在每一次想象语音任务后均设置了发声语音环节。每一个发声的单词均被记录于电子表格中。包含错误的样本不建议用于分类模型的训练。本数据集的潜在应用场景包括但不限于：对最多4种不同的想象语音词汇进行分类、区分想象语音与发声语音之间的差异，以及探究采集范式对脑信号质量的影响。