Contactless respiration rate measurement using optical method and empirical mode decomposition

• Published in: Technology and health care Vol. 24; no. 5; pp. 761 - 768
• Main Authors: Gan, K.B., Yahyavi, E.S., Ismail, M.S.
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 14.09.2016
• Subjects: Adult; Algorithms; Female; Fourier Analysis; Humans; Lasers; Male; Middle Aged; Respiratory Function Tests - instrumentation; Respiratory Rate - physiology; Thorax - physiology; displacement; empirical mode decomposition; respiration rate; Contactless; triage
• ISSN: 0928-7329; 1878-7401; 1878-7401
• DOI: 10.3233/THC-161161

BACKGROUND: At the emergency triage center, assessment of the present of the danger signs and measurement of vital signs are measured according to the guidelines. The respiration rate is still posing a challenge to the doctor as it is impractical to use conventional devices. Attaching measurement devices to the patient will induce artificial measurements (self-awareness stress effects) besides being time-consuming. Currently, the medical officers visually count the number of times the chest movement in a minute, sometimes poses cultural challenges especially for female patients. OBJECTIVE: The main objective of this paper is to develop a robust algorithm to extract respiration rate using the contactless displacement sensor. METHODS: In this study, chest movements were used as an indicative of inspiration and expiration to measure respiratory rate using the contactless displacement sensor. The contactless optical signals were recorded from 32 healthy subjects in four different controlled breathing conditions: rest, coughing, talking and hand movement to obtain the motion artifacts that the patients may have in the emergency department. The Empirical mode decomposition (EMD) algorithm was used to derive continuous RR signal from the contactless optical signal. RESULTS: The analysis showed that there is a good correlation(0.9702) with RMSE of 0.33 breaths per minutes between the contact respiration rate and contactless respiration rate using empirical mode decomposition method. CONCLUSION: It can be concluded that the empirical mode decomposition method can extract the respiration rate of the contactless optical signal from chest movement.