How can I solve this problem in the CSP feature extraction algorithm for EEG signal?

Dataset description:

Code:

% Calculate the covariance matrices for each class

cov_matrices = cell(1, 2);

disp(unique(labels));

disp(size(epochs));

for i = 1:2

if any(labels == i)

class_epochs = epochs(:, :, labels == i);

cov_matrices{i} = cov(class_epochs');

else

disp(['No data for class ', num2str(i)]);

end

end

Error:

Answer 1

[Namnendra]

Hi Komal,

The error message you're encountering indicates that the logical indexing operation `labels == i` is trying to access indices that are out of bounds for the `epochs` array. This typically happens if `labels` contains values that do not correspond to valid indices within the third dimension of `epochs`.

Here's a step-by-step approach to troubleshoot and resolve the issue:

Steps to Resolve the Issue

1. Verify Dimensions:

- Ensure that the `epochs` array and `labels` vector have compatible dimensions. The third dimension of `epochs` should match the length of `labels`. Example code:-

disp(size(epochs));  % Check the dimensions of epochs
disp(length(labels)); % Check the length of labels

2. Check Unique Labels:

- Confirm that the `labels` variable contains only the expected values (e.g., 1 and 2 for two classes). Example code:-

  unique_labels = unique(labels);
  disp(unique_labels);  % Should display [1, 2] if those are the only classes

3. Debugging the Indexing:

- Ensure that `labels` only contains values that are valid indices for the third dimension of `epochs`. Example code:-

 for i = 1:length(labels)
       if labels(i) < 1 || labels(i) > size(epochs, 3)
           disp(['Invalid label at index ', num2str(i), ': ', num2str(labels(i))]);
       end
 end

4. Correct the Indexing Logic:

- Ensure the logic used to extract `class_epochs` is correct. If `labels` are not strictly 1 and 2, adjust the logic accordingly. Example code:-

for i = 1:2
       if ismember(i, unique_labels)  % Check if the class exists in labels
           class_epochs = epochs(:, :, labels == i);
           cov_matrices{i} = cov(reshape(class_epochs, [], size(class_epochs, 3))');
       else
           disp(['No data for class ', num2str(i)]);
       end
end

5. Handle Empty Classes:

- If a class does not have any data (i.e., `labels == i` results in an empty array), handle this case to avoid attempting to calculate a covariance matrix on empty data.

Additional Tips

- Data Validation: Before processing, validate your data to ensure that all indices and labels are as expected.

- Error Handling: Implement checks and error messages to gracefully handle unexpected data conditions.

- Debugging: Use debugging tools or additional `disp` statements to track variable values and program flow.

By following these steps, you should be able to identify and fix the issue with the logical indexing in your CSP feature extraction algorithm. If the problem persists, consider examining the data loading and preprocessing steps to ensure that `epochs` and `labels` are correctly set up.

Thank you.