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Cardiac Signals Processing

A Special Issue of Sensors (ISSN 1424-8220) belonging to the section "Biomedical Sensors".

Deadline for manuscript submissions: 30 October 2026 | Viewed by 1049

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Guest Editor
School of Engineering, Ulster University, Building BC, York Street, Belfast BT15 1AP, UK
Interests: cardiovascular diagnostics and therapeutics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The heart organ in humans causes strong dynamic changes in several physical variables of various natures, including mechanical, sound, electrical, magnetic and plethysmographic. These may be sensed by means of various techniques and directly result in various important signals that require some signal processing for their useful clinical interpretation and cardiac diagnostics. Other indirectly related signals result when characterising particular body tissues for enabling some effective cardiac therapeutics and may also be included in the wide scope of cardiac applied signal processing methods and techniques in cardiovascular healthcare. Their rapid development and sophistication have increased the reliability and feasibility of long-term continuous non-invasive cardiac monitoring and diagnostics of the heart’s vital signs, as well as for the appropriate configuration of some cardiac therapeutic assistance or permanent destination devices, for the treatment of a particular heart disease. Cardiac applied signal processing for the latter devices is technologically challenging, as they usually require an implantable device in stable long-term operation and they are of increasing demand due to the global ageing population.

Overall Scope:

  • Cardiac signals processing for wearable electrodes sensing applications for long-term monitoring.
  • Cardiac haemodynamic monitoring signals processing methods.
  • Body-surface tissue characterisation signals processing methods for cardiac therapeutics applications.

Prof. Dr. Omar Escalona
Guest Editor

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Keywords

  • cardiac signals processing
  • wearable dry ECG electrodes
  • ambulatory cardiac contractility monitoring
  • long-term cardiac diagnostics
  • transcutaneous coupling bioimpedance spectroscopy
  • cardiovascular therapeutic destination implanted devices
  • capacitive coupling wireless power supply
  • impedance cardiography

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Published Papers (1 paper)

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Research

29 pages, 2119 KB  
Article
Complexity Analysis of Skin Nerve Activity for Quantitative Assessment of Acute Sympathetic Nervous System Activation
by Youngsun Kong, Yubin Choi, Farnoush Baghestani, Dong-Guk Shin, I-Ping Chen and Ki Chon
Sensors 2026, 26(5), 1611; https://doi.org/10.3390/s26051611 - 4 Mar 2026
Viewed by 732
Abstract
Skin nerve activity (SKNA), extracted from electrocardiograms, is a noninvasive surrogate of sympathetic nervous system (SNS) activity. We evaluated whether complexity-based metrics derived from integrated SKNA (iSKNA; 500–1000 Hz) and time-varying SKNA (TVSKNA; 160–1140 Hz) discriminate SNS activation in experimental (n = [...] Read more.
Skin nerve activity (SKNA), extracted from electrocardiograms, is a noninvasive surrogate of sympathetic nervous system (SNS) activity. We evaluated whether complexity-based metrics derived from integrated SKNA (iSKNA; 500–1000 Hz) and time-varying SKNA (TVSKNA; 160–1140 Hz) discriminate SNS activation in experimental (n = 23) and clinical dental datasets (n = 49). Experimental tasks included the Valsalva maneuver and thermal grill stimulation; clinical recordings involved cold testing, with exploratory subgroup analyses based on anxiety status. Pain intensity was assessed using a visual analog scale (VAS); clinically significant pain (CSP+) was defined as a VAS score ≥ 4. Approximate entropy, sample entropy, Hjorth mobility and complexity, Katz fractal dimension, and standard deviation were computed. In the experimental dataset, the Valsalva maneuver produced large-to-huge effects (Cohen’s d = 1.93–3.46, p < 0.001). Thermal grill tasks showed moderate-to-large effects for adjacent pain levels (|d| = 0.63–0.71). ROC analysis showed strong discrimination for baseline vs. pain (AUC 0.80–0.99) but limited separation between adjacent pain levels (AUC 0.56–0.64). In the clinical dataset, discrimination was strongest for no pain vs. CSP+ (|d| = 0.86–1.17), with higher AUC in severe-anxiety participants (0.81–0.96) than non-severe (0.64–0.75). Complexity measures generally decreased during SNS activation, complementing amplitude-based changes. These findings support combined magnitude- and complexity-based descriptors for characterizing short-term sympathetic activation. Full article
(This article belongs to the Special Issue Cardiac Signals Processing)
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