RT Journal Article
A1 Flavia Benetazzo
AD Dipartimento di Ingegneria dell'Informazione, Università Politecnica delle Marche, Ancona, Italy
A1 Alessandro Freddi
AD Dipartimento di Ingegneria dell'Informazione, Università Politecnica delle Marche, Ancona, Italy
A1 Andrea Monteriù
AD Dipartimento di Ingegneria dell'Informazione, Università Politecnica delle Marche, Ancona, Italy
A1 Sauro Longhi
AD Dipartimento di Ingegneria dell'Informazione, Università Politecnica delle Marche, Ancona, Italy

PB iet
T1 Respiratory rate detection algorithm based on RGB-D camera: theoretical background and experimental results
JN Healthcare Technology Letters
VO 1
IS 3
SP 81
OP 86
AB Both the theoretical background and the experimental results of an algorithm developed to perform human respiratory rate measurements without any physical contact are presented. Based on depth image sensing techniques, the respiratory rate is derived by measuring morphological changes of the chest wall. The algorithm identifies the human chest, computes its distance from the camera and compares this value with the instantaneous distance, discerning if it is due to the respiratory act or due to a limited movement of the person being monitored. To experimentally validate the proposed algorithm, the respiratory rate measurements coming from a spirometer were taken as a benchmark and compared with those estimated by the algorithm. Five tests were performed, with five different persons sat in front of the camera. The first test aimed to choose the suitable sampling frequency. The second test was conducted to compare the performances of the proposed system with respect to the gold standard in ideal conditions of light, orientation and clothing. The third, fourth and fifth tests evaluated the algorithm performances under different operating conditions. The experimental results showed that the system can correctly measure the respiratory rate, and it is a viable alternative to monitor the respiratory activity of a person without using invasive sensors.
K1 spirometer
K1 person respiratory activity monitoring
K1 light conditions
K1 human chest wall
K1 morphological changes
K1 chest movements
K1 human respiratory rate measurements
K1 respiratory rate detection algorithm
K1 benchmark
K1 sampling frequency
K1 image sensing techniques
K1 red green blue-depth camera
K1 person being monitoring
DO https://doi.org/10.1049/htl.2014.0063
UL https://digital-library.theiet.org/;jsessionid=2nfs7cptc8uj3.x-iet-live-01content/journals/10.1049/htl.2014.0063
LA English
SN
YR 2014
OL EN