# Key Vital Signs Monitor Based on MIMO Radar

## TL;DR

A new MIMO radar system monitors vital signs and sleep poses accurately without physical contact.

## Contribution

A novel MIMO radar system with a two-step approach for sleep pose estimation and vital sign monitoring.

## Key findings

- The system achieved less than 5 cm MAE for xiphoid and navel location tracking.
- Pose classification and limb movement detection reached over 90% and 98.6% accuracy.
- Breathing rate MAE was between 0.06 and 0.8 cycles per minute.

## Abstract

State-of-the-art radar systems for the contactless monitoring of vital signs and respiratory diseases are typically based on single-channel continuous wave (CW) technology. This technique allows precise measurements of respiration patterns, periods of movement, and heart rate. Major practical problems arise as CW systems suffer from signal cancellation due to destructive interference, limited overall functionality, and a possibility of low signal quality over longer periods. This work introduces a sophisticated multiple-input multiple-output (MIMO) solution that captures a radar image to estimate the sleep pose and position of a person (first step) and determine key vital parameters (second step). The first step is enabled by processing radar data with a forked convolutional neural network, which is trained with reference data captured by a time-of-flight depth camera. Key vital parameters that can be measured in the second step are respiration rate, asynchronous respiratory movement of chest and abdomen and limb movements. The developed algorithms were tested through experiments. The achieved mean absolute error (MAE) for the locations of the xiphoid and navel was less than 5 cm and the categorical accuracy of pose classification and limb movement detection was better than 90% and 98.6%, respectively. The MAE of the breathing rate was measured between 0.06 and 0.8 cycles per minute.