An efficient compression technique for Foetal phonocardiogram signals in remote healthcare monitoring systems

Abstract

Remote Healthcare Monitoring Systems (RHMs) that employ fetal phonocardiography (fPCG) signals are highly efficient technologies for monitoring continuous and long-term fetal heart rate. Wearable devices used in RHMs still face a challenge that decreases their efficacy in terms of energy consumption because these devices have limited storage and are powered by batteries. This paper proposes an effective fPCG compression algorithm to reduce RHM energy consumption. In the proposed algorithm, the Discrete Orthogonal Charlier Moment (DOCMs) is used to extract features of the signal. The householder orthonormalization method (HOM) is used with the Charlier Moment to overcome the propagation of numerical errors that occur when computing high-order Charlier polynomials. The proposed algorithm’s performance is evaluated in terms of CR, PRD, SNR, PSNR, and QS and provides the average values 18.33, 0.21, 48.85, 68.86, and 90.88, respectively. The results of the comparison demonstrate the proposed compression algorithm’s superiority over other algorithms. It also tested in terms of compression speed and computational efficiency. The results indicate that the proposed algorithm has a high Compression speed (218.672 bps) and high computational efficiency (21.33). Additionally, the results reveal that the proposed algorithm decreases the energy consumption of a wearable device due to the transmission time decreasing for data by 3.68 s.

Efficient Analysis of Large-Size Bio-Signals Based on Orthogonal Generalized Laguerre Moments of Fractional Orders and Schwarz–Rutishauser Algorithm

“…The algorithm's pseudo code is presented in Algorithm 1. (17). end for {--Step 4: Obtain the orthogonal matrix Q using the Schwarz-Rutishauser --}…”

“…Hosny et al [15] suggested an efficient Algorithm for the compression of different types of bio-medical signals based on discrete Tchebichef moments and the Artificial Bee Colony (ABC). Fathi et al [16][17][18] introduced different algorithms based on different types of DOMs for the efficient energy compression of bio-medical signals: ECG and FPCG. Such algorithms reveal high superiority concerning remote healthcare monitoring systems.…”

“…The successful utilization of DOMs with 2-D objects (i.e., images) motivates researchers to use these DOMs with 1-D objects (i.e., signals). Many studies used the DOMs as a feature descriptor for signals such as signal reconstruction and compression [15][16][17]21] and signal watermarking [22,23]. Other sets of moments are called complex moments.…”

Efficient Compression of Fetal Phonocardiography Bio-Medical Signals for Internet of Healthcare Things

“…The FPCG signals were digitized using an 8-bit ADC at a sampling rate of 333 Hz and recorded for 1 minute (60 seconds). The performance evaluation parameters are as follows [46,55]: ∑ 𝑓(𝑥) 2 × 100 (27) where 𝑓(𝑥), 𝐹(𝑥) are the original signals and their reconstructed counterparts, respectively.…”

“…The disadvantage of this work was not indicating the energy evaluation for the proposed method. In [46], Charlier moments with the householder method (HOM) were used as an efficient technique to compress the FPCG bio-signal. The advantage of this work is that it achieves good results in the quality of the compressed signals and energy consumption.…”