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In Multidisciplinary Perspectives: Healthcare Technology Research and Education Based on Artificial Intelligence and Simulation

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A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Health".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 43186

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Special Issue Editors

Dr. YoungJin Jung

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Guest Editor

Department of Radiological Science at Health Sciences Division, DongSeo University, Busan 47011, Korea
Interests: bio-signal/image analysis; radiological imaging; computational algorithms; human machine interface; motion analysis; brain stimulation; healthcare with A.I.
Special Issues, Collections and Topics in MDPI journals

Dr. Jong-Hoon Kim

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Assistant Guest Editor

Department of Computer Science, Kent State University, Kent, OH 44242, USA
Interests: analysis of emotional and affective behavioral aspects of robot-human interactions; incorporation of artificial intelligence for assisting smart teleoperations; human-robot interaction through decentralized and distributed platforms such as smart contracts in blockchain technology; tangible coding education for children

Dr. Hae Yean Park

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Assistant Guest Editor

Department of Occupational Therapy, Yonsei University, Wonju 26493, Korea
Interests: occupational therapy; driving rehabilitation; cognitive rehabilitation; pediatric/geriatric care; remote care

Special Issue Information

Dear Colleagues,

Multidisciplinary collaboration research for healthcare technology & education is becoming a important issue for enhancing the public health by providing edge technology. In this context, healthcare technology demands multidisciplinary attention and efforts for advancing research and education. Several issues in this healthcare technology field are inter-disciplinary in health sciences but have been studied and practiced without going advanced cross-technical issues, or a sole technical aspects. Hence, this Special Issue calls for papers that conceptually or practical technology of multidisciplinary research to overcome important healthcare issues through the edge technologies of Computer science, Nursing, Radiological Science, Dental hygiene, Occupational/Physical therapy, Biomedical engineering. Diverse forms of articles (Simulation, Education technologies, Fusion technology for Healthcare, etc.) are welcome. Overall, we would love to see papers working on multidisciplinary healthcare research in a new context, or A.I. / simulation-based edge research for healthcare technology / education. With such a premise, recommended topics may include but are not limited to the following:

- Multidisciplinary theoretical integration for healthcare issues;

- Artificial intelligence (A.I.) technology for healthcare;

- Multidisciplinary research (computer science, nursing, radiological science, dental hygiene, occupational/physical therapy)

- Preventive rehabilitation with prediction with computer science

- Patient care including (community-care)

- Case studies on edge technology for healthcare;

- Safety and quality issues in healthcare technology;

- Bio-signal/image analysis for health care

- Relative review / commentary

- Education science and technology

- Nursing and health sciences and technology

- Welfare and silver technology

- Blockchain technology for healthcare

- Healthcare robotics and telehealth

Dr. YoungJin Jung
Dr. Jong-Hoon Kim
Dr. Hae Yean Park
Guest Editors

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Published Papers (12 papers)

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Research

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11 pages, 1740 KiB

Open AccessArticle

Development of an Artificial Intelligence Model for Analyzing the Relationship between Imaging Features and Glucocorticoid Sensitivity in Idiopathic Interstitial Pneumonia

by Ling Jiang, Meijiao Li, Han Jiang, Liyuan Tao, Wei Yang, Huishu Yuan and Bei He

Int. J. Environ. Res. Public Health 2022, 19(20), 13099; https://doi.org/10.3390/ijerph192013099 - 12 Oct 2022

