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Intelligent Medical Sensors and Applications
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Intelligent Medical Sensors and Applications

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

Deadline for manuscript submissions: 10 June 2024 | Viewed by 2575

Special Issue Editors

Prof. Dr. Dong Ming

E-Mail Website
Guest Editor
Medical College, Tianjin University, Tianjin 300072, China
Interests: neural engineering; rehabilitation engineering; biomedical instrumentation, and signal/image processing; brain–computer interface; functional electrical stimulation; gait analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Shuang Li

E-Mail Website
Guest Editor
Medical College, Tianjin University, Tianjin, China
Interests: intelligent medical sensing; smartphone-based biosensors; wearable monitoring; visual detection; POCT
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Intelligent medical sensors are widely used in auxiliary medical equipment. The intelligent medical sensor is gradually replacing traditional medical diagnosis technology with the advantages of a small size, cost-effectiveness, rapidity, specificity, and sensitivity. With the development of advanced technologies such as nanomaterials, smartphones, and the Internet of Things, diagnosis technology based on medical sensors has broad prospects. In addition, different types of intelligent medical sensors, such as electrochemical sensors, optical sensors, piezoelectric sensors, and Internet of Things sensors, are also worth further research. In the future, how to derive more intelligent, accurate, and modal medical sensors will be of great interest to researchers, but this will be extremely challenging.

Prof. Dr. Dong Ming
Dr. Shuang Li
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

  • machine learning
  • artificial intelligence
  • telemedicine
  • physiological signal monitoring
  • in vitro or in vivo detection
  • portable or wearable sensors
  • flexible sensor
  • implantable biosensors
  • IoT
  • wireless connection
  • organ-on-chip

Published Papers (3 papers)

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Research

17 pages, 3079 KiB  
Article
Application of Independent Component Analysis and Nelder–Mead Particle Swarm Optimization Algorithm in Non-Contact Blood Pressure Estimation
by Te-Jen Su, Wei-Hong Lin, Qian-Yi Zhuang, Ya-Chung Hung, Wen-Rong Yang, Bo-Jun He and Shih-Ming Wang
Sensors 2024, 24(11), 3544; https://0-doi-org.brum.beds.ac.uk/10.3390/s24113544 - 30 May 2024
Abstract
In recent years, hypertension has become one of the leading causes of illness and death worldwide. Changes in lifestyle among the population have led to an increasing prevalence of hypertension. This study proposes a non-contact blood pressure estimation method that allows patients to [...] Read more.
In recent years, hypertension has become one of the leading causes of illness and death worldwide. Changes in lifestyle among the population have led to an increasing prevalence of hypertension. This study proposes a non-contact blood pressure estimation method that allows patients to conveniently monitor their blood pressure values. By utilizing a webcam to track facial features and the region of interest (ROI) for obtaining forehead images, independent component analysis (ICA) is employed to eliminate artifact signals. Subsequently, physiological parameters are calculated using the principle of optical wave reflection. The Nelder–Mead (NM) simplex method is combined with the particle swarm optimization (PSO) algorithm to optimize the empirical parameters, thus enhancing computational efficiency and accurately determining the optimal solution for blood pressure estimation. The influences of light intensity and camera distance on the experimental results are also discussed. Furthermore, the measurement time is only 10 s. The superior accuracy and efficiency of the proposed methodology are demonstrated by comparing them with those in other published literature. Full article
(This article belongs to the Special Issue Intelligent Medical Sensors and Applications)
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21 pages, 5069 KiB  
Article
Comparative Sensing and Judgment Control System for Temperature Maintenance for Optimal Treatment in Hyperthermic Intraperitoneal Chemotherapy Surgery
by Tae-Hyeon Lee, Kicheol Yoon, Sangyun Lee, Woong Rak Choi and Kwang Gi Kim
Sensors 2024, 24(2), 596; https://0-doi-org.brum.beds.ac.uk/10.3390/s24020596 - 17 Jan 2024
Viewed by 807
Abstract
For tumors wherein cancer cells remain in the tissue after colorectal cancer surgery, a hyperthermic anticancer agent is injected into the abdominal cavity to necrotize the remaining cancer cells with heat using a hyperthermic intraperitoneal chemotherapy system. However, during circulation, the processing temperature [...] Read more.
For tumors wherein cancer cells remain in the tissue after colorectal cancer surgery, a hyperthermic anticancer agent is injected into the abdominal cavity to necrotize the remaining cancer cells with heat using a hyperthermic intraperitoneal chemotherapy system. However, during circulation, the processing temperature is out of range and the processing result is deteriorated. This paper proposes a look-up table (LUT) module design method that can stably maintain the processing temperature range during circulation via feedback. If the temperature decreases or increases, the LUT transmits a command signal to the heat exchanger to reduce or increase heat input, thereby maintaining the treatment temperature range. The command signal for increasing and decreasing heat input is Tp and Ta, respectively. The command signal for the treatment temperature range is Ts. If drug temperatures below 41 and above 43 °C are input to the LUT, it sends a Tp or Ta signal to the heat exchanger to increase or decrease the input heat, respectively. If the drug’s temperature is 41–43 °C, the LUT generates a Ts signal and proceeds with the treatment. The proposed system can automatically control drug temperature using temperature feedback to ensure rapid, accurate, and safe treatment. Full article
(This article belongs to the Special Issue Intelligent Medical Sensors and Applications)
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Graphical abstract

