  The monitoring of vital signs such as heart rate (HR) and respiratory rate
(RR) during sleep is important for the assessment of sleep quality and
detection of sleep disorders. Camera-based HR and RR monitoring gained
popularity in sleep monitoring in recent years. However, they are all facing
with serious privacy issues when using a video camera in the sleeping scenario.
In this paper, we propose to use the defocused camera to measure vital signs
from optically blurred images, which can fundamentally eliminate the privacy
invasion as face is difficult to be identified in obtained blurry images. A
spatial-redundant framework involving living-skin detection is used to extract
HR and RR from the defocused camera in NIR, and a motion metric is designed to
exclude outliers caused by body motions. In the benchmark, the overall Mean
Absolute Error (MAE) for HR measurement is 4.4 bpm, for RR measurement is 5.9
bpm. Both have quality drops as compared to the measurement using a focused
camera, but the degradation in HR is much less, i.e. HR measurement has strong
correlation with the reference ($R \geq 0.90$). Preliminary experiments suggest
that it is feasible to use a defocused camera for cardio-respiratory monitoring
while protecting the privacy. Further improvement is needed for robust RR
measurement, such as by PPG-modulation based RR extraction.
