Description
Electromyography (EMG) signal from human trunk is often contaminated with electrocardiographic (ECG) noise (ECG artefacts), which originates from the activity of the heart muscle. ECG artefacts must be properly removed from the EMG signal, before it is further processed. Many methods for ECG artefacts removal from the EMG signal were proposed in the past. However, all these methods have limitations and/or must be used manually. Our aim was to develop a new method for ECG artefacts removal from the EMG signal that can be used automatically without a user interaction. We used EMG signals from the human trunk while performing quick arm rise test and postural reactions on sudden loading test. We proposed a new method for ECG artefacts removal from the EMG signal based on the dynamic time warping approach. Dynamic time warping is used to find ECG artefact patterns in the EMG signal with the use of predefined ECG artefact templates. ECG artefact patterns are further processed to eliminate potentially false ECG artefacts and to find missing ECG artefacts. The proposed method was evaluated for detection of the presence of the ECG artefacts in the EMG signal and for successfulness of the ECG artefacts removal from the EMG signal. Proposed method proved to be reliable for detection of the presence of ECG artefacts in the EMG signal and was successful in the ECG artefacts removal from the EMG signal.
Primary author
Mr
Andrej Panjan
(S2P, Science to Practice, Ltd., Laboratory for Motor Control and Motor Behaviour)
