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Published on: July 19, 2013
Feasibility of a Respiratory Movement Evaluation Tool to Quantify Thoracoabdominal Movement for Neuromuscular
Fumio Liu1, Michiyuki Kawakami1, Kimimasa Tamura2
1Department of Rehabilitation Medicine, Keio University School of Medicine, Tokyo, Japan.
Background:
An objective method to evaluate thoracoabdominal movement is needed in daily clinical practice to detect patients at risk of hypoventilation and to allow for timely interventions in neuromuscular diseases. The clinical feasibility, reliability, and validity of a newly developed method for quantifying respiratory movement using fiber grating sensors, called the Respiratory Movement Evaluation Tool (RMET), was evaluated.
Methods:
The time needed to measure respiratory movement and the usability of the measurement were determined by 5 clinicians using the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST) 2.0 questionnaire. Thoracoabdominal movement was measured using RMET 3 times in 10 healthy subjects to evaluate intraclass correlation coefficients (ICC). The subjects were encouraged to breathe 10 times while voluntarily changing the amount of air during ventilation simultaneously with the RMET and a spirometer, and their correlations were evaluated to test validity using Pearson's product-moment correlation coefficients. The same measurements were also performed in 10 subjects with Duchenne muscular dystrophy.
Results:
Real-time recordings of thoracoabdominal movements were obtained over a mean time of 374 ± 23.9 s. With QUEST 2.0, the median score of each item exceeded 3 (more or less satisfied). In healthy subjects, ICC(1,1) ranged from 0.82 to 0.99, and ICC(2,1) ranged from 0.83 to 0.97. Significant correlations were observed between the respiratory amplitudes measured with RMET, and the amount of air during ventilation was measured with a spirometer (r = 0.995, P < .001). In subjects with Duchenne muscular dystrophy, ICC(1,1) ranged from 0.87 to 0.97, and ICC(2,1) ranged from 0.84 to 0.99. The respiratory amplitudes measured with RMET correlated significantly with the amount of air during ventilation with a spirometer (r = 0.957, P < .001).
Conclusions:
We developed a novel method of quantifying respiratory movement called RMET that was feasible to use in daily clinical practice.
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