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Sensors-Based Healthcare Diagnostics, Monitoring and Medical Devices
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Sensors-Based Healthcare Diagnostics, Monitoring and Medical Devices

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

Deadline for manuscript submissions: 30 June 2025 | Viewed by 1702

Special Issue Editors

Dr. Shih-Lin Wu

E-Mail Website
Guest Editor
Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan City, Taiwan
Interests: medical image analysis; intelligent robots; Internet of Things; healthcare system; wireless and mobile communication network
Special Issues, Collections and Topics in MDPI journals
Dr. Jen-Jee Chen

E-Mail Website
Guest Editor
College of Artificial Intelligence, National Yang Ming Chiao Tung University (NYCU), Hsinchu, Taiwan
Interests: artificial intelligence; AI Medical Health; 5G V2X and the Internet of Things; robotics and assistive applications

Special Issue Information

Dear Colleagues,

In the rapidly evolving landscape of healthcare technology, sensor-based diagnostics, monitoring, and medical devices represent a frontier of innovation, offering unprecedented opportunities to enhance patient care, improve diagnostic accuracy, and streamline medical procedures. The forthcoming Special Issue, titled "Sensors-Based Healthcare Diagnostics, Monitoring and Medical Devices", will showcase the latest advancements and research in the application of sensor technology within the healthcare field. This Special Issue will bring together original research articles, reviews, and case studies that highlight the development, integration, methodologies, and application of sensors in healthcare settings. We welcome contributions that explore the design, functionality, and implementation of sensor-based technologies for a wide range of healthcare applications, including, but not limited to, chronic disease management, real-time healthcare monitoring, early detections and diagnostics, and non-wearable/wearable healthcare devices.

Key topics of interest include the following:

  • Innovative designs and technologies for healthcare applications;
  • Integration of sensor systems into non-wearable/wearable health devices;
  • Applications of sensors in remote monitoring and telehealth;
  • Development of non-invasive, non-wearable/wearable sensors for real-time and continuous health monitoring;
  • Design and development of handheld, portable devices and systems for rapid diagnostics of diseases;
  • Utilizing smartphones and mobile apps as diagnostic tools for health monitoring and disease detection;
  • Development of add-on devices that can interface with smartphones for enhanced diagnostic capabilities;
  • Development of implantable biosensors for the long-term monitoring of chronic conditions;
  • Systems for remote monitoring of patients with chronic diseases, leveraging IoT (Internet of Things) devices to transmit data to healthcare providers;
  • Artificial intelligence and machine learning use in sensor data analysis;
  • Predictive analytics for early disease detection and intervention based on sensor data;
  • The application of nanotechnology for the enhanced sensitivity and specificity of health-related sensors;
  • Augmented reality (AR) and virtual reality (VR) in medical diagnostics, training, and simulation;
  • The role of sensors in enhancing the accuracy and reliability of diagnostics;
  • Interdisciplinary sensor-driven healthcare innovations;
  • Advancing healthcare education through sensor-based technologies;
  • Sensor networks for monitoring environmental factors affecting public health;
  • Wearable sensors for personal exposure assessment to environmental pollutants;
  • Development of sensors for assessing and monitoring rehabilitation progress in patients recovering from injuries or surgeries;
  • Integration of sensors in assistive devices to aid individuals with disabilities;
  • Security and privacy concerns in remote patient monitoring systems;
  • Ethical, privacy, and security considerations in sensor-based healthcare solutions.

By spotlighting interdisciplinary collaboration across engineering, medicine, and data science, this Special Issue will foster a deeper understanding of how sensor-based technologies can be harnessed to improve healthcare delivery and quality of life. We invite researchers, clinicians, and technologists to contribute their insights, discoveries, and innovations to this exciting field, paving the way for sensor technologies that revolutionize healthcare diagnostics, monitoring, and medical devices.

