Lung capacity estimation through acoustic signal of breath

Abstract

Breathing disorders are generally associated with the lung cancer disease. Through daily treatment, lung cancer patients often use a traditional spirometer to measure their lung capacity. However, the use of a spirometer device for accurate measurement requires some sort of training and adjustment, which may be inconvenient for certain groups of patients, especially the elderly. In addition, the spirometer readings can become unreliable if the measurements are not taken as instructed. On the other hand, a microphone, say the microphone on a hand-held device such as a smart-phone, can easily capture the acoustic signal of breath without certain instructions. This signal can then be processed to estimate the lung capacity. In this paper, we propose a methodology through the simply recorded acoustic signal of breath, splitting the breathing cycle to inhale, pause, exhale and pause phases to measure the depth of the breath along with the time duration and signal energy of the breathing phases. We show how these computed parameters are used to estimate the lung size with a high degree of accuracy. This work is part of a virtual reality platform embedded within a smart-phone to assist lung cancer patients regulate their breath. Furthermore, the lung capacity estimation methodology proposed in this paper can also be used to aid patients with other breathing disorders.