Breathing is one of the vital signs. Breathing is also the indicator to indicate
the physical health. Breathing rate or Respiration Rate (RR) is used in diagnosing
healt conditions and able to decide the suitable treatment. This study presents
a real time contactless breathing monitoring system in android mobile phone. The
system is robust and completed with tele medic through Wi-Fi communication. The
system is capable to write the data in a string form, save the images and the videoes
of the recording automatically, and conduct live streaming video.
The proposed system is the modification of Wang et al’s. motion detection
model can detect breathing activity smoothly and periodicly. Wang et al’s.’s system
used the video as an input. The proposed system uses the frame of the camera as
the input and capable to analyse in real-time.
For the evaluation, This study uses a doc, a cat, and two pigs. A doc and cat
were under certain medical condition which are deep, middle, and shallow condition.
The pigs were in stage 1, stage 1-2, stage 6, and stage 6-7. The result were compared
to ETCO2 result which is obtained from ECG machine (Dash 5000 Monitor). The
highest accuration of result is more than 95% after removing body movement, and
the lowest is more than 93%.

Breathing is one of the vital signs. Breathing is also the indicator to indicate
the physical health. Breathing rate or Respiration Rate (RR) is used in diagnosing
healt conditions and able to decide the suitable treatment. This study presents
a real time contactless breathing monitoring system in android mobile phone. The
system is robust and completed with tele medic through Wi-Fi communication. The
system is capable to write the data in a string form, save the images and the videoes
of the recording automatically, and conduct live streaming video.
The proposed system is the modification of Wang et al’s. motion detection
model can detect breathing activity smoothly and periodicly. Wang et al’s.’s system
used the video as an input. The proposed system uses the frame of the camera as
the input and capable to analyse in real-time.
For the evaluation, This study uses a doc, a cat, and two pigs. A doc and cat
were under certain medical condition which are deep, middle, and shallow condition.
The pigs were in stage 1, stage 1-2, stage 6, and stage 6-7. The result were compared
to ETCO2 result which is obtained from ECG machine (Dash 5000 Monitor). The
highest accuration of result is more than 95% after removing body movement, and
the lowest is more than 93%.

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