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Systems for Contactless Monitoring of Vital Signs
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Systems for Contactless Monitoring of Vital Signs

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 778

Special Issue Editors

Dr. Emanuele Piuzzi

E-Mail Website
Guest Editor
Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, 00184 Rome, Italy
Interests: permittivity measurement; non-destructive material characterization; biomedical instrumentation; biomedical measurements
Special Issues, Collections and Topics in MDPI journals
Dr. Orlandino Testa

E-Mail Website
Guest Editor
Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, 00184 Rome, Italy
Interests: synthesis of near and far EM fields; antennas; radars for through-the-wall imaging and vital sign monitoring; microwave circuits; electromagnetic compatibility
Dr. Erika Pittella

E-Mail Website
Guest Editor
Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, 00184 Rome, Italy
Interests: measurement of complex permittivity of materials; time domain reflectometry applications; biomedical instrumentation design; UWB radar system for remote sensing of breath activity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The remote monitoring of vital signs represents a groundbreaking approach to healthcare, enabling the continuous assessment of physiological parameters to improve traditional clinical settings. Thanks to advances in sensor and radar technology, it is now possible to design and develop systems that capture key vital signs, such as heart and respiratory activities, in real time and without direct contact with the patient, along with precise data on patient posture and location.

These systems are particularly valuable in scenarios requiring long-term, non-invasive sensing, such as chronic disease management, post-operative care, home monitoring, and emergency response. In particular, the ability to monitor patients in a continuous and contactless way can improve unobtrusiveness and efficiency in healthcare delivery. Furthermore, combining patient tracking and localization enhances safety, supports timely interventions, and optimizes resource allocation.

For this Special Issue, we invite submissions focusing on innovative systems for the continuous contactless monitoring of vital signs, tracking, and localization. Topics of interest include, but are not limited to, the development of advanced sensing technologies, integration challenges, and the design of reliable, accurate monitoring systems. Key technologies include, but are not limited to, radar sensors, systems based on cameras, and acoustic sensing solutions. Contributions presenting original designs for physiological parameters for contactless sensing systems and their practical implementation in real-world applications are particularly encouraged.

Dr. Emanuele Piuzzi
Dr. Orlandino Testa
Dr. Erika Pittella
Guest Editors

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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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

  • radar remote sensing
  • acoustic sensors
  • infrared sensors
  • optical sensors
  • smart healthcare
  • vital sign sensors
  • non-invasive diagnostics

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Published Papers (2 papers)

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Research

23 pages, 1950 KB  
Article
Multi-Classification Model for PPG Signal Arrhythmia Based on Time–Frequency Dual-Domain Attention Fusion
by Yubo Sun, Keyu Meng, Shipan Lang, Pei Li, Wentao Wang and Jun Yang
Sensors 2025, 25(19), 5985; https://doi.org/10.3390/s25195985 - 27 Sep 2025
Abstract
Cardiac arrhythmia is a leading cause of sudden cardiac death. Its early detection and continuous monitoring hold significant clinical value. Photoplethysmography (PPG) signals, owing to their non-invasive nature, low cost, and convenience, have become a vital information source for monitoring cardiac activity and [...] Read more.
Cardiac arrhythmia is a leading cause of sudden cardiac death. Its early detection and continuous monitoring hold significant clinical value. Photoplethysmography (PPG) signals, owing to their non-invasive nature, low cost, and convenience, have become a vital information source for monitoring cardiac activity and vascular health. However, the inherent non-stationarity of PPG signals and significant inter-individual variations pose a major challenge in developing highly accurate and efficient arrhythmia classification methods. To address this challenge, we propose a Fusion Deep Multi-domain Attention Network (Fusion-DMA-Net). Within this framework, we innovatively introduce a cross-scale residual attention structure to comprehensively capture discriminative features in both the time and frequency domains. Additionally, to exploit complementary information embedded in PPG signals across these domains, we develop a fusion strategy integrating interactive attention, self-attention, and gating mechanisms. The proposed Fusion-DMA-Net model is evaluated for classifying four major types of cardiac arrhythmias. Experimental results demonstrate its outstanding classification performance, achieving an overall accuracy of 99.05%, precision of 99.06%, and an F1-score of 99.04%. These results demonstrate the feasibility of the Fusion-DMA-Net model in classifying four types of cardiac arrhythmias using single-channel PPG signals, thereby contributing to the early diagnosis and treatment of cardiovascular diseases and supporting the development of future wearable health technologies. Full article
(This article belongs to the Special Issue Systems for Contactless Monitoring of Vital Signs)
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13 pages, 1531 KB  
Article
Thermal Cameras for Overnight Measuring of Respiration in a Clinical Setting
by Raquel Alves, Fokke van Meulen, Sebastiaan Overeem, Hennie Janssen, Pauline van Hirtum, Svitlana Zinger and Sander Stuijk
Sensors 2025, 25(19), 5956; https://doi.org/10.3390/s25195956 - 24 Sep 2025
Viewed by 49
Abstract
Thermal imaging is a non-contact method for monitoring respiration activity during sleep. In this study, we evaluated its clinical application during overnight recordings in a sleep clinic. Five thermal cameras were used to detect breaths, the estimated respiration rate (RR), and inter-breath intervals [...] Read more.
Thermal imaging is a non-contact method for monitoring respiration activity during sleep. In this study, we evaluated its clinical application during overnight recordings in a sleep clinic. Five thermal cameras were used to detect breaths, the estimated respiration rate (RR), and inter-breath intervals (IBIs) in seven adults undergoing diagnostic polysomnography (PSG). Forty-five minutes of recordings were selected, consisting of 12 motionless and event-free segments. The thermal videos were processed using an adapted pre-existing thermal video processing algorithm. The respiration signals generated with the thermal cameras were validated against simultaneously recorded signals from the PSG system, the current gold standard for monitoring sleep. The results show a mean absolute error (MAE) ranging between 0.64 and 0.91 breaths per minute for the RR. Breath detection showed a sensitivity of 96.3%, and a precision of 94.1%. The MAE obtained between IBIs was 0.48 s, and the mean IBI variability difference recorded was 3.9 percentage points. In addition, the results from this clinical study show that the use of all five cameras and a single camera revealed no statistically significant differences, demonstrating the work towards a robust system. This first study of thermal cameras for the assessment of respiration in a clinical setting shows us the potential application of thermal imaging in clinical practice for respiration monitoring and establishes a foundation for further implementation in assessing sleep-disordered breathing. Full article
(This article belongs to the Special Issue Systems for Contactless Monitoring of Vital Signs)
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