Gaurav Kapur1, Lingguang Chen2, Yong Xu3, Katherine Cashen1, Jeff Clark1, Xiaoce Feng3, Sean F Wu2. 1. Department of Pediatrics, Children's Hospital of Michigan/Wayne State University, Detroit, MI. 2. Department of Mechanical Engineering, Wayne State University, Detroit, MI. 3. Department of Electric and Computer Science Engineering, Wayne State University, Detroit, MI.
Abstract
OBJECTIVES: To develop a novel device to predict systolic and diastolic blood pressure based on measured heart sound signals and evaluate its accuracy in comparison to intra-arterial blood pressure readings. STUDY DESIGN: Prospective, observational pilot study. SETTING: PICU. PATIENTS: Critically ill children (0-18 yr) undergoing continuous blood pressure monitoring via radial artery intra-arterial catheters were enrolled in the study after informed consent. The study included medical, cardiac, and surgical PICU patients. INTERVENTIONS: Along with intra-arterial blood pressure, patient's heart sounds were recorded simultaneously by a highly sensitive sensor taped to the chest. Additional hardware included a data acquisition unit and laptop computer. Subsequently, advanced signal processing technologies were used to minimize random interfering signals and extract and separate S1 and S2 signals. A computerized model was then developed using artificial neural network systems to estimate blood pressure from the extracted heart sound analysis. MEASUREMENTS AND MAIN OUTCOMES: We found a statistically significant correlation for systolic (r = 0.964; R = 0.928) and diastolic (r = 0.935; R = 0.868) blood pressure readings (n = 491) estimated by the novel heart-sound signal-based method and those recorded by intra-arterial catheters. The mean difference of the individually paired determinations of the blood pressure between the heart-sound-based method and intra-arterial catheters was 0.6 ± 7 mm Hg for systolic blood pressure and -0.06 ± 5 mm Hg for diastolic blood pressure, which was within the recommended range of 5 ± 8 mm Hg for any new blood pressure devices. CONCLUSIONS: Our findings provide proof of concept that the heart-sound signal-based method can provide accurate, noninvasive blood pressure monitoring.
OBJECTIVES: To develop a novel device to predict systolic and diastolic blood pressure based on measured heart sound signals and evaluate its accuracy in comparison to intra-arterial blood pressure readings. STUDY DESIGN: Prospective, observational pilot study. SETTING: PICU. PATIENTS: Critically ill children (0-18 yr) undergoing continuous blood pressure monitoring via radial artery intra-arterial catheters were enrolled in the study after informed consent. The study included medical, cardiac, and surgical PICU patients. INTERVENTIONS: Along with intra-arterial blood pressure, patient's heart sounds were recorded simultaneously by a highly sensitive sensor taped to the chest. Additional hardware included a data acquisition unit and laptop computer. Subsequently, advanced signal processing technologies were used to minimize random interfering signals and extract and separate S1 and S2 signals. A computerized model was then developed using artificial neural network systems to estimate blood pressure from the extracted heart sound analysis. MEASUREMENTS AND MAIN OUTCOMES: We found a statistically significant correlation for systolic (r = 0.964; R = 0.928) and diastolic (r = 0.935; R = 0.868) blood pressure readings (n = 491) estimated by the novel heart-sound signal-based method and those recorded by intra-arterial catheters. The mean difference of the individually paired determinations of the blood pressure between the heart-sound-based method and intra-arterial catheters was 0.6 ± 7 mm Hg for systolic blood pressure and -0.06 ± 5 mm Hg for diastolic blood pressure, which was within the recommended range of 5 ± 8 mm Hg for any new blood pressure devices. CONCLUSIONS: Our findings provide proof of concept that the heart-sound signal-based method can provide accurate, noninvasive blood pressure monitoring.