Viewed by 2074

Abstract

High-resolution CT (HRCT) imaging features of idiopathic interstitial pneumonia (IIP) patients are related to glucocorticoid sensitivity. This study aimed to develop an artificial intelligence model to assess glucocorticoid efficacy according to the HRCT imaging features of IIP. The medical records and chest HRCT images of 150 patients with IIP were analyzed retrospectively. The U-net framework was used to create a model for recognizing different imaging features, including ground glass opacities, reticulations, honeycombing, and consolidations. Then, the area ratio of those imaging features was calculated automatically. Forty-five patients were treated with glucocorticoids, and according to the drug efficacy, they were divided into a glucocorticoid-sensitive group and a glucocorticoid-insensitive group. Models assessing the correlation between imaging features and glucocorticoid sensitivity were established using the k-nearest neighbor (KNN) algorithm. The total accuracy (ACC) and mean intersection over union (mIoU) of the U-net model were 0.9755 and 0.4296, respectively. Out of the 45 patients treated with glucocorticoids, 34 and 11 were placed in the glucocorticoid-sensitive and glucocorticoid-insensitive groups, respectively. The KNN-based model had an accuracy of 0.82. An artificial intelligence model was successfully developed for recognizing different imaging features of IIP and a preliminary model for assessing the correlation between imaging features and glucocorticoid sensitivity in IIP patients was established. Full article

(This article belongs to the Special Issue In Multidisciplinary Perspectives: Healthcare Technology Research and Education Based on Artificial Intelligence and Simulation)

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14 pages, 360 KiB

Open AccessArticle

Application of Metaverse Service to Healthcare Industry: A Strategic Perspective

by Chang Won Lee

Int. J. Environ. Res. Public Health 2022, 19(20), 13038; https://doi.org/10.3390/ijerph192013038 - 11 Oct 2022

Cited by 70 | Viewed by 7552

Abstract

This study is to explore a state of the art in metaverse service that is an emerging issue in applying it to the healthcare industry. The purpose of this study is to provide applicable strategic scenarios for effective metaverse service planning and implementation in healthcare settings. This study is focused on metaverse service as a business model. Thus, related literatures of metaverse service are reviewed in various aspects in healthcare industry. An exploratory approach is used to analyze current qualitative data characterizing healthcare metaverse service business positions and derive applicable strategies from business trends of current metaverse services. Several cases are examined based on the data obtained from various sources of healthcare and other related industries. This study synthesizes finding results and suggests applicable strategies of metaverse service in the healthcare industry. This study will facilitate strategic decision-making and policy-making processes to pursue a business opportunity development through an application of a metaverse service in healthcare and similar settings. Full article

(This article belongs to the Special Issue In Multidisciplinary Perspectives: Healthcare Technology Research and Education Based on Artificial Intelligence and Simulation)

14 pages, 5015 KiB

Open AccessArticle

Sensor Cell Network for Pressure, Temperature and Position Detection on Wheelchair Users

by Cátia Tavares, Daniela Real, Maria de Fátima Domingues, Nélia Alberto, Hugo Silva and Paulo Antunes

Int. J. Environ. Res. Public Health 2022, 19(4), 2195; https://doi.org/10.3390/ijerph19042195 - 15 Feb 2022

Cited by 4 | Viewed by 2684

Abstract

This work proposes an optical sensing network to monitor pressure and temperature in specific areas of a wheelchair to prevent pressure ulcers and to monitor the position of the wheelchair user by analyzing its pressure distribution. The sensing network is composed of six optical fiber Bragg grating (FBG)-based sensor cells. Each sensor cell is built from a polylactic acid (PLA) base and has two FBGs, one embedded in epoxy resin to monitor pressure variations (FBG_P) and another without resin to monitor temperature (FBG_T). Once produced, all sensor cells were experimentally characterized for pressure and temperature variations, resulting in an average pressure sensitivity of 81 ± 5 pm/kPa (FBG_P) and −5.0 ± 0.4 pm/kPa (FBG_T), and an average temperature sensitivity of 25 ± 1 pm/°C (FBG_P) and 47.7 ± 0.7 pm/°C (FBG_T). The sensor cells were then placed in six specific areas of a wheelchair (four in the seat area and two in the shoulder blade area) to carry out experimental tests, wherein the response of the sensors to a specific sequence of relief positions was tested. During the execution of the test, the optical signal of all sensors was monitored, in real time, with the pressure and temperature values detected in each zone of the wheelchair. In addition, random position changes were performed in order to evaluate the precision of the proposed sensing network in the identification of such positions. Full article

(This article belongs to the Special Issue In Multidisciplinary Perspectives: Healthcare Technology Research and Education Based on Artificial Intelligence and Simulation)

