Respiratory quality indices for automated monitoring of respiration from sensor data
<p>Abnormal respiratory rate (RR) is known to be one of the most clinically effective predictors of catastrophic decline. Despite this, RR is often the least monitored and most inaccurately measured vital sign. This is primarily because of the lack of a non-invasive, robust, automated method f...
Autor Principal: | Birrenkott, D |
---|---|
Outros autores: | Clifton, D |
Formato: | Thesis |
Idioma: | English |
Publicado: |
2018
|
Subjects: |
Títulos similares
-
Biomedical Signal Analysis for Connected Healthcare /
por: Krishnan, Sri, author 651681, et al.
Publicado: (2021) -
Sleep Stage Estimation from Bed Leg Ballistocardiogram Sensors
por: Yasue Mitsukura, et al.
Publicado: (2020-10-01) -
Biomedical and Health Informatics /
por: Ferrari, Erica, author 648245, et al.
Publicado: (2012) -
Mobile Health : A Technology Road Map /
por: Adibi, Sasan. editor
Publicado: (2015) -
Machine learning for the detection of clinical deterioration on hospital wards
por: Shamout, F
Publicado: (2019)