Development and evaluation of a wearable peripheral vascular compensation sensor in a swine model of hemorrhage

Abstract

Postpartum hemorrhage (PPH) is the leading and most preventable cause of maternal mortality, particularly in low-resource settings. PPH is currently diagnosed through visual estimation of blood loss or monitoring of vital signs. Visual assessment routinely underestimates blood loss beyond the point of pharmaceutical intervention. Quantitative monitoring of hemorrhage-induced compensatory processes, such as the constriction of peripheral vessels, may provide an early alert for PPH. To this end, we developed a low-cost, wearable optical device that continuously monitors peripheral perfusion via laser speckle flow index (LSFI) to detect hemorrhage-induced peripheral vasoconstriction. The measured LSFI signal produced a linear response in phantom models and a strong correlation coefficient with blood loss averaged across subjects (>0.9) in a large animal model, with superior performance to vital sign metrics.

Fig. 1.

Data acquisition and visualization via Bluetooth communication used in swine studies. Left) User inputs to control laser and video capture are sent to the Raspberry Pi. Images are recorded and processed on the device and sent back to the computer where they are automatically plotted. Right) Experimental setup for swine hemorrhage model, with blood draw port and arterial blood pressure port. Device was worn on the swine’s “wrist”.

Fig. 2.

Laser characterization. Overlayed spectra of the benchmark (a) and low-cost laser (b) every hour for six hours. Optical power output of the benchmark laser (c), an initially increasing low-cost laser (d), and an initially decreasing low-cost laser (e). Low-cost laser spectra (f) and optical power output (g) over temperatures ranging from 8.8-38.4°C. Range of LSFI values produced by benchmark laser (h) and low-cost laser (i) while measuring static and moving media at 5 ms exposure time.

Fig. 3.

Comparison of linear response to fluid velocity between low-cost and benchtop lasers. Mean LSFI measured while recording various physiological blood velocities with 0.5 ms exposure time.

Fig. 4.

Wearable LSFI response during swine hemorrhage and resuscitation. Peak-normalized mean LSFI signal captured before hemorrhage (black), during hemorrhage (red), and during crystalloid resuscitation (blue) studies compared to net fluid change (green) for each of six swine.

Fig. 5.

Response of LSFI sensor and vital signs during swine hemorrhage. Correlation between LSFI (a), shock index (SI) (b), mean arterial pressure (MAP) (c), and heart rate (HR) (d) vs net fluid change since the start of blood removal for each swine during blood loss only. (e) Summary of correlation coefficients and slopes for each case. “Average” takes the correlation coefficient from each individual swine and averages the values. “Across all swine” groups all the swine datapoints together and calculates a single correlation from the pooled data.

Fig. 6.

Response of LSFI sensor and vital signs during swine resuscitation. Correlation between LSFI (a), shock index (SI)(b), mean arterial pressure (MAP) (c), and heart rate (HR) (d) vs. net fluid change in each swine since the start of crystalloid infusion. (e) Summary of correlation coefficients and slopes from linear fitting for each case. “Average” takes the correlation coefficient from each individual swine and averages the values. “Across all swine” groups all the swine datapoints together and calculates a single correlation from the pooled data.