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Technologies
Special Issues
Digital Data Processing Technologies: Trends and Innovations
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Digital Data Processing Technologies: Trends and Innovations

A special issue of Technologies (ISSN 2227-7080).

Deadline for manuscript submissions: 15 February 2026 | Viewed by 325

Special Issue Editor

Prof. Dr. Len Gelman

E-Mail Website
Guest Editor
Department of Engineering, School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK
Interests: condition monitoring; structural health monitoring; non-destructive testing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Novel digital data processing technologies have become very important for all industrial sectors, healthcare, and academic research. 

The main challenges for these technologies are as follows:

  • Most industrial assets and assets in healthcare and bioengineering work in transient conditions, and most asset excitations are also transient;
  • Most acoustical, vibration, and current data captured from these assets, engineering structures, and materials are transient.

Addressing these challenges requires novel transient and stationary data processing technologies related to frequency and time-frequency, as well as the non-linear higher-order spectral analysis of acoustical, vibration, and current data, novel transient artificial intelligence technologies, and novel adaptations of these technologies to transient conditions related to machineries, structures, and materials.

This Special Issue will not cover non-novel “case study papers”. Potential authors need to make clear statements of manuscript novelties that should be based on comprehensive state-of-the art reviews.

Research areas may include (but are not limited) to the following:

  • Novel transient and stationary data processing technologies for all industrial sectors, bioengineering, and healthcare;
  • Novel artificial intelligence technologies for decision-making;
  • Novel structural health monitoring technologies and systems;
  • Novel non-destructive testing technologies and systems;
  • Novel condition monitoring technologies and systems;
  • Novel adaptive technologies and systems;
  • Novel technologies and systems for linear and non-linear assets.

Prof. Dr. Len Gelman
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Technologies is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • transient conditions
  • digital data processing
  • artificial intelligence
  • data analysis
  • structural health monitoring
  • non-destructive testing
  • condition monitoring
  • adaptive technologies
  • stationary and transient data processing

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

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28 pages, 5163 KiB  
Article
Design of High-Pass and Low-Pass Active Inverse Filters to Compensate for Distortions in RC-Filtered Electrocardiograms
by Dobromir Dobrev, Tatyana Neycheva, Vessela Krasteva and Irena Jekova
Technologies 2025, 13(4), 159; https://doi.org/10.3390/technologies13040159 - 15 Apr 2025
Viewed by 308
Abstract
Distortions of electrocardiograms (ECGs) caused by mandatory high-pass and low-pass analog RC filters in ECG devices are always present. The fidelity of the ECG waveform requires limiting the RC cutoff frequencies of the diagnostic (0.05–150 Hz) and monitoring systems (0.5–40 Hz). However, the [...] Read more.
Distortions of electrocardiograms (ECGs) caused by mandatory high-pass and low-pass analog RC filters in ECG devices are always present. The fidelity of the ECG waveform requires limiting the RC cutoff frequencies of the diagnostic (0.05–150 Hz) and monitoring systems (0.5–40 Hz). However, the use of fixed frequency bands is a compromise between enhanced noise immunity and ECG distortions. This study aims to propose active inverse high-pass and low-pass filters which are able to compensate for distortions in digital recordings of RC-filtered ECGs, thereby overcoming the limitations imposed by analog filtering. A new straightforward design of an inverse high-pass filter (IHPF) uses an integrator as the forward-path gain block, with a feedback loop containing an active digital filter equivalent to the analog RC high-pass filter. In contrast, the inverse low-pass filter (ILPF) employs a constant-gain block in the forward path to ensure stability and prevent phase delay, while its feedback path features an active digital counterpart of the RC low-pass filter. Second-order inverse filters are created by cascading two first-order stages. The proposed filters were validated according to essential performance requirements for electrocardiographs. The low-frequency (impulse) responses of IHPFs with cutoff frequencies of 0.05–5 Hz exhibit no overshoot and undershoot by magnitudes of 0.1–25 µV, well within the ±100 µV compliance limit defined for a test rectangular pulse (3 mV, 100 ms). The high-frequency responses of ILPFs with cutoff frequencies of 10–150 Hz present a relative amplitude drop of only 0.2–2.5%, far below the 10% limit for peak amplitude reduction of a triangular pulse (1.5 mV) with 20 ms vs. 200 ms widths. For any of the eight ECG leads (I, II, and V1–V6) available in the standard signal (ANE20000), the IHPF (0.05–5 Hz) presents ST-segment deviations <5 μV (within the ±25 μV limit) and R- and S-peak deviations <±3.5% (within the ±5% limit). The ILPF (10–150 Hz) preserves R- and S-peak amplitudes with deviations less than −1%. Diagnostic-level recovery of ECG waveforms distorted by first- and second-order analog RC filters in ECG devices is possible with the innovative and comprehensive inverse filter design presented in this study. This approach offers a significant advancement in ECG signal processing, effectively restoring essential waveform components even after aggressive, noise-robust analog filtering in ECG acquisition circuits. Although validated for ECG signals, the proposed inverse filters are also applicable to other biosignal front-end circuits employing RC coupling. Full article
(This article belongs to the Special Issue Digital Data Processing Technologies: Trends and Innovations)
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