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Design and implementation of a smart sensor for respiratory rate monitoring.

Luis JA, Roa Romero LM, Gómez-Galán JA, Hernández DN, Estudillo-Valderrama MÁ, Barbarov-Rostán G, Rubia-Marcos C - Sensors (Basel) (2014)

Bottom Line: This sensor is aimed at overcoming the drawbacks of other systems currently available in market, namely, devices that are costly, uncomfortable, difficult-to-install, provide low detection sensitivity, and little-to- patient-to-patient calibration.The device is based on capacitive sensing by means of an LC oscillator.Experimental results show that the sensor meets the necessary requirements, making feasible the proposed monitoring system with the technology used.

View Article: PubMed Central - PubMed

Affiliation: OnTech Security Enterprise, C/Lucena del Puerto, Huelva E-21002, Spain. juan.aponte@ontech.es.

ABSTRACT
This work presents the design, development and implementation of a smart sensor to monitor the respiratory rate. This sensor is aimed at overcoming the drawbacks of other systems currently available in market, namely, devices that are costly, uncomfortable, difficult-to-install, provide low detection sensitivity, and little-to- patient-to-patient calibration. The device is based on capacitive sensing by means of an LC oscillator. Experimental results show that the sensor meets the necessary requirements, making feasible the proposed monitoring system with the technology used.

No MeSH data available.


Resulting respiratory signal after second-stage processing of both volunteer patients. (a) Patient 1; (b) Patient 2.
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f8-sensors-14-03019: Resulting respiratory signal after second-stage processing of both volunteer patients. (a) Patient 1; (b) Patient 2.

Mentions: On a 2 m × 2 m inflatable mattress located 30 cm over the ground, two electrodes were placed according to the arrangements described above. In this first study, two males aged 35 and 29, 1.82 and 1.75 m tall, and weighing 99.5 and 80 kg, respectively, were asked to lie in different positions (face up, face down, on one side) on the electrodes, placed at the level of their chest. The value of the instantaneous oscillation frequencies of the sensor device were sent to a computer through the serial port at rate of 32 samples per second. These data were processed by Matlab software by means of a 3-stage algorithm. In the first stage, a fourth-order Butterworth low pass filtering was accomplished with a cutoff frequency of 0.32 Hz to smooth the signal and eliminate noise components (see Figure 8). In the second stage, a fourth-order Butterworth low pass filtering, but in this case at a much lower cutoff frequency (0.064 Hz), allowed extracting the DC component of the signal, since a drift in the DC level was experimentally detected.


Design and implementation of a smart sensor for respiratory rate monitoring.

Luis JA, Roa Romero LM, Gómez-Galán JA, Hernández DN, Estudillo-Valderrama MÁ, Barbarov-Rostán G, Rubia-Marcos C - Sensors (Basel) (2014)

Resulting respiratory signal after second-stage processing of both volunteer patients. (a) Patient 1; (b) Patient 2.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3958216&req=5

f8-sensors-14-03019: Resulting respiratory signal after second-stage processing of both volunteer patients. (a) Patient 1; (b) Patient 2.
Mentions: On a 2 m × 2 m inflatable mattress located 30 cm over the ground, two electrodes were placed according to the arrangements described above. In this first study, two males aged 35 and 29, 1.82 and 1.75 m tall, and weighing 99.5 and 80 kg, respectively, were asked to lie in different positions (face up, face down, on one side) on the electrodes, placed at the level of their chest. The value of the instantaneous oscillation frequencies of the sensor device were sent to a computer through the serial port at rate of 32 samples per second. These data were processed by Matlab software by means of a 3-stage algorithm. In the first stage, a fourth-order Butterworth low pass filtering was accomplished with a cutoff frequency of 0.32 Hz to smooth the signal and eliminate noise components (see Figure 8). In the second stage, a fourth-order Butterworth low pass filtering, but in this case at a much lower cutoff frequency (0.064 Hz), allowed extracting the DC component of the signal, since a drift in the DC level was experimentally detected.

Bottom Line: This sensor is aimed at overcoming the drawbacks of other systems currently available in market, namely, devices that are costly, uncomfortable, difficult-to-install, provide low detection sensitivity, and little-to- patient-to-patient calibration.The device is based on capacitive sensing by means of an LC oscillator.Experimental results show that the sensor meets the necessary requirements, making feasible the proposed monitoring system with the technology used.

View Article: PubMed Central - PubMed

Affiliation: OnTech Security Enterprise, C/Lucena del Puerto, Huelva E-21002, Spain. juan.aponte@ontech.es.

ABSTRACT
This work presents the design, development and implementation of a smart sensor to monitor the respiratory rate. This sensor is aimed at overcoming the drawbacks of other systems currently available in market, namely, devices that are costly, uncomfortable, difficult-to-install, provide low detection sensitivity, and little-to- patient-to-patient calibration. The device is based on capacitive sensing by means of an LC oscillator. Experimental results show that the sensor meets the necessary requirements, making feasible the proposed monitoring system with the technology used.

No MeSH data available.