Title:
|
Evaluating respiratory muscle activity using a wireless sensor platform
|
Author:
|
Estrada, Luis; Torres Cebrián, Abel; Sarlabous Uranga, Leonardo; Jané Campos, Raimon
|
Other authors:
|
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. BIOSPIN - Biomedical Signal Processing and Interpretation |
Abstract:
|
Wireless sensors are an emerging technology that allows to assist physicians in the monitoring of patients
health status. This approach can be used for the non-invasive recording of the electrical respiratory muscle activity of
the diaphragm (EMGdi). In this work, we acquired the EMGdi signal of a healthy subject performing an inspiratory load
test. To this end, the EMGdi activity was captured from a single channel of electromyography using a wireless platform
which was compared with the EMGdi and the inspiratory mouth pressure (Pmouth) recorded with a conventional
lab equipment. From the EMGdi signal we were able to evaluate the neural respiratory drive, a biomarker used for
assessing the respiratory muscle function. In addition, we evaluated the breathing movement and the cardiac activity,
estimating two cardio-respiratory parameters: the respiratory rate and the heart rate. The correlation between the two
EMGdi signals and the Pmouth improved with increasing the respiratory load (Pearson's correlation coefficient ranges
from 0.33 to 0.85). The neural respiratory drive estimated from both EMGdi signals showed a positive trend with an
increase of the inspiratory load and being higher in the conventional EMGdi recording. The respiratory rate comparison
between measurements revealed similar values of around 16 breaths per minute. The heart rate comparison showed a
root mean error of less than 0.2 beats per minute which increased when incrementing the inspiratory load. In summary,
this preliminary work explores the use of wireless devices to record the muscle respiratory activity to derive several
physiological parameters. Its use can be an alternative to conventional measuring systems with the advantage of being
portable, lightweight, flexible and operating at low energy. This technology can be attractive for medical staff and may
have a positive impact in the way healthcare is being delivered. |
Abstract:
|
Peer Reviewed |
Subject(s):
|
-Àrees temàtiques de la UPC::Enginyeria biomèdica -Biomedical engineering -body sensor networks -cardiovascular system -electromyography -health care -medical signal detection -medical signal processing -pneumodynamics -statistical analysis – telemedicine -wireless sensor platform -patient health status monitoring -noninvasive electrical respiratory muscle activity recording -diaphragm -EMGdi signal acquisition -electromyography -inspiratory mouth pressure recording -breathing movement evaluation -cardio-respiratory parameter estimation -Pearson correlation coefficient -neural respiratory -physiological parameters -healthcare -Enginyeria biomèdica |
Rights:
|
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Document type:
|
Article - Submitted version Conference Object |
Published by:
|
Institute of Electrical and Electronics Engineers (IEEE)
|
Share:
|
|