5.2. “Power by sections” Mode5.2. “Power by sections” Mode5.2. “Power by sections” Mode5.2. “Power by sections” Mode
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CleverPoint 4 User Manual

16
  • Introduction
    • Customer Support
    • Regulatory Compliance
    • Warranty and Copyright
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    • Technical specifications
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Stressonika - Guide for Working with raw ECG data

20
  • Introduction
  • Chapter 1. General points.
    • General points
  • Chapter 2. Cardio domain
    • Cardio domain
    • Sector. 1
    • Sector. 2
    • Sector. 3
    • Sector 4
    • Sector 5
    • Sector 6
    • Sector 7
    • Sector 8
  • Chapter 3. Cardio domain: examples
    • Cardio domain: examples
    • 3.1. ECG recording quality
    • 3.2. Preparing the “Cardio domain” page for consultation
    • 3.3 Viewing the “Cardio domain” page during consultation (Example 1)
    • 3.4 . Viewing the “Cardio domain” page during consultation (Example 2)
    • 3.5. Viewing the “Cardio domain” page during consultation (Example 3)
    • 3.6 . Viewing the “Cardio domain” page during consultation (Example 4)
    • 3.7. Viewing the “Cardio domain” page during consultation (Example 5)
    • 3.8. The “Cardio domain” page. Conclusion.

CleverPoint View Data v2.15 User Guide

55
  • Introduction
    • Introduction
  • 0. Fundamentals of Electrophysiology for Beginners
    • 0.1. What Are Physiological Signals?
    • 0.2. Autonomic Nervous System (ANS)
    • 0.3. Emotions and the Brain
    • 0.4. Electrodes and Their Placement in the CleverPoint Setup
  • 1. General Principles of Signal Processing
    • 1.1. Basic Transformations
    • 1.2. Marking and Trim
    • 1.3. CAR (Common Average Reference)
    • 1.4. Denoise (Blink Artifact Suppression)
    • 1.5. Normalize
    • 1.6. IMF (Empirical Mode Decomposition)
    • 1.7. Filtering
    • 1.8. Power vs Amplitude
    • 1.9. Epoch
  • 2. “Summary” Interface
    • 2.1. Purpose
    • 2.2. Controls
    • 2.3. Graphs
    • 2.4. Data Export
  • 3. “Time Domain” Interface
    • 3.1. Purpose
    • 3.2. Controls
    • 3.3. Signal Display
    • 3.4. Signal Transformations
  • 4. “Frequency Domain” Interface
    • 4.1. Purpose
    • 4.2. Interface Structure
    • 4.3. Controls
    • 4.4. Spectral Analysis Methods
    • 4.5. Channel Correlation
    • 4.6. Time Series
  • 5. “Power Domain” Interface
    • 5.1. Purpose
    • 5.2. “Power by sections” Mode
    • 5.3. “Between-channel interactions” Mode
    • 5.4. Frequency-Band Graphs
  • 6. “Coherence” Interface
    • 6.1. Purpose
    • 6.2. Controls
    • 6.3. Coherence Calculation Method
    • 6.4. Display
    • 6.5. Interpretation
    • 6.6. Use in Research
  • 7. “Emotional State” Interface
    • 7.1. Purpose
    • 7.2. Interface Structure
    • 7.3. Controls
    • 7.4. Emotion Calculation Method
    • 7.5. Display
    • 7.6. Section Selection
  • 8. “Cardio Domain” Interface
    • 8.1. Purpose
    • 8.2. Interface Structure
    • 8.3. Controls
    • 8.4. Extraction of RR Intervals
    • 8.5. HRV Parameters
    • 8.6. Visualization
    • 8.7. Data Export
  • 9. Conclusion
    • Conclusion
    • 9.1. Recommendations for Use
    • 9.2. Additional Resources
    • 9.3. Beginner’s Guide
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  • 5. “Power Domain” Interface
  • 5.2. “Power by sections” Mode

5.2. “Power by sections” Mode

2 min read

5.2.1. Controls #

  1. Trim: Remove artifact segments
  2. CAR: Common average reference
  3. Denoise: Blink artifact suppression
  4. Filter: Frequency filter selection
  5. Function: Aggregation function (sum, mean, median, std)
  6. Relative: Relative values (percentage of the total spectrum)
  7. Epoch length: Epoch length for averaging
  8. Recalculation button
  9. Mode selection: Power by sections / Between-channel interactions

5.2.2. Results Table #

    The table contains: #

    1. Section/filter: Section name or filter name
    2. F8, AF4, AF3, F7, L Zygoma: Power for each electrode
    3. Epoch length: Epoch length
    4. Power: Checkbox for including or excluding the section

    5.2.3. Power Calculation Method #

    • Transformations are applied: Trim, CAR, Denoise (blink artifacts)
    • The frequency filter is applied (if selected)
    • The signal is converted to power:
      power = signal.^2
    • Epoch averaging is applied:
      power_smoothed = filtfilt(moving_average, 1, power)
    • An aggregate statistic is calculated for each section:
      sum: sum(power_section) / Fs (power integral)
      mean: mean(power_section) (mean power)
      median: median(power_section) (median power)
      std: std(power_section) (standard deviation)

    5.2.4. Relative Values #

    When Relative is enabled:

    • Total power (without filtering) is calculated for each channel.
    • Power in the selected band is expressed as a percentage:
      relative_power = 100 * filtered_power / total_power

    Interpretation: Percentage of power in the selected frequency band relative to the total signal power.

    Physiological explanation of relative power:

    Absolute power depends on many factors (contact quality, individual characteristics). Relative power shows what share of total brain activity belongs to a given frequency band.

    • Relative power is more stable and makes it easier to compare people.
    • It shows the “balance” between different rhythms.

    Examples:

    • Alpha 50%: half of the brain’s activity is alpha rhythm (strong relaxation)
    • Beta 30%: one third of the activity is beta rhythm (active thinking)
    • Theta 10%: one tenth of the activity is theta rhythm (light sleep or meditation)

    Interpretation of changes:

    • Increased relative alpha: transition toward relaxation
    • Increased relative beta: transition toward active work
    • A change in balance reflects a change in functional state
    Updated on 21.03.2026

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    5.1. Purpose5.3. “Between-channel interactions” Mode
    Table of Contents
    • 5.2.1. Controls
    • 5.2.2. Results Table
    • The table contains:
    • 5.2.3. Power Calculation Method
    • 5.2.4. Relative Values

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    We strive to empower our users with the tools to effectively manage stress, prevent burnout, and optimize their well-being.

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