BackgroundRespiratory rehabilitation reduces breathlessness from patient with respiratory dysfunction. Chest expansion score, which represents the circumference magnitude of the thoracic cage, is used for a target when treating patients with respiratory disease. However, it is often difficult for patients to understand the changes in the respiratory status and be motivated for therapy continuously. We developed a new measurement system with biofeedback named BREATH which shows chest expansion scores in real time. The purpose of this study was to determine the reliability and validity of the novel system in advance of clinical application.MethodsThree evaluators measured chest expansion in 33 healthy individuals using tape measure, which is used for the measurement traditionally, and BREATH. The wire for BREATH system was threaded over the thoracic continuously and the data was recorded automatically; whereas the tape was winded and measured each maximal expiration and inspiration timing by evaluator. All participants were performed both measurement simultaneously for three times during deep breath. In this study, we studied chest expansion score without using biofeedback data of BREATH to check the validity of the result. To confirm intra- and inter-evaluator reliability, we computed intra-class correlations (ICCs). We used Pearson’s correlation coefficient to evaluate the validity of measurement result by BREATH with reference to the tape measure results.ResultsThe average (standard deviation) chest expansion scores for all, men and women by the tape measure were 5.53 (1.88), 6.40 (1.69) and 5.22 (1.39) cm, respectively, and those by BREATH were 3.89 (2.04), 4.36 (1.83) and 2.89 (1.66) cm, respectively. ICC within and among the three evaluators for BREATH and the tape measure were 0.90-0.94 and 0.85-0.94 and 0.85 and 0.82, respectively. The correlation coefficient between the two methods was 0.76-0.87.ConclusionThe novel measurement system, BREATH, has high intra- and inter-evaluator reliabilities and validity; therefore it can lead us more effective respiratory exercise. Using its biofeedback data, this system may help patients with respiratory disease to do exercises more efficiently and clinicians to assess the respiratory exercise more accurately.