Proof-of-concept for a non-invasive, portable, and wireless device for cardiovascular monitoring in pediatric patients

Abstract

Measurement of cardiac function is vital for the health of pediatric patients with heart disease. Standard tools to measure function including echocardiogram and magnetic residence imaging are time intensive, costly, and have limited accessibility. The Vivio is a novel, non-invasive, handheld device that screens for cardiac dysfunction by analyzing intrinsic frequencies (IF) ω 1 and ω 2 of carotid artery waveforms. Prior studies demonstrated that left ventricular ejection fraction can be derived from IFs in adults. This study 1) studies whether the Vivio can capture carotid arterial pulse waveform data in children ages 0-19 years old; 2) tests the performance of two sensor head geometries, one larger and smaller than the standard size used in adults, designed for the pediatric population; 3) compares the IFs between pediatric age groups and adults with normal function. The Vivio successfully measured a carotid artery waveform in all children over 5 years old and 28% of children under the age of five. The small head did not accurately measure a waveform in any age group. One-way analysis of variance (ANOVA) demonstrated a difference in the IF ω 1 between the adult and pediatric cohorts (F = 7.3, Prob>F = 0.0001). Post host analysis demonstrated a difference between the adult cohort (ω 1 = 99 +/-5 bpm) and the cohorts ages 0-4 (ω 1 = 111 +/-2 bpm; p = 0.0006) and 15-19 years old (ω 1 = 105 +/-5 bpm; p = 0.02). One-way ANOVA demonstrated a difference in the IF ω 2 between the adult and pediatric cohorts (F = 4.8, Prob>F = 0.003), specifically between the adult (ω 2 = 81 +/-13 bpm) and age 0-4 cohorts (ω 2 = 48 +/-8 bpm; p = 0.002). These results suggest that the Vivio can be used to capture carotid pulse waveform data in pediatric populations and that the data produced can be used to measure intrinsic frequencies.

Intrinsic frequency method for instantaneous assessment of left ventricular-arterial coupling after transcatheter aortic valve replacement

“…In this study, we applied invasively measured aortic pressure waveforms to extract IF indices and quantify LV-arterial coupling through ∆ω. However, arterial pressure waveforms can be easily recorded non-invasively by applanation tonometry from the carotid artery (O'Rourke et al 2001, Nelson et al 2010), a smartphone (Pahlevan et al 2017) or smartphone-based handheld devices (Armenian et al 2018, Miller et al 2020. Thus, IF method has the potential to facilitate post-procedure follow-up in assessing cardiac and systemic circulation performance post TAVR procedure.…”

Accuracy and applicability of non-invasive evaluation of aortic wave intensity using only pressure waveforms in humans

“…Numerous wave analysis techniques have been proposed to study the patterns found in these waves in order to uncover clinically valuable information, such as pulse wave analysis (Davies et al 2006) as well as separation into backwards and forwards components (Manisty et al 2010). Many of these methods have demonstrated efficacy in predicting or capturing relevant clinical metrics through analysis of both pressure and flow measurements (Mynard et al 2020), although pressure wave-only analysis methods (such as reservoirexcess pressure Parker 2020, Armstrong et al 2021), wave condition number (Pahlevan and Mazandarani 2020) and intrinsic frequency (Pahlevan et al 2014, Cooper et al 2021) have recently enjoyed increased traction due to the immense interest in obtaining blood pressure measurements cheaply, easily and non-invasively (Pahlevan et al 2017, Miller et al 2020.…”

Screening left ventricular systolic dysfunction in children using intrinsic frequencies of carotid pressure waveforms measured by a novel smartphone-based device

“…We previously reported that there was a significant difference in w 1 among different age groups (Miller et al 2020); particularly, w 1 of the age group from 0 to 4 years old showed significant difference from the that of the adult cohort (Miller et al 2020). Therefore, we divided the study population into three age groups: 0-6 years old, 7-13 years old, and 14-20 years old.…”