Smart Health最新文献_第4页

Latent Space Representation of Adversarial AutoEncoder for Human Activity Recognition: Application to a low-cost commercial force plate and inertial measurement units

Smart Health Pub Date : 2025-01-04 DOI: 10.1016/j.smhl.2024.100537

Kenta Kamikokuryo , Gentiane Venture , Vincent Hernandez

{"title":"Latent Space Representation of Adversarial AutoEncoder for Human Activity Recognition: Application to a low-cost commercial force plate and inertial measurement units","authors":"Kenta Kamikokuryo , Gentiane Venture , Vincent Hernandez","doi":"10.1016/j.smhl.2024.100537","DOIUrl":"10.1016/j.smhl.2024.100537","url":null,"abstract":"<div><div>Human Activity Recognition (HAR) is a key component of a home rehabilitation system that provides real-time monitoring and personalized feedback. This research explores the application of Adversarial AutoEncoder (AAE) models for data dimensionality reduction in the context of HAR. Visualizing data in a lower-dimensional space is important to understand changes in motor control due to medical conditions or aging, to aid personalized interventions, and to ensure continuous benefits in remote rehabilitation settings. This makes patient assessment effective, easier, and faster.</div><div>In this study, the classification performance of the latent space created by the AAE is evaluated using the Wii Balance Board (WiiBB) and/or three Inertial Measurement Units (IMUs) placed on the forearms and hip. Various sensor configurations are considered, including only WiiBB, only IMUs, combinations of WiiBB with the IMU at the hip, and combinations of WiiBB with the 3 IMUs.</div><div>The accuracy of the latent space representation is compared with two common supervised classification models, which are the Convolutional Neural Network (CNN) and the neural network called CNNLSTM, which is composed of convolution layers followed by recurrent layers. The approach was demonstrated for two different sets of exercises consisting of upper and lower body exercises collected with 19 participants.</div><div>The results show that the latent space representation of the AAE achieves a strong classification accuracy performance while also serving as a visualization tool. This study is an initial demonstration of the potential of integrating WiiBB and IMU sensors for comprehensive activity recognition for upper and lower body movement analysis.</div></div>","PeriodicalId":37151,"journal":{"name":"Smart Health","volume":"35 ","pages":"Article 100537"},"PeriodicalIF":0.0,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143129614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Novel EEG feature selection based on hellinger distance for epileptic seizure detection

Smart Health Pub Date : 2025-01-01 DOI: 10.1016/j.smhl.2024.100536

Muhammed Sadiq , Mustafa Noaman Kadhim , Dhiah Al-Shammary , Mariofanna Milanova

{"title":"Novel EEG feature selection based on hellinger distance for epileptic seizure detection","authors":"Muhammed Sadiq , Mustafa Noaman Kadhim , Dhiah Al-Shammary , Mariofanna Milanova","doi":"10.1016/j.smhl.2024.100536","DOIUrl":"10.1016/j.smhl.2024.100536","url":null,"abstract":"<div><div>This study introduces a novel feature selection method based on Hellinger distance and particle swarm optimization (PSO) for reducing the dimensionality of features in electroencephalogram (EEG) signals and improving epileptic seizure detection accuracy. In the first phase, the Hellinger distance is used as a filter to remove redundant and irrelevant features by calculating the similarity between blocks within the feature, thus reducing the search space for the subsequent second phase. In the second phase, PSO searches the reduced feature space to select the best subset. Recognizing that both classification accuracy and dimensionality play crucial roles in the performance of feature subsets, PSO searches various sets of features (ranging from 410 to 2867 in EEG signals) derived from the first stage using Hellinger distance, rather than searching through the full set of 4047 features, to select the optimal subset. The proposed Hellinger-PSO approach demonstrates significant improvements in classification accuracy across multiple models. Specifically, Logistic Regression (LR) improved from 91% to 95% (4% improvement), Decision Tree (DT) from 95% to 97% (2% improvement), Naive Bayes (NB) from 94% to 99% (5% improvement), and Random Forest (RF) from 96% to 98% (2% improvement) on the Bonn dataset. Additionally, the method reduces dimensionality while maintaining high classification performance. The results validate the efficacy of the Hellinger-PSO technique, which enhances both the accuracy and efficiency of epileptic seizure detection. This approach has the potential to improve diagnostic accuracy in medical settings, aiding in better patient care and more effective clinical decision-making.</div></div>","PeriodicalId":37151,"journal":{"name":"Smart Health","volume":"35 ","pages":"Article 100536"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143129218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Explainable screening of oral cancer via deep learning and case-based reasoning

