Abstract: Obstructive sleep apnea in patients, between 70 and 80
percent, can be cured with just a posture correcting. The most import
thing to do this is detection of obstructive sleep apnea. Detection of
obstructive sleep apnea can be performed through heart rate variability
analysis using power spectrum density analysis. After HRV analysis
we needed to know the current position information for correcting the
position. The pressure sensors of the array type were used to obtain
position information. These sensors can obtain information from the
experimenter about position. In addition, air cylinder corrected the
position of the experimenter by lifting the bed. The experimenter can
be changed position without breaking during sleep by the system.
Polysomnograph recording were obtained from 10 patients. The
results of HRV analysis were that NLF and LF/HF ratio increased,
while NHF decreased during OSA. Position change had to be done the
periods.
Abstract: In this paper, we were introduces a skin detection
method using a histogram approximation based on the mean shift
algorithm. The proposed method applies the mean shift procedure to a
histogram of a skin map of the input image, generated by comparison
with standard skin colors in the CbCr color space, and divides the
background from the skin region by selecting the maximum value
according to brightness level. The proposed method detects the skin
region using the mean shift procedure to determine a maximum value
that becomes the dividing point, rather than using a manually selected
threshold value, as in existing techniques. Even when skin color is
contaminated by illumination, the procedure can accurately segment
the skin region and the background region. The proposed method may
be useful in detecting facial regions as a pretreatment for face
recognition in various types of illumination.