I analyze your single-channel brain signal data (EEG) using a published research method to detect hidden structural patterns that standard spectral analysis misses. You receive a full PDF report with clear findings.
I Will Detect Hidden Theta-Band Structural Patterns in Your EEG Data Using a Peer-Reviewed Method
Single EEG file analysis with anchor score, peak frequencies, and a basic PDF report.
- Analysis of 1 EEG file (single-channel or multi-channel)
- Anchor score (0-1) per channel
- Peak frequencies (f1, f2) in Hz
- Basic PDF report with figures
- Data privacy: source data deleted within 7 days
Single EEG file with temporal dynamics analysis and full interpretation report.
- Analysis of 1 EEG file
- Anchor score (0-1) per channel
- Peak frequencies (f1, f2) in Hz
- Temporal dynamics: how the pattern changes over the recording
- Theta-beta correlation analysis
- Full PDF report (5-10 pages) with figures and interpretation
- CSV results table
- 2 rounds of Q&A
- Data privacy: source data deleted within 7 days
Batch analysis of up to 5 EEG files with cross-file comparison and extended report.
- Analysis of up to 5 EEG files
- Anchor score (0-1) per channel per file
- Peak frequencies (f1, f2) in Hz per file
- Temporal dynamics per file
- Theta-beta correlation analysis per file
- Cross-file comparison table
- Extended PDF report with summary statistics
- CSV results table
- 3 rounds of Q&A
- Data privacy: source data deleted within 7 days
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Value Position
Analysis Method
EEG Compatibility
Deliverables
Data Privacy
What You'll Receive
Full Description
I Will Analyze Your Brain Signals for Hidden Structural Patterns Using a Published Method
What I do
I analyze your single-channel EEG data using a published, peer-reviewed method (DOI: 10.5281/zenodo.22850972). This method detects a specific structural pattern — two frequency peaks separated by a valley within the theta band — that standard tools like power spectral density, coefficient of variation, and sample entropy do NOT capture.
The method was first applied to a public meditation EEG dataset, where it identified a subject whose pattern was not present in any of the other 23 participants. I now offer the same analysis to individuals and research teams.
What you get
- Per-channel structural pattern analysis
- Anchor score (0–1): a single value indicating how strongly the pattern is present
- Peak frequencies (f1, f2) in Hz
- Temporal dynamics: how the pattern changes over your recording session
- A full PDF report with figures and plain-language interpretation
What this is NOT
- This is not a medical diagnosis
- This is not a measure of meditation depth or spiritual advancement
- This does not predict future events or mental states
It is a research-grade analysis for personal insight and self-exploration.
Who this is for
- Meditators using Muse, OpenBCI, Emotiv, or research-grade EEG who want to explore their own data
- Research teams analyzing meditation, sleep, or cognitive EEG datasets
- BCI developers and neurofeedback practitioners needing a new analytical dimension
What you need to provide
- Your EEG data file (CSV, BDF, or EDF format)
- Sampling rate in Hz
- Recording duration
- A short description of what you want to learn
Data privacy
Your data is used only for your analysis. After delivery, source data is permanently deleted within 7 days. Your data is never shared or used for any other purpose.
Delivery
- Single file analysis: within 3 business days
- Batch analysis (multiple files): contact for quote
Important note
This method is based on a preprint that has not yet undergone formal peer review at a journal. The identified pattern is an observation, not a diagnostic category. Results are for research and personal exploration purposes only.
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Compare Packages
| 特色 | Basic | Standard | Advanced |
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
| Revisions | 1 | 2 | 3 |
| Analysis of 1 EEG file (single-channel or multi-channel) | ✓ | ✓ | ✓ |
| Anchor score (0-1) per channel | ✓ | ✓ | ✓ |
| Peak frequencies (f1, f2) in Hz | ✓ | ✓ | ✓ |
| Basic PDF report with figures | ✓ | ✕ | ✕ |
| Data privacy: source data deleted within 7 days | ✓ | ✓ | ✓ |
| Temporal dynamics: how the pattern changes over the recording | ✕ | ✓ | ✓ |
| Theta-beta correlation analysis | ✕ | ✓ | ✓ |
| Full PDF report (5-10 pages) with figures and interpretation | ✕ | ✓ | ✕ |
| CSV results table | ✕ | ✓ | ✓ |
| 2 rounds of Q&A | ✕ | ✓ | ✕ |
| Analysis of up to 5 EEG files | ✕ | ✕ | ✓ |
| Cross-file comparison table | ✕ | ✕ | ✓ |
| Extended PDF report with summary statistics | ✕ | ✕ | ✓ |
| 3 rounds of Q&A | ✕ | ✕ | ✓ |
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Meditation EEG Anomaly Detection Study
A single-subject case study from a 24-subject meditation EEG dataset (OpenNeuro ds001787). The analysis identified a unique subject (sub-017) with three features not observed in any other participant: - Highest mean anchor score (0.184) - Strongest theta-beta anticorrelation (r = -0.64) - High temporal variability (std = 0.110) The method and implementation are retained as a commercial asset. This portfolio item demonstrates my ability to detect hidden patterns in complex EEG data. Published
Extra Information
My workflow
Service Details
Frequently Asked Questions
No. This is a research-grade analysis for personal insight and self-exploration. It is not a medical diagnosis and cannot be used for clinical decision-making, insurance, or regulatory submission.
Yes. Your data is used only for your analysis. After delivery, your source data is permanently deleted within 7 days. Your data is never shared, published, or used for any other purpose.
No. The algorithm and its implementation are retained as a commercial asset. You receive the analysis results (PDF report, CSV data, figures), not the source code.
English or Chinese. Please specify your preference when ordering. If not specified, I will deliver in English.
If you are not satisfied with the delivered report, please contact me within 7 days. I will revise the report based on your feedback at no extra cost. If the issue is about data interpretation, I will explain my reasoning and provide additional context.
Refunds are considered on a case-by-case basis. Since this is custom data analysis, refunds are not guaranteed once the report is delivered.
Yes. The analysis requires at least 60 seconds of continuous data per channel. For reliable temporal dynamics (how the pattern changes over time), I recommend at least 5 minutes.
Files shorter than 60 seconds per channel cannot be analyzed. Files between 1 and 5 minutes will be analyzed but temporal dynamics may be limited.
For multi-channel files, I analyze all channels by default and report per-channel anchor scores. You will see which channels show the pattern and which do not.
If you want to focus on specific channels (e.g., Cz, Fz, Pz), specify them when ordering.
For consumer EEG devices with few channels (Muse, Emotiv), results may differ from research-grade 64-channel data. Message me before ordering if you are unsure about your setup.
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