Smart Health Pub Date : 2025-01-01 DOI: 10.1016/j.smhl.2024.100538

Mario G.C.A. Cimino , Giuseppina Campisi , Federico A. Galatolo , Paolo Neri , Pietro Tozzo , Marco Parola , Gaetano La Mantia , Olga Di Fede

{"title":"Explainable screening of oral cancer via deep learning and case-based reasoning","authors":"Mario G.C.A. Cimino , Giuseppina Campisi , Federico A. Galatolo , Paolo Neri , Pietro Tozzo , Marco Parola , Gaetano La Mantia , Olga Di Fede","doi":"10.1016/j.smhl.2024.100538","DOIUrl":"10.1016/j.smhl.2024.100538","url":null,"abstract":"<div><div>Oral Squamous Cell Carcinoma is characterized by significant mortality and morbidity. Dental professionals can play an important role in its early detection, thanks to the availability of embedded smart cameras for oral photos and remote screening supported by Deep Learning (DL). Despite the promising results of DL for automated detection and classification of oral lesions, its effectiveness is based on a clearly defined protocol, on the explainability of results, and on periodic cases collection. This paper proposes a novel method, combining DL and Case-Based Reasoning (CBR), to allow the post-hoc explanation of the system answer. The method uses explainability tools organized in a protocol defined in the Business Process Model and Notation (BPMN) to allow its experimental validation. A redesign of the Faster-R-CNN Feature Pyramid Networks (FPN) + DL architecture is also proposed for lesions detection and classification, fine-tuned on 160 cases belonging to three classes of oral ulcers. The DL system achieves state-of-the-art performance, i.e., 83% detection and 92% classification rate (98% for neoplastic vs. non-neoplastic binary classification). A preliminary experimentation of the protocol involved both resident and specialized doctors over selected difficult cases. The system and cases have been publicly released to foster collaboration between research centers.</div></div>","PeriodicalId":37151,"journal":{"name":"Smart Health","volume":"35 ","pages":"Article 100538"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143129615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel convolutional interpretability model for pixel-level interpretation of medical image classification through fusion of machine learning and fuzzy logic

