Respiration pattern recognition by wearable mask device.
Mask
Principle component analysis
Respiration pattern
Respiratory rate
Steady state
Wearable device
Journal
Biosensors & bioelectronics
ISSN: 1873-4235
Titre abrégé: Biosens Bioelectron
Pays: England
ID NLM: 9001289
Informations de publication
Date de publication:
01 Dec 2020
01 Dec 2020
Historique:
received:
15
06
2020
revised:
22
08
2020
accepted:
01
09
2020
pubmed:
15
9
2020
medline:
15
5
2021
entrez:
14
9
2020
Statut:
ppublish
Résumé
Compared to heart rate, body temperature and blood pressure, respiratory rate is the vital sign that has been often overlooked, largely due to the lack of easily accessible tool for reliable and natural respiration monitoring. To address this unmet need, we designed and built a wearable, stand-alone, fully integrated mask device for accurate tracking of respiration in free-living conditions. The wearable mask device can provide comprehensive respiration information in a wearable and wireless manner. It can not only accurately measure respiratory rate, tidal volume, respiratory minute volume, and peak flow rate but also recognize unique respiration pattern of the subject via Principle Component Analysis (PCA) algorithms. The reported wearable mask device and respiratory pattern recognition algorithms could be widely used in routine clinical examination, lung function assessment, asthma and chronic obstructive pulmonary disease (COPD) management, metabolic rate measurement, capnography, spirometry, sleep pattern analysis, and biometrics.
Identifiants
pubmed: 32927349
pii: S0956-5663(20)30580-7
doi: 10.1016/j.bios.2020.112590
pmc: PMC7572779
mid: NIHMS1628764
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
112590Subventions
Organisme : NIBIB NIH HHS
ID : R03 EB027336
Pays : United States
Organisme : NHLBI NIH HHS
ID : R44 HL123164
Pays : United States
Informations de copyright
Copyright © 2020 Elsevier B.V. All rights reserved.
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