"数羊 PSG":与 EEGLAB 兼容的开放源码 MATLAB 软件,用于多导睡眠图数据的信号处理、可视化、事件标记和分期。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-05-11 DOI:10.1016/j.jneumeth.2024.110162
L.B. Ray , D. Baena , S.M. Fogel
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引用次数: 0

摘要

背景:利用多导睡眠图(PSG)推进睡眠研究的进展受到了广泛可用的开源睡眠专用分析工具有限的负面影响:新方法:我们在此介绍计数羊 PSG,这是一款与 EEGLAB 兼容的软件,用于 MATLAB PSG 数据的信号处理、可视化、事件标记和手动睡眠阶段评分:主要功能包括(1) 信号处理工具,包括坏道插值、下采样、重参照、滤波、独立成分分析、伪像子空间重构和功率谱分析;(2) 多导睡眠图数据和催眠图的自定义显示;(3) 事件标记模式,包括手动睡眠阶段评分;(4) 自动事件检测,包括运动伪像、睡眠棘波、慢波和眼球运动;(5) 导出主要描述性睡眠结构统计、事件统计和可发表的催眠图:数羊 PSG 是在 sleepSMG(https://sleepsmg.sourceforge.net/)的基础上发展起来的。当前软件的范围和功能在 EEGLAB 集成/兼容性、预处理、伪影校正、事件检测、功能性和易用性方面都取得了显著进步。相比之下,商业软件可能成本高昂,并使用专有数据格式和算法,从而限制了分发和共享数据及分析结果的能力:睡眠研究领域仍然受制于一个抵制标准化、阻碍互操作性、计划性淘汰、保留专有黑盒数据格式和分析方法的行业。这给睡眠研究领域带来了重大挑战。要想在这一领域取得科学进步,就必须要有能读取开放格式数据的免费开源软件。
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“Counting sheep PSG”: EEGLAB-compatible open-source matlab software for signal processing, visualization, event marking and staging of polysomnographic data

Background

Progress in advancing sleep research employing polysomnography (PSG) has been negatively impacted by the limited availability of widely available, open-source sleep-specific analysis tools.

New method

Here, we introduce Counting Sheep PSG, an EEGLAB-compatible software for signal processing, visualization, event marking and manual sleep stage scoring of PSG data for MATLAB.

Results

Key features include: (1) signal processing tools including bad channel interpolation, down-sampling, re-referencing, filtering, independent component analysis, artifact subspace reconstruction, and power spectral analysis, (2) customizable display of polysomnographic data and hypnogram, (3) event marking mode including manual sleep stage scoring, (4) automatic event detections including movement artifact, sleep spindles, slow waves and eye movements, and (5) export of main descriptive sleep architecture statistics, event statistics and publication-ready hypnogram.

Comparison with existing methods

Counting Sheep PSG was built on the foundation created by sleepSMG (https://sleepsmg.sourceforge.net/). The scope and functionalities of the current software have made significant advancements in terms of EEGLAB integration/compatibility, preprocessing, artifact correction, event detection, functionality and ease of use. By comparison, commercial software can be costly and utilize proprietary data formats and algorithms, thereby restricting the ability to distribute and share data and analysis results.

Conclusions

The field of sleep research remains shackled by an industry that resists standardization, prevents interoperability, builds-in planned obsolescence, maintains proprietary black-box data formats and analysis approaches. This presents a major challenge for the field of sleep research. The need for free, open-source software that can read open-format data is essential for scientific advancement to be made in the field.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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