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13 pages, 2322 KiB

Open AccessArticle

Assessment of Bi-Ventricular and Bi-Atrial Areas Using Four-Chamber Cine Cardiovascular Magnetic Resonance Imaging: Fully Automated Segmentation with a U-Net Convolutional Neural Network

by Hideo Arai, Masateru Kawakubo, Kenichi Sanui, Ryoji Iwamoto, Hiroshi Nishimura and Toshiaki Kadokami

Int. J. Environ. Res. Public Health 2022, 19(3), 1401; https://doi.org/10.3390/ijerph19031401 - 27 Jan 2022

Cited by 4 | Viewed by 2415

Abstract

Four-chamber (4CH) cine cardiovascular magnetic resonance imaging (CMR) facilitates simultaneous evaluation of cardiac chambers; however, manual segmentation is time-consuming and subjective in practice. We evaluated deep learning based on a U-Net convolutional neural network (CNN) for fully automated segmentation of the four cardiac chambers using 4CH cine CMR. Cine CMR datasets from patients were randomly assigned for training (1400 images from 70 patients), validation (600 images from 30 patients), and testing (1000 images from 50 patients). We validated manual and automated segmentation based on the U-Net CNN using the dice similarity coefficient (DSC) and Spearman’s rank correlation coefficient (ρ); p < 0.05 was statistically significant. The overall median DSC showed high similarity (0.89). Automated segmentation correlated strongly with manual segmentation in all chambers—the left and right ventricles, and the left and right atria (end-diastolic area: ρ = 0.88, 0.76, 0.92, and 0.87; end-systolic area: ρ = 0.81, 0.81, 0.92, and 0.83, respectively; p < 0.01). The area under the curve for the left ventricle, left atrium, right ventricle, and right atrium showed high scores (0.96, 0.99, 0.88, and 0.96, respectively). Fully automated segmentation could facilitate simultaneous evaluation and detection of enlargement of the four cardiac chambers without any time-consuming analysis. Full article

(This article belongs to the Special Issue In Multidisciplinary Perspectives: Healthcare Technology Research and Education Based on Artificial Intelligence and Simulation)

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11 pages, 695 KiB

Open AccessArticle

A Randomized, Double-Blind, Placebo-Controlled Clinical Trial of a Mouthwash Containing Glycyrrhiza uralensis Extract for Preventing Dental Caries

by Yu-Rin Kim and Seoul-Hee Nam

Int. J. Environ. Res. Public Health 2022, 19(1), 242; https://doi.org/10.3390/ijerph19010242 - 26 Dec 2021

Cited by 10 | Viewed by 4072

Abstract

This study sought to confirm the effect of using a mouthwash containing Glycyrrhiza uralensis extract for oral health management by investigating changes in the pH of dental plaque and bacteria that cause dental caries. A randomized, double-blind, placebo-controlled study was conducted on 60 subjects categorized in either the Glycyrrhiza uralensis extract gargle group (n = 30) or the saline gargle group (n = 30). Scaling was conducted in order to ensure the homogeneity of the oral environment, while gargling was performed once daily before the subjects went to bed for 5 days based on the group. Caries activity was assessed using the Cariview test, while detection of the bacteria that cause dental caries was confirmed using microbiological analysis. All clinical measurements and evaluations were conducted by two trained dental hygienists under the supervision of a dentist. Based on the analysis of dental caries activity and dental caries-causing bacteria, the Glycyrrhiza uralensis extract gargle group showed a clear decrease in bacteria compared to the saline gargle group. Glycyrrhiza uralensis extract demonstrated no risk of tooth demineralization. It also showed excellent antibacterial activity through inhibition and effective reduction of bacteria that cause dental caries. Therefore, the mouthwash containing Glycyrrhiza uralensis extract is an effective oral care product suitable for use as an effective dental caries prevention agent. Full article

(This article belongs to the Special Issue In Multidisciplinary Perspectives: Healthcare Technology Research and Education Based on Artificial Intelligence and Simulation)