Smart Health Pub Date : 2024-12-21 DOI: 10.1016/j.smhl.2024.100535

Mohammad Ennab, Hamid Mcheick

{"title":"A novel convolutional interpretability model for pixel-level interpretation of medical image classification through fusion of machine learning and fuzzy logic","authors":"Mohammad Ennab, Hamid Mcheick","doi":"10.1016/j.smhl.2024.100535","DOIUrl":"10.1016/j.smhl.2024.100535","url":null,"abstract":"<div><div>Artificial intelligence (AI) models for medical image analysis have achieved high diagnostic performance, but they often lack interpretability, limiting their clinical adoption. Existing methods can explain predictions at the image level, but they cannot provide pixel-level insights. This study proposes a novel fusion of machine learning and fuzzy logic to develop an interpretable model that can precisely identify discriminative image regions driving diagnostic decisions and generate heatmap visualization. The model is trained and evaluated on a dataset of CT scans containing healthy and diseased organ images. Quantitative features are extracted across pixels and normalized into representation matrices using a machine learning model. Subsequently, the contribution of each detected lesion to the overall prediction is quantified using fuzzy logic. Organ segment weighted averages are computed to identify significant lesions. The model explains application of AI in medical imaging with an unprecedented level of detail. It can explain fine-grained image areas that have the greatest influence on diagnostic outcomes by mapping raw image pixels to fuzzy membership concepts. Lesions are found with effect sizes and statistical significance (p < 0.05).</div><div>Our model outperforms three existing methods in terms of interpretability and diagnostic accuracy by 10–15%, while maintaining computational efficiency. By disclosing crucial image evidence that supports AI decisions, this interpretable model improves transparency and clinician trust. Ethical implications of integrating AI in clinical settings are discussed, and future research directions are outlined. This study significantly advances the development of safe and interpretable AI for enhancing patient care through imaging analytics.</div></div>","PeriodicalId":37151,"journal":{"name":"Smart Health","volume":"35 ","pages":"Article 100535"},"PeriodicalIF":0.0,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143129217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel guidance framework for nasal rapid antigen tests with improved swab keypoint detection

Smart Health Pub Date : 2024-12-06 DOI: 10.1016/j.smhl.2024.100534

Matthias Tschöpe, Dennis Schneider, Sungho Suh, Paul Lukowicz

{"title":"A novel guidance framework for nasal rapid antigen tests with improved swab keypoint detection","authors":"Matthias Tschöpe, Dennis Schneider, Sungho Suh, Paul Lukowicz","doi":"10.1016/j.smhl.2024.100534","DOIUrl":"10.1016/j.smhl.2024.100534","url":null,"abstract":"<div><div>The global impact of the COVID-19 pandemic has placed an unprecedented burden on healthcare systems. In this paper, we present a novel deep learning-based framework to guide individuals in performing nasal antigen rapid tests, with a particular focus on improving swab keypoint detection. Our system provides real-time feedback to participants on the correct execution of the test and may issue a certificate upon successful completion. While initially developed for COVID-19 antigen rapid tests, our versatile framework extends its applicability to various nasal screening tests, eliminating the need for specific information about the liquid solvent. To implement and evaluate our framework, we curated a comprehensive dataset with rapid test components and trained an object detection model to identify the position and size of all objects in each video frame. Addressing the challenge of swab depth classification, we propose a novel approach to locate and classify crucial swab points by a self-defined decision tree for depth assessment within the nasal cavity. The robustness of the proposed framework is validated with COVID-19 antigen rapid tests from various manufacturers. Experimental results demonstrate the remarkable performance of the framework in classifying the nasal placement of the swab, achieving an <span><math><msub><mrow><mi>F</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>-Score of 89.78%. Additionally, our framework attains an <span><math><msub><mrow><mi>F</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>-Score of 99.37% in classifying final test results on the test device.</div></div>","PeriodicalId":37151,"journal":{"name":"Smart Health","volume":"35 ","pages":"Article 100534"},"PeriodicalIF":0.0,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143129216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-driven assessment of the effectiveness of non-pharmaceutical interventions on Covid spread mitigation in Italy

