Stimulus based algorithm for extracting electrocardiogram signal from the head for eyewear devices

There are many existing wearable devices which are just meant to measure the heart rate using the Electrocardiogram (ECG), and worn on the wrist or on the chest. However, the future trend of wearable devices is moving towards head mounted wearable devices. Hence, an algorithm has to be developed to filter and extract head ECG signals from other physiological signals from the head such as electroencephalogram (EEG), EOG (electro-oculogram) and EMG (electromyogram). In this study, ECG signals from the head will be extracted by using a stimulus based algorithm utilizing ensemble averaging technique. The chest ECG signals (lead I, lead II and lead III) and Photoplethysmogram (PPG) signals (from earlobe and fingertip) will be used as an event stimulus in extracting the head ECG signals. The results obtained by running the algorithm are analyzed by using Mean Absolute Error (MAE). The expected outcome is the minimum number of heart beats needed to recover the morphology of the head ECG waveform using chest ECG signals (lead I, lead II and lead III) is lesser than the minimum number of heart beats needed to recover the morphology of the head ECG waveform using PPG signals from earlobe and fingertip.