Brainwaves are the electrical impulses generated by the brain's neurons when they communicate with each other. These waves are measured using an electroencephalogram (EEG), a device that detects and records the brain's electrical activity. There are several types of brainwaves, each associated with different mental states and activities.
脑电波是大脑神经元相互通信时产生的电脉冲。这些波通过使用脑电图（EEG）来测量，这是一种检测和记录大脑电活动的设备。有几种类型的脑电波，每一种都与不同的精神状态和活动相关。
Delta Waves (0.5-4 Hz): Delta waves are the slowest brainwaves and are associated with deep sleep, unconsciousness, and regeneration. They are also observed in states of deep meditation and trance.
三角洲波（0.5-4 Hz）： 三角洲波是最慢的脑电波，与深睡眠、失去意识和再生有关。它们也观察到在深度冥想和恍惚状态。
Theta Waves (4-8 Hz): Theta waves are present during light sleep, dreaming, deep meditation, and creativity. They are associated with the subconscious mind and are involved in memory formation and intuition.
Theta波（4-8 Hz）： Theta波在轻度睡眠、梦境、深度冥想和创造力发挥作用。它们与潜意识有关，并参与记忆形成和直觉。
Alpha Waves (8-12 Hz): Alpha waves are dominant during wakeful relaxation, such as during meditation or when the mind is in a calm, idle state. They are associated with increased creativity and enhanced learning.
阿尔法波（8-12 Hz）： 阿尔法波在清醒的放松状态下占主导地位，例如在冥想时或当思维处于平静、空闲状态时。它们与增强创造力和增强学习有关。
Beta Waves (12-30 Hz): Beta waves are present during active thinking, concentration, and alertness. They are associated with cognitive tasks, problem-solving, and decision-making.
β波（12-30 Hz）： β波在主动思考、专注和警觉时存在。它们与认知任务、问题解决和决策有关。
Gamma Waves (30-100 Hz): Gamma waves are the fastest brainwaves and are associated with higher mental processes such as perception, consciousness, and memory recall. They are also linked to peak concentration and cognitive functioning.
γ波（30-100 Hz）： γ波是最快的脑电波，与更高级别的心理过程如感知、意识和记忆召回有关。它们也与最高浓度和认知功能相关联。
Understanding brainwaves provides valuable insights into the functioning of the human mind and can be used in various fields, including neuroscience, psychology, and medicine.
理解脑电波提供了对人类思维功能的宝贵见解，并可在多个领域中使用，包括神经科学、心理学和医学。
以下是两篇关于脑电波的文章摘录：
Researchers from the University of California, San Francisco, have made a significant breakthrough in the field of brain-computer interfaces (BCIs). They have developed a device that can translate the brain waves of a patient who is unable to speak into full sentences. This advancement brings us one step closer to the sci-fi concept of "mind reading." The device, known as a "speech neuroprosthetic," works by receiving and analyzing brain waves that control the speech production mechanisms. It captures the brain signals associated with the movements of the lips, jaw, tongue, and larynx, and translates them into verbal language. The research was published in the "New England Journal of Medicine" and has been praised by peers in the field.
加州大学旧金山分校的研究人员在脑机接口（BCI）领域取得了重大突破。他们开发了一种设备，能够将无法说话的患者的脑电波转换成完整的句子。这一进步使我们更接近于科幻概念中的“读心术”。这种设备被称为“言语神经义肢”，它的工作原理是接收和分析控制言语产生机制的脑电波。它捕捉与嘴唇、下颌、舌头和喉部运动相关的大脑信号，并将其翻译成口头语言。这项研究发表在《新英格兰医学杂志》上，并得到了该领域同行的赞誉。
The DeWave model segments brain wave signals into different units to capture specific features and patterns. By learning from a vast amount of brain wave data, the model has acquired the ability to convert electroencephalogram (EEG) signals into words and sentences. This technology can not only assist individuals with diseases or injuries (such as stroke or paralysis) who have lost the ability to speak but also enable seamless communication between humans and machines, such as the operation of prosthetic limbs or robots. Previous methods of converting brain signals to language required either surgical implantation of electrodes in the brain (like Neuralink by Musk) or scanning in an MRI machine. The former is invasive, and the latter is bulky, expensive, and not easily usable in daily life. Moreover, these methods generally require additional tools like eye-tracking to assist in converting brain signals into word-level fragments, which is not a limitation for BrainGPT.
DeWave模型将脑电波信号分割成不同的单元，从中捕获特定的特征和模式。通过从大量脑电数据中学习，该模型已经获得了将脑电图（EEG）信号转换为单词和句子的能力。这项技术不仅可以帮助因疾病或受伤（如中风或瘫痪）而失去说话能力的人，还可以实现人与机器之间的无缝通信，例如仿生肢体或机器人的操作。以前将大脑信号转换为语言的技术，要么需要在大脑中植入电极（例如马斯克的Neuralink），要么在MRI机器中扫描。前者为侵入性，而后者体积大，价格昂贵，且难以在日常生活中使用。此外，这些方法通常需要额外的工具，如眼动追踪，以帮助将大脑信号转换为单词级片段，而BrainGPT没有这个限制。