13 pages, 2115 KiB  
Article
Differences in EEG Event-Related Potentials during Dual Task in Parkinson’s Disease Carriers and Non-Carriers of the G2019S-LRRK2 Mutation
by Eden Shkury, Shani Danziger-Schragenheim, Zoya Katzir, Yael Ezra, Nir Giladi, Anat Mirelman and Inbal Maidan
Sensors 2023, 23(19), 8266; https://0-doi-org.brum.beds.ac.uk/10.3390/s23198266 - 6 Oct 2023
Viewed by 1078
Abstract
Background: The G2019S-LRRK2 gene mutation is a common cause of hereditary Parkinson’s disease (PD), associated with a higher frequency of the postural instability gait difficulty (PIGD) motor phenotype yet with preserved cognition. This study investigated neurophysiological changes during motor and cognitive tasks [...] Read more.
Background: The G2019S-LRRK2 gene mutation is a common cause of hereditary Parkinson’s disease (PD), associated with a higher frequency of the postural instability gait difficulty (PIGD) motor phenotype yet with preserved cognition. This study investigated neurophysiological changes during motor and cognitive tasks in PD patients with and without the G2019S-LRRK2 mutation. Methods: 33 iPD patients and 22 LRRK2-PD patients performed the visual Go/NoGo task (VGNG) during sitting (single-task) and walking (dual-task) while wearing a 64-channel EEG cap. Event-related potentials (ERP) from Fz and Pz, specifically N200 and P300, were extracted and analyzed to quantify brain activity patterns. Results: The LRRK2-PD group performed better in the VGNG than the iPD group (group*task; p = 0.05). During Go, the iPD group showed reduced N2 amplitude and prolonged N2 latency during walking, whereas the LRRK2-PD group showed only shorter latency (group*task p = 0.027). During NoGo, opposite patterns emerged; the iPD group showed reduced N2 and increased P3 amplitudes during walking while the LRRK2-PD group demonstrated increased N2 and reduced P3 (N2: group*task, p = 0.010, P3: group*task, p = 0.012). Conclusions: The LRRK2-PD group showed efficient early cognitive processes, reflected by N2, resulting in greater neural synchronization and prominent ERPs. These processes are possibly the underlying mechanisms for the observed better cognitive performance as compared to the iPD group. As such, future applications of intelligent medical sensing should be capable of capturing these electrophysiological patterns in order to enhance motor–cognitive functions. Full article
(This article belongs to the Special Issue Intelligent Medical Sensors and Applications)
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