Digital Signal Processing for Healthcare Applications
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 896
Special Issue Editor
Interests: wearable device; biomedical signal processing; biomedical system modeling and simulation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the era of digital health and precision medicine, healthcare applications are undergoing a transformative shift from traditional symptom-driven diagnosis to data-centric, proactive health monitoring and disease management. At the core of this technological evolution lies Digital Signal Processing (DSP), an indispensable interdisciplinary technology that integrates electrical engineering, computer science, applied mathematics and biomedical science. DSP refers to the mathematical manipulation and analysis of discrete digital signals to extract meaningful information, reduce noise interference, enhance signal characteristics and interpret underlying patterns — capabilities that have become foundational to modern healthcare systems.
The scope of DSP applications in healthcare spans the entire healthcare continuum, from non-invasive wearable health monitoring for healthy populations to clinical diagnosis, therapeutic intervention and post-treatment rehabilitation for patients with chronic diseases. For instance, DSP algorithms enable real-time analysis of cardiac signals to detect arrhythmias and myocardial ischemia, process neurological signals to identify seizure activity in epilepsy patients, and extract respiratory features to monitor sleep apnea and chronic respiratory disorders. Beyond clinical diagnostics, DSP also underpins the functionality of portable medical devices, telemedicine systems and personalized health platforms, making high-quality health assessment accessible outside of hospital settings and advancing the goal of universal healthcare equity.
In essence, DSP bridges the gap between raw physiological data and clinical decision-making in healthcare. As healthcare systems continue to embrace digitalization, miniaturization and artificial intelligence integration, the role of DSP will only grow in importance — driving innovation, improving diagnostic accuracy, reducing medical costs and ultimately elevating the quality of patient care and health outcomes. This work thus focuses on exploring the principles, methodologies and practical implementations of DSP, with a specific emphasis on its tailored applications to address key challenges in modern healthcare.
We welcome original research papers on Digital Signal Processing for Healthcare Applications.
Prof. Dr. Hong Tang
Guest Editor
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Keywords
- biomedical engineering
- cardiovascular signal
- vital sign monitoring
- wearable medical devices
- intelligent signal analysis
- disease diagnosis & screening
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