Smart Health Pub Date : 2024-12-05 DOI: 10.1016/j.smhl.2024.100524

Divya Pragna Mulla , Mario Alessandro Bochicchio , Antonella Longo

{"title":"Data-driven assessment of the effectiveness of non-pharmaceutical interventions on Covid spread mitigation in Italy","authors":"Divya Pragna Mulla , Mario Alessandro Bochicchio , Antonella Longo","doi":"10.1016/j.smhl.2024.100524","DOIUrl":"10.1016/j.smhl.2024.100524","url":null,"abstract":"<div><div>To mitigate the impact of pandemics such as COVID-19, governments can implement various Non-Pharmaceutical Interventions (NPIs), ranging from the use of personal protective equipment to social distancing measures. While it has been demonstrated that NPIs can be effective over time, the assessment of their efficacy and the estimation of their cost-benefit ratio are still debated issues. For COVID-19, several authors have used case confirmation as a key parameter to assess the efficacy of NPIs. In this paper, we compare the efficacy of this parameter to that of the death rate, hospitalizations, and intensive care unit cases, in conjunction with human mobility indicators, in evaluating the effectiveness of NPIs. Our research uses data on daily COVID-19 cases and deaths, intensive care unit cases, hospitalizations, Google Mobility Reports, and NPI data from all Italian regions from March 2020 to May 2022. The evaluation method is based on the approach proposed by Wang et al., in 2020 to assess the impact of NPI efficacy and understand the effect of other parameters. Our results indicate that, when combined with human mobility indicators, the mortality rate and the number of intensive care units perform better than the number of cases in determining the efficacy of NPIs. These findings can assist policymakers in developing the best data-driven methods for dealing with confinement problems and planning for future outbreaks.</div></div>","PeriodicalId":37151,"journal":{"name":"Smart Health","volume":"35 ","pages":"Article 100524"},"PeriodicalIF":0.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143129220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel rule-based expert system for early diagnosis of bipolar and Major Depressive Disorder

Smart Health Pub Date : 2024-12-04 DOI: 10.1016/j.smhl.2024.100525

Mohammad Hossein Zolfagharnasab , Siavash Damari , Madjid Soltani , Artie Ng , Hengameh Karbalaeipour , Amin Haghdadi , Masood Hamed Saghayan , Farzam Matinfar

{"title":"A novel rule-based expert system for early diagnosis of bipolar and Major Depressive Disorder","authors":"Mohammad Hossein Zolfagharnasab , Siavash Damari , Madjid Soltani , Artie Ng , Hengameh Karbalaeipour , Amin Haghdadi , Masood Hamed Saghayan , Farzam Matinfar","doi":"10.1016/j.smhl.2024.100525","DOIUrl":"10.1016/j.smhl.2024.100525","url":null,"abstract":"<div><div>A confident and timely diagnosis of mental illnesses is one of the primary challenges practitioners repeatedly encounter when they start treating new patients. However, diagnosing can quickly become problematic as the subjects expose comparative symptoms among mental illnesses. Due to influencing a broad populace among mental ailments, an adjusted differentiation between Major Depressive Disorder, Mania Bipolar Disorder, Depressive Bipolar Disorder, and ordinary individuals with mild symptoms is one of the critical subjects for community health. This study responded to the described problem by proposing a novel rule-based Expert System, which evaluates the impact of disorder symptoms on the Certainty Factor concerning each mental status. The semantic rules are developed based on the recommendation of experts, and the implementation is carried out using Prolog and <em>C#</em> languages. Furthermore, an easy-to-use user interface is considered to facilitate the system workflow. The consistency of the developed framework is established by performing rigorous tests by expert psychiatrists as well as 120 clinical samples collected from private samples. Based on the results, the current model classifies mental disorder cases with a success rate of 93.33% using only the 17 symptoms specified in the ontology model. Furthermore, a questionnaire that measures user satisfaction after the test also achieves a mean score of 3.56 out of 4, which indicates a high degree of user acceptance. As a result, it is concluded that the current framework is a reliable tool for achieving a solid diagnosis in a shorter period.</div></div>","PeriodicalId":37151,"journal":{"name":"Smart Health","volume":"35 ","pages":"Article 100525"},"PeriodicalIF":0.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143129215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Differences in gait parameters between supervised laboratory and unsupervised daily assessments of healthy adults measured with an in-shoe motion sensor system 用鞋内运动传感器系统测量有监督的实验室和无监督的健康成人每日评估之间的步态参数差异

Smart Health Pub Date : 2024-11-26 DOI: 10.1016/j.smhl.2024.100526

Hiroki Shimizu , Takanobu Saito , Shione Kashiyama , Shinichi Kawamoto , Saori Morino , