sensors-logo

Journal Browser

Journal Browser

Special Issue "Selected Papers from IEEE ICASI 2018"

A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (30 September 2018).

Special Issue Editors

Prof. Dr. Shoou-Jinn Chang
E-Mail Website
Guest Editor
Department of Electrical Engineering, National Cheng Kung University, Tainan 701, Taiwan
Interests: optical and electronic devices; semi-conductive materials; nanotechnology
Special Issues and Collections in MDPI journals
Prof. Dr. Teen­-Hang Meen
E-Mail Website
Guest Editor
Department of Electronic Engineering National Formosa University, Yunlin 632, Taiwan
Interests: IOT devices; photovoltaic devices; STEM education
Special Issues and Collections in MDPI journals
Dr. Stephen D. Prior
E-Mail Website
Guest Editor
Aeronautics, Astronautics and Computational Engineering, University of Southampton, Southampton SO16 7QF, UK
Interests: microsystem design; nanotechnology
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The 2018 IEEE International Conference on Applied System Innovation (IEEE ICASI 2018) will be held in Chiba, Tokyo, Japan, April 13–17, 2018, and will provide a unified communication platform for material topics. In recent years, applications of advanced materials on microelectronic and optical sensors has been a highly developing field. Due to flexibility and the light weight for daily use, it has the potential to be deployable. The scopes of IEEE ICASI 2018 not only encompasses material sizes at the nanoscale, but also in various dimensions where the onset of size dependent phenomena usually enables novel applications.

This Special Issue selects excellent papers from IEEE ICASI 2018 and covers fundamental materials of electrical and optical engineering, including synthesis engineering, integration with many elements, design of electrical or optical devices, evaluation of various performances and exploring their broad applications in industry, environmental control, material analysis, etc. We invite investigators to contribute original research articles, as well as review articles, that will stimulate the continuing efforts to understand microelectronic and optical sensors. Potential topics include, but are not limited to:

  • Advanced materials with new electronic and optical properties
  • Advanced materials for preparation and applications
  • Subjects related to electro-optical thin films and coatings
  • Synthesis engineering in advanced materials
  • Properties of microelectronic and optical sensors

Schedule

Manuscript Due: June 30, 2018
First Round of Reviews: July 31, 2018
Second Round of Reviews: August 31, 2018
Acceptance of Final papers and Publication: October 15, 2018

Prof. Dr. Shoou-Jinn Chang
Prof. Dr. Teen­Hang Meen
Dr. Stephen D. Prior
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 papers will be 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 2200 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

  • advanced materials
  • microelectronic devices
  • optical sensors

Published Papers (4 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Experiments on Temperature Changes of Microbolometer under Blackbody Radiation and Predictions Using Thermal Modeling by COMSOL Multiphysics Simulator
Sensors 2018, 18(8), 2593; https://doi.org/10.3390/s18082593 - 08 Aug 2018
Cited by 8 | Viewed by 2496
Abstract
In this study, we study a heat transfer model, with the surface of the microbolometer device receiving radiation from blackbody constructed using a COMSOL Multiphysics simulator. We have proposed three kinds of L-type 2-leg and 4-leg with the pixel pitch of 35 μm [...] Read more.
In this study, we study a heat transfer model, with the surface of the microbolometer device receiving radiation from blackbody constructed using a COMSOL Multiphysics simulator. We have proposed three kinds of L-type 2-leg and 4-leg with the pixel pitch of 35 μm based on vanadium oxide absorbent membrane sandwiched with top passivated and bottom Si3N4 supporting films, respectively. Under the blackbody radiation, the surface temperature changes and distributions of these samples are simulated and analyzed in detail. The trend of change of the temperature dependent resistance of the four kinds of bolometer devices using the proposed heat transfer model is consistent with the actual results of the change of resistance of 4 samples irradiated with 325 K blackbody located in the front distance of 5 cm. In this paper, ΔT indicates the averaged differences of the top temperature on the suspended membrane and the lowest temperature on the post of legs of the microbolometers. It is shown that ΔT ≈ 17 mK is larger in nominal 2-leg microbolometer device than that of 4-leg one and of 2-leg with 2 μm × 2 μm central square hole and two 7.5 μm × 2 μm slits in suspended films. Additionally, only ΔT ≈ 5 mK with 4-leg microbolometer device under the same radiated energy of 325 K blackbody results from the larger total thermal conductance. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICASI 2018)
Show Figures

Figure 1

Article
An Augmented Reality System Using Improved-Iterative Closest Point Algorithm for On-Patient Medical Image Visualization
Sensors 2018, 18(8), 2505; https://doi.org/10.3390/s18082505 - 01 Aug 2018
Cited by 18 | Viewed by 2035
Abstract
In many surgery assistance systems, cumbersome equipment or complicated algorithms are often introduced to build the whole system. To build a system without cumbersome equipment or complicated algorithms, and to provide physicians the ability to observe the location of the lesion in the [...] Read more.
In many surgery assistance systems, cumbersome equipment or complicated algorithms are often introduced to build the whole system. To build a system without cumbersome equipment or complicated algorithms, and to provide physicians the ability to observe the location of the lesion in the course of surgery, an augmented reality approach using an improved alignment method to image-guided surgery (IGS) is proposed. The system uses RGB-Depth sensor in conjunction with the Point Cloud Library (PCL) to build and establish the patient’s head surface information, and, through the use of the improved alignment algorithm proposed in this study, the preoperative medical imaging information obtained can be placed in the same world-coordinates system as the patient’s head surface information. The traditional alignment method, Iterative Closest Point (ICP), has the disadvantage that an ill-chosen starting position will result only in a locally optimal solution. The proposed improved para-alignment algorithm, named improved-ICP (I-ICP), uses a stochastic perturbation technique to escape from locally optimal solutions and reach the globally optimal solution. After the alignment, the results will be merged and displayed using Microsoft’s HoloLens Head-Mounted Display (HMD), and allows the surgeon to view the patient’s head at the same time as the patient’s medical images. In this study, experiments were performed using spatial reference points with known positions. The experimental results show that the proposed improved alignment algorithm has errors bounded within 3 mm, which is highly accurate. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICASI 2018)
Show Figures

Figure 1

Article
Levenberg-Marquardt Neural Network Algorithm for Degree of Arteriovenous Fistula Stenosis Classification Using a Dual Optical Photoplethysmography Sensor
Sensors 2018, 18(7), 2322; https://doi.org/10.3390/s18072322 - 17 Jul 2018
Cited by 44 | Viewed by 2272
Abstract
This paper proposes a noninvasive dual optical photoplethysmography (PPG) sensor to classify the degree of arteriovenous fistula (AVF) stenosis in hemodialysis (HD) patients. Dual PPG measurement node (DPMN) becomes the primary tool in this work for detecting abnormal narrowing vessel simultaneously in multi-beds [...] Read more.
This paper proposes a noninvasive dual optical photoplethysmography (PPG) sensor to classify the degree of arteriovenous fistula (AVF) stenosis in hemodialysis (HD) patients. Dual PPG measurement node (DPMN) becomes the primary tool in this work for detecting abnormal narrowing vessel simultaneously in multi-beds monitoring patients. The mean and variance of Rising Slope (RS) and Falling Slope (FS) values between before and after HD treatment was used as the major features to classify AVF stenosis. Multilayer perceptron neural networks (MLPN) training algorithms are implemented for this analysis, which are the Levenberg-Marquardt, Scaled Conjugate Gradient, and Resilient Back-propagation, to identify the degree of HD patient stenosis. Eleven patients were recruited with mean age of 77 ± 10.8 years for analysis. The experimental results indicated that the variance of RS in the HD hand between before and after treatment was significant difference statistically to stenosis (p < 0.05). Levenberg-Marquardt algorithm (LMA) was significantly outperforms the other training algorithm. The classification accuracy and precision reached 94.82% and 92.22% respectively, thus this technique has a potential contribution to the early identification of stenosis for a medical diagnostic support system. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICASI 2018)
Show Figures

Figure 1

Article
An Accurate Bioimpedance Measurement System for Blood Pressure Monitoring
Sensors 2018, 18(7), 2095; https://doi.org/10.3390/s18072095 - 29 Jun 2018
Cited by 19 | Viewed by 3788
Abstract
One potential method to estimate noninvasive cuffless blood pressure (BP) is through measurement of pulse wave velocity (PWV), which can be characterized by measuring the distance and the transit time of the pulse between two arterial sites. To obtain the pulse waveform, bioimpedance [...] Read more.
One potential method to estimate noninvasive cuffless blood pressure (BP) is through measurement of pulse wave velocity (PWV), which can be characterized by measuring the distance and the transit time of the pulse between two arterial sites. To obtain the pulse waveform, bioimpedance (BI) measurement is a promising approach because it continuously reflects the change in BP through the change in the arterial cross-sectional area. Several studies have investigated BI channels in a vertical direction with electrodes located along the wrist and the finger to calculate PWV and convert to BP; however, the measurement systems were relatively large in size. In order to reduce the total device size for use in a PWV-based BP smartwatch, this study proposes and examines a horizontal BI structure. The BI device is also designed to apply in a very small body area. Our proposed structure is based on two sets of four-electrode BI interface attached around the wrist. The effectiveness of our system and approach is evaluated on 15 human subjects; the PWV values are obtained with various distances between two BI channels to assess the efficacy. The results show that our BI system can monitor pulse rate efficiently in only a 0.5 × 1.75 cm2 area of the body. The correlation of pulse rate from the proposed design against the reference is 0.98 ± 0.07 (p < 0.001). Our structure yields higher detection ratios for PWV measurements of 99.0 ± 2.2%, 99.0 ± 2.1%, and 94.8 ± 3.7% at 1, 2, and 3 cm between two BI channels, respectively. The measured PWVs correlate well with the BP standard device at 0.81 ± 0.08 and 0.84 ± 0.07 with low root-mean-squared-errors at 7.47 ± 2.15 mmHg and 5.17 ± 1.81 mmHg for SBP and DBP, respectively. Our results inform future designs of smart watches capable of measuring blood pressure. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICASI 2018)
Show Figures

Figure 1

Back to TopTop