Optimizing wearable laser speckle imaging for detection of postpartum hemorrhage in high- and low-resource settings

Postpartum hemorrhage (PPH) is the leading cause of maternal mortality globally, with the majority of PPH deaths occurring in low- and middle-income countries. Importantly, PPH has been noted as the most preventable cause of maternal mortality, and the leading factors causing preventable PPH are delays in diagnosis and treatment. This is especially critical in rural and low resource settings that often have low blood stores for transfusion, relying primarily on early pharmacologic treatment. There is an urgent need for a technology that can monitor occult blood loss, which would otherwise go undetected, in real-time to detect PPH in early stages. To this end, our lab has developed a compact, low-cost, wrist-worn wearable device that continuously monitors perfusion via laser speckle flow index (LSFI) to detect early signs of blood loss. The system was designed as a wireless, battery-powered reflectance mode configuration using off-the-shelf components. The device is Bluetooth enabled and can process and transmit LSFI signal to a receiving device for near real-time data visualization. Preliminary data in a swine hemorrhage model demonstrated that the system was sensitive to blood loss volumes of less than 5% with a highly linear response to blood loss volume (correlation coefficient of -0.94). To quantify blood loss, we moved to mining LSFI cardiac waveform features and preliminary data in swine show blood loss volume prediction errors of less than 100 mL over a 1000 mL blood loss range. These promising results motivate further development of hardware, which is being both simplified and expanded to also include a wired version of the device that hosts greater computational power and longer patient monitoring duration. Additionally, generalization of our data processing and analysis pipeline increases the robustness of our feature extraction algorithms and expansion into additional cardiovascular parameters. Finally, device adaptations informed by patient and healthcare provider interviews from a Nigerian hospital setting will be discussed.