TY - GEN
T1 - Design of respiratory rate measurement based on ultrasound proximity sensor
AU - Danurwindo, Ismoyo
AU - Basari,
PY - 2019/11
Y1 - 2019/11
N2 - The respiratory rate is one of the five vital signs in human body. The measurement that is most often done is by counting the amount of breath a person does in one minute. This method is considered to be subjective in which each outcome measurement will depend on the counter. Other methods that can be used are by using contact methods, such as strain gauges or impedance methods, transcutaneous CO2methods, probe oximetry (SpO2) methods, and ECG derived respiration rate methods. However, the use of contact methods can cause several problems, such as skin irritation, and surface loading effect. Therefore, in this paper a respiratory rate measurement based on ultrasound proximity sensor is proposed. Measurements are made by calculating the distance change between the front of thoracoabdominal area and the sensor. The results are then processed by peak detection using the Gaussian filter and discrete wavelet transform (DWT). According to the data processing results, the measurement gets the smallest deviation for each error about 3.79 with discrete wavelet transform (DWT) and fast fourier transform (FFT) calculation approach.
AB - The respiratory rate is one of the five vital signs in human body. The measurement that is most often done is by counting the amount of breath a person does in one minute. This method is considered to be subjective in which each outcome measurement will depend on the counter. Other methods that can be used are by using contact methods, such as strain gauges or impedance methods, transcutaneous CO2methods, probe oximetry (SpO2) methods, and ECG derived respiration rate methods. However, the use of contact methods can cause several problems, such as skin irritation, and surface loading effect. Therefore, in this paper a respiratory rate measurement based on ultrasound proximity sensor is proposed. Measurements are made by calculating the distance change between the front of thoracoabdominal area and the sensor. The results are then processed by peak detection using the Gaussian filter and discrete wavelet transform (DWT). According to the data processing results, the measurement gets the smallest deviation for each error about 3.79 with discrete wavelet transform (DWT) and fast fourier transform (FFT) calculation approach.
KW - Arduino
KW - Fast fourier transform
KW - Peak detection
KW - Respiratory rate measurement
KW - Ultrasound proximity sensor
UR - http://www.scopus.com/inward/record.url?scp=85083031244&partnerID=8YFLogxK
U2 - 10.1109/R10-HTC47129.2019.9042463
DO - 10.1109/R10-HTC47129.2019.9042463
M3 - Conference contribution
T3 - IEEE Region 10 Humanitarian Technology Conference, R10-HTC
BT - Proceedings of 2019 IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2019
Y2 - 12 November 2019 through 14 November 2019
ER -