Stockwell Transform Detector For Photoplethysmography Signal Segmentation

Real-time embedded analysis of physiologic waveforms is critical to predict impending pathophysiology. While electrocardiogram (ECG) data is often analyzed to assess cardiovascular disease, there is recent evidence that photo-plethysmography (PPG) can track blood loss and thereby alert to hypovolemia. In this work we present a Stockwell transform inspired filler hank to segment PPG waveforms. The Stockwell transform allows for computationally efficient frequency analysis. The proposed Stockwell filter bank utilizes a sparse time-frequency spectrum and is coupled to the Shannon energy envelope to extract PPG peaks. Finally, we demonstrate that the described method is tolerant to the presence of additive Gaussian noise.