Dr. Shih-Lin Wu
Dr. Jen-Jee Chen
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

  • sensor-based diagnostics
  • monitoring
  • medical devices
  • healthcare
  • real-time healthcare monitoring
  • early detections and diagnostics
  • non-wearable/wearable healthcare devices

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

Published Papers (2 papers)

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Research

13 pages, 1681 KiB  
Article
Early Findings on the Effectiveness of Novel Awakening Stimuli for Patients with Congenital Central Hypoventilation Syndrome
by Silvia Rapella, Caterina Piazza, Francesco Morandi, Alessandro Carcano, Cinzia Arzilli, Niccolò Nassi, Igor Catalano, Francesca Formica and Emilia Biffi
Sensors 2025, 25(6), 1759; https://doi.org/10.3390/s25061759 - 12 Mar 2025
Viewed by 352
Abstract
Congenital Central Hypoventilation Syndrome (CCHS) is a rare disorder that impairs autonomic breathing control, leading to alveolar hypoventilation and sometimes to central apnoea, predominantly during sleep. Patients typically require nocturnal ventilatory support and alarms to prevent life-threatening desaturation events. However, current alarm systems [...] Read more.
Congenital Central Hypoventilation Syndrome (CCHS) is a rare disorder that impairs autonomic breathing control, leading to alveolar hypoventilation and sometimes to central apnoea, predominantly during sleep. Patients typically require nocturnal ventilatory support and alarms to prevent life-threatening desaturation events. However, current alarm systems integrated into pulse oximeters do not provide adequate assistance at home. To address these limitations, we developed an assistive device with customizable multisensory stimulation that activates based on the severity and duration of desaturation episodes. In a multicenter clinical trial involving 4 children and 11 young adults with CCHS, we assessed the device’s effectiveness and the role of arousals over three nights: one baseline and two test nights. The results showed that the device significantly improved awakening rates and enabled faster recovery from desaturations in young adults. However, no such improvements were observed in children compared to the baseline. Arousal events and sleep efficiency were unaffected by the device in both groups. These findings suggest that the device can enhance the safety and autonomy of young adults with CCHS but may be more effective in alerting caregivers in pediatric cases than directly waking children. Further studies are needed to refine its application across different age groups, given the limited sample size. Full article
(This article belongs to the Special Issue Sensors-Based Healthcare Diagnostics, Monitoring and Medical Devices)
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18 pages, 1394 KiB  
Article
Exploring the Link Between Motor Functions and the Relative Use of the More Affected Arm in Adults with Cerebral Palsy
by Isabelle Poitras, Jade Clouâtre, Alexandre Campeau-Lecours and Catherine Mercier
Sensors 2025, 25(3), 660; https://doi.org/10.3390/s25030660 - 23 Jan 2025
Viewed by 589
Abstract
Individuals with hemiparetic cerebral palsy (CP) exhibit reduced use of their more affected (MA) arm, yet the factors that influence its use during activities of daily living remain elusive. The objectives of this study were to describe the relative use of the MA [...] Read more.
Individuals with hemiparetic cerebral palsy (CP) exhibit reduced use of their more affected (MA) arm, yet the factors that influence its use during activities of daily living remain elusive. The objectives of this study were to describe the relative use of the MA arm during an ecological task, examine its relationship with the level of impairment, and investigate its association with performance in various unilateral and bilateral tasks. Methods: Participants took part in two sessions comprising robotic assessments and clinical assessments of motor functions, as well as accelerometry measurement during kitchen tasks. Four variables were derived from accelerometry data. Stepwise regression analyses were used to identify the best contributors to the accelerometry variables among robotic and clinical assessments. Results: Nineteen adults with CP (34.3 years old ± 11.5; MACS I = 7, II = 6, III = 6) were included. The Use Ratio measured during the kitchen tasks ranged between 0.10 and 0.63. The best predictors of all accelerometry metrics were two bilateral assessments (r2 = 0.23–0.64). Conclusions: The importance of assessing bilateral tasks was reaffirmed by the key role played by two bilateral tasks in determining the relative use of the MA arm. The results support the use of intensity-based accelerometry metrics to measure MA arm use. Full article
(This article belongs to the Special Issue Sensors-Based Healthcare Diagnostics, Monitoring and Medical Devices)
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