Tidal Volume Estimation Using the Blanket Fractal Dimension of the Tracheal Sounds Acquired by Smartphone

Abstract

In this paper, we propose the use of blanket fractal dimension (BFD) to estimate the tidal volume from smartphone-acquired tracheal sounds. We collected tracheal sounds with a Samsung Galaxy S4 smartphone, from five (N = 5) healthy volunteers. Each volunteer performed the experiment six times; first to obtain linear and exponential fitting models, and then to fit new data onto the existing models. Thus, the total number of recordings was 30. The estimated volumes were compared to the true values, obtained with a Respitrace system, which was considered as a reference. Since Shannon entropy (SE) is frequently used as a feature in tracheal sound analyses, we estimated the tidal volume from the same sounds by using SE as well. The evaluation of the performed estimation, using BFD and SE methods, was quantified by the normalized root-mean-squared error (NRMSE). The results show that the BFD outperformed the SE (at least twice smaller NRMSE was obtained). The smallest NRMSE error of 15.877% ± 9.246% (mean ± standard deviation) was obtained with the BFD and exponential model. In addition, it was shown that the fitting curves calculated during the first day of experiments could be successfully used for at least the five following days.

On Deriving Tidal Volume From Electrocardiogram During Maximal Effort Test

“…However, only little research concerning the estimation of tidal volume (TV) has been published. To the best of our knowledge, previous studies focused on noninvasive TV estimation have mostly considered ECG-unrelated techniques, such as inductive [5] or opto-electronic plethysmography [6], traqueal sounds [7] or even image acquisition using a smarthpone camera [8]. However, proportionality between ECG-derived respiration (EDR) and TV was reported in [2], whereas in [9] they conducted a conceptual study for estimating TV from ECG or intra-cardiac signals [9] in mechanically ventilated swines, hence in a controlled environment.…”

Photoplethysmography Signal Analysis for Optimal Region-of-Interest Determination in Video Imaging on a Built-In Smartphone under Different Conditions

“…In other words, they are suitable for developing monitoring systems that can potentially be used by the general public [ 3 ]. They have accordingly been found to be accurate in a variety of vital sign monitoring applications [ 4 , 5 , 6 , 7 ]. Recently, our research group proposed an approach using dual cameras consisting of contact and noncontact video monitoring directly implemented on a smartphone for estimation of heart rate (HR) and the mean respiratory rate (RR), respectively [ 8 ].…”

Identification of S1 and S2 Heart Sound Patterns Based on Fractal Theory and Shape Context

“…For lung sounds belonging to pediatric patients, Katz FD (KFD) [17] is applied in identification of crackles and swallowing in [18,19]. In [20], blanket method (BFD) is used for the tidal volume estimation using tracheal sounds. In the previous work of our group, initial examination of blanket method is shown as a possible tool for primary heart sounds as well [21].…”