194
N. Blanik
If only an extraction of vital parameters from a short sequence is intended, it is
advisable to record longer sequences than the minimum length, though and analyze in
detail the sections containing the smallest artifacts in particular. A quick method for
assessment of occurring artifacts is described in the next subsection. The underlying
principle is to conduct continuous monitoring by employing movement tracking
and compensation methods. Multiple algorithms are available for a wide range of
applications, and these, together with a selection of different principles, are discussed
in detail in the following pages.
11.5.1 Initial Assessment of Occurring Movement Events
The first step in the analysis of PPGI sequences is to determine whether movement
artifacts occur, and if so, where and when they do so. This lays the foundation for
the identification of spatial and temporal sections within the recordings best suited
for further analysis.
To fulfill this purpose the actual disturbance produced by the artifacts itself can
be used. Different positions assigned on the measured object, with varied levels of
brightness to the same analyzing pixel over a specific period of time, would produce
strong fluctuations in pixel intensity. Keeping this in mind, a rapid approach, therefore, is designed based on a threshold method, which analyses changes in consecutive
images I t−1 and I t pixel by pixel:
I D (x, y) =
l
t=1 |I t (x, y) − I t−1 (x, y)|
t l − t 0
(11.6)
In the above equation, t 0 and t l represent the initial and final time of measurement
respectively for the considered time interval. Entries of I D exceeding a prescribed
threshold indicate positions of occurring motion artifact. Subsequently, an assessment of the temporal boundaries of motion artefacts can be made by performing a
summation along the spatial axes instead of the temporal:
i D (t) =
x,y |I t (x, y) − I t−1 (x, y)|
m · n
(11.7)
In the above expression, m and n correspond to the spatial resolution of the image
frame.
The level of the threshold is defined by the kind of application. Among others, it
is dependent on the filling ratio of the image foreground to background, the scene
illumination, background noise for example of the camera chip, the dynamic range
of the camera, and the character of contained vital signs as well as artefacts.
Figure 11.16 presents an example of the applied threshold method. In this presentation, the reference image of a neonate resting inside an incubator is shown on the
left. All local intensity changes (arising mainly from motion artefacts) are displayed
N. Blanik
If only an extraction of vital parameters from a short sequence is intended, it is
advisable to record longer sequences than the minimum length, though and analyze in
detail the sections containing the smallest artifacts in particular. A quick method for
assessment of occurring artifacts is described in the next subsection. The underlying
principle is to conduct continuous monitoring by employing movement tracking
and compensation methods. Multiple algorithms are available for a wide range of
applications, and these, together with a selection of different principles, are discussed
in detail in the following pages.
11.5.1 Initial Assessment of Occurring Movement Events
The first step in the analysis of PPGI sequences is to determine whether movement
artifacts occur, and if so, where and when they do so. This lays the foundation for
the identification of spatial and temporal sections within the recordings best suited
for further analysis.
To fulfill this purpose the actual disturbance produced by the artifacts itself can
be used. Different positions assigned on the measured object, with varied levels of
brightness to the same analyzing pixel over a specific period of time, would produce
strong fluctuations in pixel intensity. Keeping this in mind, a rapid approach, therefore, is designed based on a threshold method, which analyses changes in consecutive
images I t−1 and I t pixel by pixel:
I D (x, y) =
l
t=1 |I t (x, y) − I t−1 (x, y)|
t l − t 0
(11.6)
In the above equation, t 0 and t l represent the initial and final time of measurement
respectively for the considered time interval. Entries of I D exceeding a prescribed
threshold indicate positions of occurring motion artifact. Subsequently, an assessment of the temporal boundaries of motion artefacts can be made by performing a
summation along the spatial axes instead of the temporal:
i D (t) =
x,y |I t (x, y) − I t−1 (x, y)|
m · n
(11.7)
In the above expression, m and n correspond to the spatial resolution of the image
frame.
The level of the threshold is defined by the kind of application. Among others, it
is dependent on the filling ratio of the image foreground to background, the scene
illumination, background noise for example of the camera chip, the dynamic range
of the camera, and the character of contained vital signs as well as artefacts.
Figure 11.16 presents an example of the applied threshold method. In this presentation, the reference image of a neonate resting inside an incubator is shown on the
left. All local intensity changes (arising mainly from motion artefacts) are displayed