Robust Sleep Quality Quantification Method for a Personal Handheld Device

Abstract

The purpose of this study was to develop and validate a novel method for sleep quality quantification using personal handheld devices. The proposed method used 3- or 6-axes signals, including acceleration and angular velocity, obtained from built-in sensors in a smartphone and applied a real-time wavelet denoising technique to minimize the nonstationary noise. Sleep or wake status was decided on each axis, and the totals were finally summed to calculate sleep efficiency (SE), regarded as sleep quality in general. The sleep experiment was carried out for performance evaluation of the proposed method, and 14 subjects participated. An experimental protocol was designed for comparative analysis. The activity during sleep was recorded not only by the proposed method but also by well-known commercial applications simultaneously; moreover, activity was recorded on different mattresses and locations to verify the reliability in practical use. Every calculated SE was compared with the SE of a clinically certified medical device, the Philips (Amsterdam, The Netherlands) Actiwatch. In these experiments, the proposed method proved its reliability in quantifying sleep quality. Compared with the Actiwatch, accuracy and average bias error of SE calculated by the proposed method were 96.50% and -1.91%, respectively. The proposed method was vastly superior to other comparative applications with at least 11.41% in average accuracy and at least 6.10% in average bias; average accuracy and average absolute bias error of comparative applications were 76.33% and 17.52%, respectively.