Experiment and configuration files for PsychoPy incorporating the Lab Streaming Layer (LSL) for data collection.
- Setup the Recording Environment by following this guide
- Read through the data collection protocol for this experiment
- Updated Setup
config.yamlfile contains the various configurations for accommodating different modalities in the experiment and handling the timings for various routines in the experiment.- It currently supports three configurations:
eeg,fnirs,test - Each of the configurations has the following attributes:
sound_files: ["babycry", "chewing" ... ] # List of sound file names to include from the sounds folder
baseline_duration: 15 # Duration of the baseline routine (in seconds)
stimuli_repeat: 5 # Number of times each sound stimulus will repeat
stimulus_dration: 4 # Duration of the stimulus routine (in seconds)
response_duration: 5 # Duration of the response routine following the stimulus (in seconds)
rest_range: [6, 8] # Duration range of the rest routine following the response (in seconds)- Check the
config.yamlfile for the actual values for each configuration
- Experiment files:
hearing.pyexp: Experiment file for the fNIRS/EEG modality experimentspupil.pyexp: Experiment file for pupil dilation and fNIRS/EEG modality experiments
- Before running the PsychoPy experiment, it expects a few inputs:
participant: A unique ID (number) for the participant. By default, it generates a random number which can be changed.run: Run number for the same participant for the same experiment if multiple recordings are needed (usually 1)config: The name of the experimental configuration value defined above.
Raspberry Pi Related Setup
- Make sure FFMPEG is installed on both Raspberry Pi and the recording computer
- Install GStreamer to stream video from Raspberry Pi to the recording computer
- For Windows, make sure to select complete installation (not typical) when installing
Useful Commands
- Streaming from Pi (update with hostname or ip-address of the computer):
python stream.py- Capturing from the computer (Replace <port_num> with actual port number):
gst-launch-1.0 -v udpsrc port=<port_num> caps="application/x-rtp, media=(string)video, clock-rate=(int)90000, encoding-name=(string)H264" ! rtpjitterbuffer ! rtph264depay ! avdec_h264 ! videoconvert ! fpsdisplaysink video-sink=autovideosink- Converting .h264 to .mp4:
ffmpeg -i <input_file>.h264 -c copy <output_file>.mp4- Converting .mjpeg to .mp4:
ffmpeg -i <input_file>.mjpeg -pix_fmt yuv420p -c:v libx264 -crf 20 -an <output_file>.mp4- Splitting a video file by times:
ffmpeg -i <input_file>.h264 -ss <start_time> -to <end_time> -c:v libx264 -preset fast -crf 18
-crfflag ensures the quality (0-51, 0 - lossless, 23 - default, 51 - worst)
- Create a virtual environment with
--system-site-packagesflag - Activate the virtual environment
- Install pylsl
- Install picamera2
- Follow the installation instructions under the
Installation using pipsection
- Follow the installation instructions under the
- Copy and run the
server-camera.pyscript on the Raspberry Pi - After the experiment, the video will be saved to the
recordingsfolder with the current date and time. Access this folder using a file manager and move the file to theinputfolder for further analysis.
- Run the
pi-recorder.pyscript on the raspberry pi
- Move the raw video (.mp4) from Raspberry Pi to the
inputfolder - Move the experiment data file (ends with
.xdf) to theexp_datafolder - The processing script will load and segment the data based on the markers. It will then save the segmented video files and create an output folder