Update README.md

README.md

@@ -75,6 +75,7 @@ This BCI Intent Data Study (conceptual early design) is for training machine lea
 large scale real hardware BCI datasets, addressing data scarcity and privacy issues around BCI intent studies.
 
 ## Key Features
+
 - **Frame-by-Frame Timelapse**: Synchronized image sequences at 320x240 resolution
 - **Multiple Capture Modes**: Manual (LMB), Auto-interval, and Sequence recording
 - **BCI Intent Labels**: 13 intent categories including timelapse capture events
@@ -83,6 +84,7 @@ large scale real hardware BCI datasets, addressing data scarcity and privacy iss
 - **Sequence Analysis**: Grouped frames into temporal sequences for time-series analysis
 
 ## Dataset Structure
+
 - `timelapse_frames.jsonl`: Frame metadata (one per line)
 - `frames/`: JPG images for each frame
 - `sequences.json`: Temporal grouping of frames
@@ -91,11 +93,13 @@ large scale real hardware BCI datasets, addressing data scarcity and privacy iss
 - `README.md`: This documentation
 
 ## Capture Modes
+
 1. **MANUAL**: LMB click captures single frame (hold for burst)
 2. **AUTO**: Automatic capture at 500ms intervals
 3. **SEQUENCE**: Start/stop recording for continuous frame sequences
 
 ## Dataset Statistics
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 - **Total Frames**: 188
 - **Sequences**: 1
 - **Session Duration**: 01:35
@@ -104,6 +108,7 @@ large scale real hardware BCI datasets, addressing data scarcity and privacy iss
 - **Total Kills**: 30
 
 ## Frame Data Structure
+
 Each frame includes:
 - Image data (320x240 JPG)
 - Timestamp and game time
@@ -113,6 +118,7 @@ Each frame includes:
 - RLHF rating (if applicable)
 
 ## Usage for BCI Research
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 ```python
 import json
 import cv2
@@ -156,6 +162,7 @@ for seq_id, sequence in sequences.items():
 ```
 
 ## Citation
+
 ```
 @dataset{datastrike_bci,
   title={DATASTRIKE BCI Timelapse Dataset},