This study aims to improve the understanding of explainability in deep learning (DL) architectures utilized for heart disease (HD) classification through electrocardiogram (ECG) data. It offers a systematic review of methodological choices, analyses their impacts on model interpretability, and highlights significant challenges in this domain while suggesting opportunities for future research. A systematic literature review (SLR) was conducted based on Kitchenham and Charters guidelines. To address the proposed research questions, this article provides an SLR of academic articles on Explainable AI (XAI)-based DL for the classification of HDs using ECGs dated from January 2018 to September 2024. Results were synthesized by identifying the valuable insights into the datasets, preprocessing methods, and techniques employed in the development of XAI-based DL models for the classification of ECG-based HDs. This study identified 6448 primary studies that utilized machine learning and DL techniques for the classification of HD based on ECG data, of which 51 used an XAI-based DL architecture. Our finding indicates that there are 25 different datasets that were used, 16 different DL architectures were introduced, and eight novel XAI techniques were introduced, while most of the selected studies used the conventional XAI approaches such as SHAP, Saliency Maps, Grad-Cam, and LIME. A considerable amount of XAI-based DL architectures were identified for the classification of ECG-based HD. The techniques frequently selected by these studies have potential limitations such as data standardization, inconsistent explainability, temporal dependency visualization, lack of XAI benchmarking, lack of standardized metrics, and many more, which are presented with proposed future research directions.

This letter presents a novel passive focusing metasurface designed for wrist pulse detection within the 60 GHz millimeter wave frequency range, incorporating a dual-layer transmitarray antenna. The proposed metasurface demonstrates exceptional polarization characteristics and a high degree of operational efficiency, as substantiated by rigorous far-field assessments. This innovative metasurface has significant potential for applications in human-device interfaces, health monitoring systems, and safety screening protocols, where the ability to focus and manipulate waves with flexibility is paramount. We rigorously evaluated its radiative safety and compared its efficacy with a conventional photoplethysmogram (PPG) reference. The results show a close agreement between our proposed design and the PPG.

This study introduces a novel method employing adaptable transmitarray lenses for medical radar systems, enhancing the direction of electromagnetic beams in the far-field. The newly developed antenna array exhibited marked improvements in gain, bandwidth, return loss, and isolation within specific frequency ranges during testing. Comprehensive evaluations, including various focal lengths and bending scenarios, underscored the superior performance of this adaptable lens over prior techniques. Its exceptional precision and sensitivity render it an ideal tool for real-time remote health monitoring systems, particularly in pulse detection. The research findings consistently aligned the heart rates detected by this innovative method with standard reference rates, reaffirming its reliability and accuracy. This consistency highlights the potential of the transmitarray lenses as a valuable advancement in medical radar systems. The study not only validates the effectiveness and reliability of the lenses but also lays a solid foundation for further research and development in this field. The insights garnered are expected to significantly bolster the progression of radar technologies in healthcare, leading to more accurate, efficient, and non-invasive health monitoring solutions, thereby enhancing patient care and outcomes.

This study introduces a novel seatbelt-integrated, non-invasive, beam-focusing metamaterial sensing system characterized by its thinness and flexibility. The system comprises a flexible transmitarray lens and an FMCW radar sensor, enabling the accurate detection and analysis of seatbelt usage and positioning through human tissue. The metasurface design remains effective even when subjected to different bending angles. Our system closely tracks heart rate and respiration, validated against standard reference methods, highlighting its potential for enhancing in-car healthcare monitoring. Experimental results demonstrate the system’s reliability in monitoring physiological signals within dynamic vehicular environments.

The number of mobile users is increasing rapidly, 3GPP initiated a new technology 4G Long Term Evolution (LTE). LTE is an enabling technology as a solution to the problem of network capacity and quality in areas that have a high demand like Sleman. The quality of LTE networks are supported by backbone and distribution network. This paper describes the designing of fiber optic network as the LTE backbone network in Sleman. The backbone network requires G-652 optical cable along 85 km with a ring topology and WDM-STM64 technology. The distribution network uses GPON technology and the type of G984 optical cable along 61.35 km. The minimum of power received at the end-point in the optisystem simulation is −25 dBm and −26 dBm through the calculation, this value is good because it is still above the minimum of power received (Receiver Sensitivity) −28 dBm which refers to the standard parameters of G.984.2. The average value of rise time is 69 ps, this value is still below the maximum allowable value of rise time 70 ps. Average BER of backbone link is 5×10⁻⁴.

EDFA (Erbium Doped Fiber Amplifier) is an amplifier where EDFA material consists of glass materials such as Er, SiO, and GeO. Erbium (Er) is a class of lanthanides in which this section is suitable as an active ingredient in solid state lasers. In this research, we do the design of fiber optic backbone network using EDFA in Sleman District. This research was conducted to find out how much EDFA needed to reach the transmission distance of 146,25 km. In addition, another purpose of this research is to know the design that has been fulfilled the needs of fiber optic network, based on data transmission distance and performance parameters such as Power Received at -7 to -30 dBm, Q Factor minimum 6, BER (Bit Error Rate) \pmb ≤ 10-9, and minimum OSNR (Optical Signal to Noise Ratio) 13.5 dB. The method used is to calculate the maximum distance of transmission before and after using the amplifier. Then perform performance parameter calculations before and after the addition of EDFA. Before using EDFA various performance parameters have not met the standard, but after application of EDFA as Booster Amplifier for downstream transmission and Pre-Amplifier for upstream transmission, performance parameters have met the standard. After performing the calculation, it takes 1 set of EDFA with maximum range of 152 km. This means it is able to meet the needs of fiber-optic network of Sleman District based data transmission distance. In this design also requires EDFA to meet the performance standards.