Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/716991
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dc.contributor.authorTamer Elfaramawy|Cheikh Latyr Fall|Soodeh Arab|Martin Morissette|François Lellouche|Benoit Gosselinen_US
dc.date.accessioned2013en_US
dc.date.accessioned2021-05-16T17:43:32Z-
dc.date.available2021-05-16T17:43:32Z-
dc.date.issueden_US
dc.identifier.isbn1530-437Xen_US
dc.identifier.other10.1109/JSEN.2018.2877617en_US
dc.identifier.urihttp://localhost/handle/Hannan/716991-
dc.description.abstractWireless body sensors are increasingly used by clinicians and researchers in a wide range of applications, such as sports, space engineering, and medicine. Monitoring vital signs in real time can dramatically increase diagnosis accuracy and enable automatic curing procedures, e.g., detect and stop epilepsy or narcolepsy seizures. Breathing parameters are critical in oxygen therapy, hospital, and ambulatory monitoring, while the assessment of cough severity is essential when dealing with several diseases, such as chronic obstructive pulmonary disease. In this paper, a low-power wireless respiratory monitoring system with cough detection is proposed to measure the breathing rate and the frequency of coughing. This system uses wearable wireless multimodal patch sensors, designed using off-the-shelf components. These wearable sensors use a low-power nine-axis inertial measurement unit to quantify the respiratory movement and a MEMs microphone to record audio signals. Data processing and fusion algorithms are used to calculate the respiratory frequency and the coughing events. The architecture of each wireless patch-sensor is presented. In fact, the results show that the small 26.67 × 65.53 mm <sup xmlns:mml= http://www.w3.org/1998/Math/MathML xmlns:xlink= http://www.w3.org/1999/xlink >2</sup> patch-sensor consumes around 12-16.2 mA and can last at least 6 h with a miniature 100-mA lithium ion battery. The data processing algorithms, the acquisition, and wireless communication units are described. The proposed network performance is presented for experimental tests with a freely behaving user in parallel with the gold standard respiratory inductance plethysmography.en_US
dc.relation.haspart08502791.pdfen_US
dc.subjectlow-power|Breathing rate|data fusion|inertial measurement unit|wireless|real-time|wearable|coughing detection|patch sensors networken_US
dc.titleA Wireless Respiratory Monitoring System Using a Wearable Patch Sensor Networken_US
dc.title.alternativeIEEE Sensors Journalen_US
dc.typeArticleen_US
dc.journal.volumeVolumeen_US
dc.journal.issueIssueen_US
dc.journal.titleIEEE Sensors Journalen_US
Appears in Collections:New Ieee 2019

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dc.contributor.authorTamer Elfaramawy|Cheikh Latyr Fall|Soodeh Arab|Martin Morissette|François Lellouche|Benoit Gosselinen_US
dc.date.accessioned2013en_US
dc.date.accessioned2021-05-16T17:43:32Z-
dc.date.available2021-05-16T17:43:32Z-
dc.date.issueden_US
dc.identifier.isbn1530-437Xen_US
dc.identifier.other10.1109/JSEN.2018.2877617en_US
dc.identifier.urihttp://localhost/handle/Hannan/716991-
dc.description.abstractWireless body sensors are increasingly used by clinicians and researchers in a wide range of applications, such as sports, space engineering, and medicine. Monitoring vital signs in real time can dramatically increase diagnosis accuracy and enable automatic curing procedures, e.g., detect and stop epilepsy or narcolepsy seizures. Breathing parameters are critical in oxygen therapy, hospital, and ambulatory monitoring, while the assessment of cough severity is essential when dealing with several diseases, such as chronic obstructive pulmonary disease. In this paper, a low-power wireless respiratory monitoring system with cough detection is proposed to measure the breathing rate and the frequency of coughing. This system uses wearable wireless multimodal patch sensors, designed using off-the-shelf components. These wearable sensors use a low-power nine-axis inertial measurement unit to quantify the respiratory movement and a MEMs microphone to record audio signals. Data processing and fusion algorithms are used to calculate the respiratory frequency and the coughing events. The architecture of each wireless patch-sensor is presented. In fact, the results show that the small 26.67 × 65.53 mm <sup xmlns:mml= http://www.w3.org/1998/Math/MathML xmlns:xlink= http://www.w3.org/1999/xlink >2</sup> patch-sensor consumes around 12-16.2 mA and can last at least 6 h with a miniature 100-mA lithium ion battery. The data processing algorithms, the acquisition, and wireless communication units are described. The proposed network performance is presented for experimental tests with a freely behaving user in parallel with the gold standard respiratory inductance plethysmography.en_US
dc.relation.haspart08502791.pdfen_US
dc.subjectlow-power|Breathing rate|data fusion|inertial measurement unit|wireless|real-time|wearable|coughing detection|patch sensors networken_US
dc.titleA Wireless Respiratory Monitoring System Using a Wearable Patch Sensor Networken_US
dc.title.alternativeIEEE Sensors Journalen_US
dc.typeArticleen_US
dc.journal.volumeVolumeen_US
dc.journal.issueIssueen_US
dc.journal.titleIEEE Sensors Journalen_US
Appears in Collections:New Ieee 2019

