Parameters for LSTM with CNN in a sequential data

I am doing a classification problem with ECG data. I built a LSTM model but the accuracy of the model is not quiet good. Hence, I am thinking to implement it with CNN. I am planning to pass the data from CNN, then passing the output from CNN to LSTM. Howver, I have noticed that CNN is mostly used in Image classifications. I have sequential data with 4000 time steps. Could you please help me to define the parameters of the CNN model.

Conv2d(in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True, padding_mode='zeros', device=None, dtype=None)

Can someone explain me what would be the in_channels, out_channels, kernel_size and stride for a sequence data having 4000 time steps?