Learning Higher-Order Dynamics in Video-Based Cardiac Measurement

10/07/2021
by   Brian L. Hill, et al.
0

Computer vision methods typically optimize for first-order dynamics (e.g., optical flow). However, in many cases the properties of interest are subtle variations in higher-order changes, such as acceleration. This is true in the cardiac pulse, where the second derivative can be used as an indicator of blood pressure and arterial disease. Recent developments in camera-based vital sign measurement have shown that cardiac measurements can be recovered with impressive accuracy from videos; however, the majority of research has focused on extracting summary statistics such as heart rate. Less emphasis has been put on the accuracy of waveform morphology that is necessary for many clinically impactful scenarios. In this work, we provide evidence that higher-order dynamics are better estimated by neural models when explicitly optimized for in the loss function. Furthermore, adding second-derivative inputs also improves performance when estimating second-order dynamics. By incorporating the second derivative of both the input frames and the target vital sign signals into the training procedure, our model is better able to estimate left ventricle ejection time (LVET) intervals.

READ FULL TEXT

Authors

page 14

page 15

12/02/2021

A higher order Minkowski loss for improved prediction ability of acoustic model in ASR

Conventional automatic speech recognition (ASR) system uses second-order...
07/20/2021

Adjoint based methods to compute higher order topological derivatives with an application to elasticity

The goal of this paper is to give a comprehensive and short review on ho...
02/17/2021

Cardiac Motion Modeling with Parallel Transport and Shape Splines

In cases of pressure or volume overload, probing cardiac function may be...
06/13/2022

ReViSe: Remote Vital Signs Measurement Using Smartphone Camera

Remote Photoplethysmography (rPPG) is a fast, effective, inexpensive and...
06/08/2018

Noise-adding Methods of Saliency Map as Series of Higher Order Partial Derivative

SmoothGrad and VarGrad are techniques that enhance the empirical quality...
04/15/2018

From CDF to PDF --- A Density Estimation Method for High Dimensional Data

CDF2PDF is a method of PDF estimation by approximating CDF. The original...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.