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13 pages, 569 KiB

Open AccessArticle

Twelve Smartphone Applications for Health Management of Older Adults during the COVID-19 Pandemic

by Seong Kyu Ha, Hey Sig Lee and Hae Yean Park

Int. J. Environ. Res. Public Health 2021, 18(19), 10235; https://doi.org/10.3390/ijerph181910235 - 29 Sep 2021

Cited by 4 | Viewed by 3145

Abstract

This study investigated smartphone applications that may be helpful in managing the health of the elderly during COVID-19. The application searched the seven areas of health management, newly classified in OTPF 4th edition with keywords in the Google Play Store. As a result, two applications meeting the selection criteria were selected for each area. The selected applications are social and emotional health promotion and maintenance: Wysa & MindDoc, symptom and condition management: Ada & Diseases Dictionary, communication with the health care system: Telehealth & Blood Pressure Diary, medication management: Medisafe & MyTherapy, physical activity: FitOn & Samsung Health, nutrition management: Lifesum & Health and Nutrition Guide. Through the analyzed applications, twelve applications with the potential to improve the health management and quality of life in older adults during social distancing or self-isolation due to COVID-19 were identified. Full article

(This article belongs to the Special Issue In Multidisciplinary Perspectives: Healthcare Technology Research and Education Based on Artificial Intelligence and Simulation)

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9 pages, 939 KiB

Open AccessArticle

Effect of Exposure Angulation on the Occupational Radiation Exposure during Cardiac Angiography: Simulation Study

by Younghoon Roh, Jungsu Kim, Hyemin Park, Jungmin Kim, Dongryeol Ryu, Kwangjin Chun, Jeonghun Seo, Bongki Lee, Byungryul Cho and Yongsu Yoon

Int. J. Environ. Res. Public Health 2021, 18(15), 8097; https://doi.org/10.3390/ijerph18158097 - 30 Jul 2021

Cited by 8 | Viewed by 2959

Abstract

Cardiac angiography to visualize the cardiac coronary artery for lesions causes a lot of radiation exposure dose to the interventional cardiologist. We evaluated the occupational radiation exposure to the interventional cardiologist based on changes to the angle of the X-ray tube used in cardiac angiography and calculated the conversion factor for effective dose in this study. To evaluate the occupational radiation exposure resulting from scattered radiation to interventional cardiologists, organ doses for eyeball, thyroid, and heart were calculated using Monte Carlo simulation with korean typical man(KTMAN) phantom at the left anterior oblique (LAO)30/cranial (CRAN)30, CRAN40, right anterior oblique (RAO)30/CRAN30, RAO30/caudal(CAUD)20, CAUD39, LAO40/CAUD35, and LAO40 positions in the femoral and the radial artery puncture. In this study, analysis of the different angles showed the highest radiation exposure on LAO30/CRAN30 and CRAN40 position, which were 150.65% and 135.3%, respectively, compared to AP angles. Therefore, to reduce occupational dose for interventional cardiologists, it is recommended that radiation protection, such as using radiation shield and personal protective equipment (PPE), be used at LAO30/CRAN30 and CRAN40 angulation, and the conversion factor for calculating the organ dose received by the interventional cardiologists based on patient dose can be applied for improved occupational dose management. Full article

(This article belongs to the Special Issue In Multidisciplinary Perspectives: Healthcare Technology Research and Education Based on Artificial Intelligence and Simulation)

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10 pages, 3183 KiB

Open AccessArticle

Proper Management of the Clinical Exposure Index Based on Body Thickness Using Dose Optimization Tools in Digital Chest Radiography: A Phantom Study

by Yongsu Yoon, Hyemin Park, Jungmin Kim, Jungsu Kim, Younghoon Roh, Nobukazu Tanaka and Junji Morishita

Int. J. Environ. Res. Public Health 2021, 18(10), 5203; https://doi.org/10.3390/ijerph18105203 - 13 May 2021

