Abstract
An estimated 15 million babies are born prematurely every year worldwide, and suffer from disabilities. Appropriate care of these pre-term babies immediately after birth through telemedicine monitoring is vital. However, problems associated with a limited bandwidth and network overload due to the excessive size of the electromyography (EMG) signal impede the practical application of such medical information systems. Therefore, this research proposes an EMG uterine monitoring transmission solution (EUMTS), a lossless efficient real-time EMG transmission solution that solves such problems through efficient EMG data lossless compression. EMG data samples obtained from the Physionet PhysioBank database were used. Solution performance comparisons were conducted using Lempel-Ziv Welch (LZW) and Huffman methods, in addition to related researches. The LZW and Huffman methods showed CRs of 1.87 and 1.90, respectively, compared to 3.61 for the proposed algorithm. This was relatively high compared to related researches, even when considering that those researches were lossy whereas the proposed research was lossless. The results also showed that the proposed algorithm contributes to a reduction in battery consumption by reducing the wake-up time by 1470.6 ms. Therefore, EUMTS will contribute to providing an efficient wireless transmission environment for the prediction of pre-term delivery, enabling immediate interventions by medical professionals. Another novel point of EUMTS is that it is a lossless algorithm, which will prevent any misjudgement by clinicians because the data will not be distorted. Pre-term babies may receive point-of-care immediately after birth, preventing exposure to the development of disabilities.
Highlights
An estimated 15 million babies are born prematurely every year worldwide, which is more than one in ten [1]
The World Health Organization (WHO) has indicated that almost one million children die annually, due to complications associated with pre-term birth
We proposed an algorithm solution to transmit data in a compact size in real-time, thereby contributing to lessening the strains in the wireless communication bandwidth and data contributing to lessening the strains in the wireless communication bandwidth and data transmission transmission strains in battery consumption
Summary
An estimated 15 million babies are born prematurely (pre-term birth) every year worldwide, which is more than one in ten [1]. Recent studies of a uterine electromyography (EMG) signal focused on the prediction or detection of pre-term birth [4,5] These technologies facilitate the remote monitoring of preterm incidents. Compression of the transmitted data is required This would allow more patients to be supported using a limited bandwidth [8], resulting in a safe EMG signal transmission environment for transmitting maternal patient’s signal. The proposed solution is envisioned to contribute to providing a seamless network platform for preterm telemedicine, facilitating the appropriate care of pre-term babies prior to exposure to infection and contamination.
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