标题： 用于连续小波分析的新软件能够在便携式计算机上对脑电图进行实时分析 显示英文标题

标题： Novel software for continuous wavelet analysis enable EEG real-time analysis on portable computers

摘要： 连续小波变换（CWT）常用于波形分析。 例如，在神经科学研究领域，CWT 被用来分析脑电图（EEG）并计算脑活动指数。 计算机技术的最新进展，如图形处理单元通用计算（GPGPU），使得 CWT 可以应用于实时波形分析。 然而，CWT 的计算复杂度较高，并且将其作为实时分析方法（例如在需要小型化和低成本的脑机接口 BMI 中）具有挑战性。 因此，需要一种适合小型轻量级计算机的快速计算方法。 本研究开发并测试了基于 Python 的 CWT 软件，并在便携式计算机上进行了验证。 使用该软件，基于 CWT 的 64 电极 EEG 数据实时分析被模拟，并展示了足够的实时分析速度。 此外，它还表现出在使用各种参数时执行 CWT 的灵活性。 该软件有助于紧凑型和轻量级 BMI 设备的发展。 由于 CWT 是一种数学方法，它可能被用作其他用途的工具。 显示英文摘要

摘要： Continuous Wavelet Transform (CWT) is frequently used for waveform analysis. For example, in the field of neuroscience research, CWT is performed to analyze electroencephalograms (EEG) and calculate the index of brain activity. Recent advancements in computer technology, such as general-purpose computing on Graphics Processing Units (GPGPU), have enabled the application of CWT to real-time waveform analysis. However, the computational complexity of CWT is large, and it is challenging to employ CWT as a real-time analysis method, such as in brain-machine interfaces (BMI), which require small size and cost. Therefore, a fast calculation method suitable for small and lightweight computers is desired. In this study, Python-based software for the CWT was developed and tested on portable computers. Using this software, real-time analysis of 64-electrode EEG data based on CWT was simulated and demonstrated adequate speed for the real-time analysis. Furthermore, it exhibited flexibility in performing CWT with various parameters. This software can contribute to the development of compact and lightweight BMI devices. Since CWT is a mathematical method, it may be used as a tool for other purposes.