This paper explores the idea of identifying activities from muscle activation which is captured by wearable ECG recording devices that use wet and textile electrodes. Most of the devices available today filter out the high frequency components to retain only the signal related to an ECG. We explain how the high frequency components that correspond to muscle activation can be extracted from the recorded signal and can be used to identify activities. We notice that is possible to obtain good performance for both the wet and dry electrodes. However, we observed that signals from the dry textile electrodes introduce less artifacts associated with muscle activation.