JA-128

ShimmerLSL/python/README.md

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+# Introduction
+
+The following shows how to use Lab Streaming Layer support on Consensys, in this example Lab Recorder is used to record the LSL stream, and a python script (_which is included here_) is used to convert the recorded xdf file into csv format.
+
+# Consensys
+
+First enable Lab Streaming Layer
+![enable_LSL](https://github.com/user-attachments/assets/6c4c4a9f-7854-43f3-9845-e9783f129ded)
+Next connect to the Shimmer device and start streaming as shown below
+![2024-10-18_10h43_30](https://github.com/user-attachments/assets/c0c9de67-b885-4d84-bd60-4ed572288717)
+
+# Lab Recorder
+
+Select the Shimmer device you want to record and click Start, this will start recording the Shimmer device data to an xdf file.
+_Should you not see the Shimmer device which is streaming in Consensys you can try clicking update_
+![2024-10-18_10h43_56](https://github.com/user-attachments/assets/3c4f39e8-79d1-46bf-8703-98fd64f5e0e4)
+
+# Python Script
+
+Remember to update the file name and path below
+![image](https://github.com/user-attachments/assets/efa92b1f-0957-4fd8-b7c3-837a06d24b39)

ShimmerLSL/python/converttocsv.py

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+import pyxdf
+import pandas as pd
+
+# Step 1: Load the XDF file
+xdf_file_path = 'C:\\Users\\XX\\Documents\\CurrentStudy\\sub-P001\\ses-S001\\eeg\\sub-P001_ses-S001_task-Default_run-001_eeg.xdf'
+streams, header = pyxdf.load_xdf(xdf_file_path)
+
+
+# Iterate through the streams and save each as a CSV
+for idx, stream in enumerate(streams):
+    # Extract data and timestamps
+    data = stream['time_series']
+    timestamps = stream['time_stamps']
+
+    # Attempt to retrieve channel names, fallback to generic names if not available
+    try:
+        channels = [ch['label'][0] for ch in stream['info']['desc'][0]['channels'][0]['channel']]
+    except (KeyError, TypeError, IndexError):
+        channels = [f'channel_{i}' for i in range(data.shape[1])]
+
+    # Retrieve the stream name
+    try:
+        stream_name = stream['info']['name'][0]
+    except (KeyError, TypeError, IndexError):
+        stream_name = f'stream_{idx+1}'
+
+    # Create a DataFrame
+    print(channels)
+    print(data)
+    df = pd.DataFrame(data, columns=channels)
+    df['time_stamps'] = timestamps
+
+    # Save DataFrame to CSV using the stream name
+    csv_file_path = f'{stream_name}.csv'
+    df.to_csv(csv_file_path, index=False)
+    print(f"Stream {idx+1} saved to {csv_file_path}")