Cited by 5 | Viewed by 3964

Abstract

In radiography, the exposure index (EI), as per the International Electrotechnical Commission standard, depends on the incident beam quality and exposure dose to the digital radiography system. Today automatic exposure control (AEC) systems are commonly employed to obtain the optimal image quality. An AEC system can maintain a constant incident exposure dose on the image receptor regardless of the patient thickness. In this study, we investigated the relationship between body thickness, entrance surface dose (ESD), EI, and the exposure indicator (S value) with the aim of using EI as the dose optimization tool in digital chest radiography (posterior–anterior and lateral projection). The exposure condition from the Korean national survey for determining diagnostic reference levels and two digital radiography systems (photostimulable phosphor plate and indirect flat panel detector) were used. As a result, ESD increased as the phantom became thicker with constant exposure indicator, which indicates similar settings to an AEC system, but the EI indicated comparatively constant values without following the tendency of ESD. Therefore, body thickness should be considered under the AEC system for introducing EI as the dose optimization tool in digital chest radiography. Full article

(This article belongs to the Special Issue In Multidisciplinary Perspectives: Healthcare Technology Research and Education Based on Artificial Intelligence and Simulation)

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10 pages, 4273 KiB

Open AccessArticle

The Whitening Effect and Histological Safety of Nonthermal Atmospheric Plasma Inducing Tooth Bleaching

by Seoul-Hee Nam, Byul Bo Ra Choi and Gyoo-Cheon Kim

Int. J. Environ. Res. Public Health 2021, 18(9), 4714; https://doi.org/10.3390/ijerph18094714 - 28 Apr 2021

Cited by 12 | Viewed by 3071

Abstract

Various light sources have been applied to enhance the bleaching effect. This study was to identify the histological evaluation in oral soft tissues, as well as tooth color change after tooth bleaching by nonthermal atmospheric pressure plasma (NAPP). Nine New Zealand adult female rabbits were randomly divided into three groups (n = 3): group 1 received no treatment; group 2 was treated with NAPP and 15% carbamide peroxide (CP), which contains 5.4% H₂O₂, and group 3 was treated with 15% CP without NAPP. Color change (ΔE) was measured using the Shade Eye NCC colorimeter. Animals were euthanized one day later to analyze the histological responses occurring in oral soft tissues, including pulp, gingiva, tongue, buccal mucosa, and hard and soft palates. Changes in all samples were analyzed by hematoxylin and eosin staining and Masson’s trichrome. Teeth treated with plasma showed higher ΔE than that obtained with bleaching agents alone. Overall, the histological characteristics observed no appreciable changes. The combinational treatment of plasma had not indicated inflammatory responses as well as thermal damages. NAPP did not cause histological damage in oral soft tissues during tooth bleaching. We suggest that NAPP could be a novel alternative energy source to conventional light sources for tooth bleaching. Full article

(This article belongs to the Special Issue In Multidisciplinary Perspectives: Healthcare Technology Research and Education Based on Artificial Intelligence and Simulation)

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10 pages, 1265 KiB

Open AccessArticle

A Randomized, Double-Blind, Placebo-Controlled Trial to Assess the Acidogenic Potential of Dental Biofilms through a Tablet Containing Weissella cibaria CMU

by Mi-Sun Kang, Dong-Suk Lee, Myoungsuk Kim, Seung-Ah Lee and Seoul-Hee Nam

Int. J. Environ. Res. Public Health 2021, 18(9), 4674; https://doi.org/10.3390/ijerph18094674 - 28 Apr 2021

Cited by 5 | Viewed by 2643

Abstract

The possibility of preventing dental caries by taking probiotic bacterium Weissella cibaria (W. cibaria) CMU tablets to alter the pH of the dental plaque in the oral cavity was evaluated. A randomized, double-blind, placebo-controlled trial was performed on adults aged 20 years or older with 20 or more natural teeth. Ninety-two people underwent dental scaling before being randomly assigned to the experimental group (n = 49) or the control group (n = 43). Depending on the group they belonged to, W. cibaria CMU or the placebo was administered to them once daily for 8 weeks before bedtime. Twenty-four subjects were later excluded from the study because the week 8 dosing was not smoothly performed, for a final subject count of 68. The Cariview test was used to evaluate the amount of acid produced by the dental plaque to assess the risk of caries. The results showed that although there was no significant difference between the results of the two groups, the intake of the W. cibaria CMU tablets eliminated the risk of developing dental caries from acid production in the oral flora because the W. cibaria colonizes and lives in the dental plaque and the oral cavity and suppresses acids. Full article