Files in This Item:
File Description SizeFormat 
08502791.pdf3.79 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorTamer Elfaramawy|Cheikh Latyr Fall|Soodeh Arab|Martin Morissette|François Lellouche|Benoit Gosselinen_US
dc.date.accessioned2013en_US
dc.date.accessioned2021-05-16T17:43:32Z-
dc.date.available2021-05-16T17:43:32Z-
dc.date.issueden_US
dc.identifier.isbn1530-437Xen_US
dc.identifier.other10.1109/JSEN.2018.2877617en_US
dc.identifier.urihttp://localhost/handle/Hannan/716991-
dc.description.abstractWireless body sensors are increasingly used by clinicians and researchers in a wide range of applications, such as sports, space engineering, and medicine. Monitoring vital signs in real time can dramatically increase diagnosis accuracy and enable automatic curing procedures, e.g., detect and stop epilepsy or narcolepsy seizures. Breathing parameters are critical in oxygen therapy, hospital, and ambulatory monitoring, while the assessment of cough severity is essential when dealing with several diseases, such as chronic obstructive pulmonary disease. In this paper, a low-power wireless respiratory monitoring system with cough detection is proposed to measure the breathing rate and the frequency of coughing. This system uses wearable wireless multimodal patch sensors, designed using off-the-shelf components. These wearable sensors use a low-power nine-axis inertial measurement unit to quantify the respiratory movement and a MEMs microphone to record audio signals. Data processing and fusion algorithms are used to calculate the respiratory frequency and the coughing events. The architecture of each wireless patch-sensor is presented. In fact, the results show that the small 26.67 × 65.53 mm <sup xmlns:mml= http://www.w3.org/1998/Math/MathML xmlns:xlink= http://www.w3.org/1999/xlink >2</sup> patch-sensor consumes around 12-16.2 mA and can last at least 6 h with a miniature 100-mA lithium ion battery. The data processing algorithms, the acquisition, and wireless communication units are described. The proposed network performance is presented for experimental tests with a freely behaving user in parallel with the gold standard respiratory inductance plethysmography.en_US
dc.relation.haspart08502791.pdfen_US
dc.subjectlow-power|Breathing rate|data fusion|inertial measurement unit|wireless|real-time|wearable|coughing detection|patch sensors networken_US
dc.titleA Wireless Respiratory Monitoring System Using a Wearable Patch Sensor Networken_US
dc.title.alternativeIEEE Sensors Journalen_US
dc.typeArticleen_US
dc.journal.volumeVolumeen_US
dc.journal.issueIssueen_US
dc.journal.titleIEEE Sensors Journalen_US
Appears in Collections:New Ieee 2019

Files in This Item:
File Description SizeFormat 
08502791.pdf3.79 MBAdobe PDFThumbnail
Preview File