請點選參考產品介紹

BESA Research

Choose the best signal processing for your EEG and MEG data

BESA Research has been developed on the basis of 30 years experience in human brain research by Michael Scherg, University of Heidelberg, and Patrick Berg, University of Konstanz.
BESA Research is a highly versatile and user-friendly Windows® program with optimized tools and scripts to preprocess raw or averaged data for source analysis. All important aspects of source analysis are displayed in one window for immediate selection of a wide range of tools. BESA Research provides fast and easy hypothesis testing, a variety of source analysis algorithms, integration with MRI and fMRI, standardized realistic head models (FEM) as well as the possibility to import individual head models (FEM) generated by BESA MRI 2.0 .

Source coherence, an unique feature for viewing brain activity

The Source Coherence Module provides an extremely fast and user-friendly implementation of time-frequency analysis based on complex demodulation. Users can create event-related time-frequency displays of power, amplitude, or event-related (de)synchronization and coherence for the current montage using brain sources or surface channels. Induced and evoked activities can be separated. Source coherence analysis reveals the functional connectivity between brain regions by reducing the volume conduction effects seen in surface coherence.
BESA Research transforms the surface signals into brain activity using source montages derived from multiple source models. This allows to display ongoing EEG/MEG, single epochs, and averages with much higher spatial resolution.

More than just dipole source localization
BESA研究涵蓋了信號處理和採集的原始數據，以動態源圖像分析的整個範圍：

• Data review and processing
• Source montages and 3D whole-head mapping
• ERP analysis and averaging
• Source localization and source imaging
• Cortical mapping and visualization in standard MRI
• Individual MRI and fMRI integration with BESA MRI and BrainVoyager
• Source coherence and time-frequency analysis
   

BESA MRI 數據分析軟體
快速的coregistering EEG / MRI 數據且建立 FEM 模型

BESA MRI是一種CE認證的軟體來生成個人頭模型（ FEM ），可用於腦電信號源分析。
允許個別MRI數據EEG / MEG數據配準。 BESA MRI它提供了一種簡單，直觀的界面和集成的工作流程，指導用戶一步一步操作
自動分割包括自動不均勻性校正，以校正掃描工件，產生一個高質量的皮質和頭皮重建，並在一個可選步驟中，也可以產生一個4層結構（頭皮，顱骨，腦脊液和腦）個體頭部模型（ FEM） 。
BESA MRI 2.0運行與BESA研究6.0和5.3的組合。個人頭模型（ FEM）與BESA MRI 2.0生成可以通過BESA研究6.0腦電信號源分析進口。 EEG / MEG數據可以共同註冊使用單獨的數字化電極位置或頭部形狀分個人MRI數據。由於BESA MRI的獨特功能， 10-10標準電極（包括劣質電極）也可以演變與個別MRI數據。

功能

• Integrated workflow
• Inhomogeneity correction
• Segmentation and individual head models (FEM)
• Coregistration
• Cortical sources on individual MRI

Co-registered electrode coordinates are immediately available in BESA Research. Thus, source images / localizations can be displayed on the individual MRI even if no individual digitization of electrodes has taken place.
MRI data import is easily performed with DICOM, ANALYZE/NIFTI, VMR readers. The preparation of the MRI data to be automatically processed by BESA MRI requires just a couple of simple worksteps typically demanding only a few minutes of the users attention. BESA MRI's automatic processing can be applied to all subjects prepared by the user in one go, therefore conveniently minimizing the time the user has to work on the computer.

BESA Statistics

BESA Statistics提供了用戶引導工作流程的EEG / MEG數據的跨學科分析。所使用的統計方法是statistical method used is parameter-free permutation testing on the basis of Student’s t-tests (Maris, E. and Oostenveld, R., 2007)。所有的分析都最小化，以限定的時間和/或感興趣的頻率範圍內自動地計算出來，計算在BESA統計的統計值可以被直接用於學術報告，無需進行進一步的分析在其他程序中，所有的結果都可視化。

功能

• Integrated workflow
• Preliminary Statistics
• Permutation Testing
• Optimal Visualization

BESA Statistics integrates optimally with data that were analyzed in BESA Research, but it can also process data from other software packages as long as they conform to the BESA Statistics file format.
BESA Statistics will automatically identify clusters in time, and if applicable frequency and space that show significant and stable differences between two groups or conditions. Results are corrected for multiple comparisons as only those data periods will be marked significant that survive the data re-shuffling of the permutation test. Thus, results obtained by BESA Statistics are objective and robust.
 

BESA Epilepsy

新的CE認證臨床軟件的癲癇腦電活動快速審查和集群
自動檢測和癇樣放電的快速聚類
採用了全新的hyperclustering技術
超過24小時的長期腦電數據進行快速評估
全面的概述和控制
輕鬆選擇和腦電圖的檢討

功能

• Detection Module
• Evaluation Module
• Fast and easy decision process
• Intuitive patient database

EEGFocus

所有功能於一身的軟體，用於快速審查和先進的腦電圖分析
結合了先進的分析功能，如3D全頭的映射，秒殺模式搜索和平均數據，頻譜分析， DSA趨勢分析，在線校正的眼睛和心電圖等文物數字化腦電圖檢討

數位腦電圖評論
EEGFocus提供了一個人性化的用戶界面為異常模式時審查，如即時分析尖峰或有節奏的腦電活動。類似的模式可以在整個腦電圖進行查找和平均值，例如，去分析一個spike或癲癇發作。

• Ergonomic buttons and key functions for fast manual or automatic paging. Overlapped paging to detect EEG abnormalities at page boundaries. Easy tool to measure peaks and frequencies
• Video synchronized paging, optionally with whole head mapping
• Fast navigation using the event bar or the DSA trend display with separation of the hemispheres (DSA = density spectral arrays)
• Advanced digital filters including zero-phase shift, band and notch filters

BESA Connectivity

BESA Connectivity 1.0 provides optimized, user-guided workflows for time-frequency and connectivity analysis of EEG/MEG data. Multiple well-established methods are provided. They were optimized for stream-lined performance that yields results for multiple combinations of input data types, time-frequency methods, and connectivity measures.
Particular highlights include:

• Three time-frequency methods and six connectivity methods supported, including Imaginary Part of Coherency, Granger Causality, PDC, DTF
• Direct comparison between conditions, time-frequency methods, connectivity methods with one or two mouse clicks
• Support for source montages as well as sensor-level data and polygraphic channels
• Superior visualization of results in 2D and 3D
• Highly versatile image and video export of results
• ASCII data result export and input support for Matlab
• Modern 64-bit architecture optimized for multi-core processing
• Workflow-based user guidance for optimized usability