(This article belongs to the Special Issue In Multidisciplinary Perspectives: Healthcare Technology Research and Education Based on Artificial Intelligence and Simulation)

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Review

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20 pages, 1519 KiB

Open AccessReview

Smart Wearable Systems for the Remote Monitoring of Selected Vascular Disorders of the Lower Extremity: A Systematic Review

by Julio Souza, Sara Escadas, Isidora Baxevani, Daniel Rodrigues and Alberto Freitas

Int. J. Environ. Res. Public Health 2022, 19(22), 15231; https://doi.org/10.3390/ijerph192215231 - 18 Nov 2022

Cited by 6 | Viewed by 2860

Abstract

This systematic review aims at providing an overview of the state of the art regarding smart wearable systems (SWS) applications to monitor the status of patients suffering from vascular disorders of the lower extremity. Peer-reviewed literature has been analyzed to identify employed data collection methods, system characteristics, and functionalities, and research challenges and limitations to be addressed. The Medline (PubMed) and SCOPUS databases were considered to search for publications describing SWS for remote or continuous monitoring of patients suffering from intermittent claudication, venous ulcers, and diabetic foot ulcers. Publications were first screened based on whether they describe an SWS applicable to the three selected vascular disorders of the lower extremity, including data processing and output to users. Information extracted from publications included targeted disease, clinical parameters to be measured and wearable devices used; system outputs to the user; system characteristics, including capabilities of remote or continuous monitoring or functionalities resulting from advanced data analyses, such as coaching, recommendations, or alerts; challenges and limitations reported; and research outputs. A total of 128 publications were considered in the full-text analysis, and 54 were finally included after eligibility criteria assessment by four independent reviewers. Our results were structured and discussed according to three main topics consisting of data collection, system functionalities, and limitations and challenges. Full article

(This article belongs to the Special Issue In Multidisciplinary Perspectives: Healthcare Technology Research and Education Based on Artificial Intelligence and Simulation)

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13 pages, 2260 KiB

Open AccessReview

Theme Trends and Knowledge-Relationship in Lifestyle Research: A Bibliometric Analysis

by Ah-Ram Kim and Hae Yean Park

Int. J. Environ. Res. Public Health 2021, 18(14), 7503; https://doi.org/10.3390/ijerph18147503 - 14 Jul 2021

Cited by 16 | Viewed by 4012

Abstract

Healthy living habits (healthy eating, regular physical activity, abstinence from smoking, restrictions on alcohol consumption, and stress management) can help prevent a significant number of diseases. The purpose of this study is to use a bibliometric analysis to analyze the relationships between countries, institutions and authors through lifestyle studies from 2016 to 2020 to find out the latest research trends. This study utilized bibliometric data collected through Scopus including thesis titles, authors, agencies, countries/regions, publication years, and keywords. Data were analyzed using the VOS viewer (Vers. 1.6.13; Leiden University, Leiden, The Netherlands) and the findings were used to visualize similarity mapping techniques. Publication of lifestyle-related research papers has steadily increased between 2016 and 2020. The country/region most actively conducting such research was the United States, also home to the majority of institutions conducting work in the field. PloS ONE published the most lifestyle-related research under the field of Medicine. Identified keywords were related to risk measures, psychosocial factors, prevention, health promotion, and risk factors. Lifestyle research is a promising field of research worldwide and has great potential to improve human health, the environment, and quality of life. The findings are expected to promote future research and give direction to the advancement of the field of research by comprehensively analyzing and summarizing lifestyle research trends. Full article

(This article belongs to the Special Issue In Multidisciplinary Perspectives: Healthcare Technology Research and Education Based on Artificial Intelligence and Simulation)

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