New research: MJM application in clinical practice
13 May 2023
Dr. Martinot and Dr. Pépin have recently published a peer-reviewed article in Frontiers titled "Mandibular jaw movements as a non-invasive measure of respiratory effort during sleep: application in clinical practice."
The article highlights the importance of accurately assessing respiratory effort during sleep and the challenges associated with current methods. The authors propose the use of mandibular jaw movements (MJM) as a reliable and non-invasive measure of respiratory effort, which can provide valuable information for the diagnosis of sleep-disordered breathing.
The articles emphasizes the close relationship between changes in the MJM bio-signal as a function of respiratory effort, which is similar to levels of respiratory effort measured by reference bio-signals such as esophageal pressure or crural diaphragmatic electromyography. The automatic analysis of MJM using a dedicated machine learning algorithm delivers a comprehensive and clinically informative study report, making it an attractive option for physicians.
This publication highlights the potential of MJM monitoring in clinical practice and could pave the way for future advancements in the diagnosis and treatment of sleep-disordered breathing.
Read more: https://www.frontiersin.org/ar...
#SleepDisorders #RespiratoryEffort #ClinicalPractice #MJM #MachineLearning
The article highlights the importance of accurately assessing respiratory effort during sleep and the challenges associated with current methods. The authors propose the use of mandibular jaw movements (MJM) as a reliable and non-invasive measure of respiratory effort, which can provide valuable information for the diagnosis of sleep-disordered breathing.
The articles emphasizes the close relationship between changes in the MJM bio-signal as a function of respiratory effort, which is similar to levels of respiratory effort measured by reference bio-signals such as esophageal pressure or crural diaphragmatic electromyography. The automatic analysis of MJM using a dedicated machine learning algorithm delivers a comprehensive and clinically informative study report, making it an attractive option for physicians.
This publication highlights the potential of MJM monitoring in clinical practice and could pave the way for future advancements in the diagnosis and treatment of sleep-disordered breathing.
Read more: https://www.frontiersin.org/ar...
#SleepDisorders #RespiratoryEffort #ClinicalPractice #MJM #MachineLearning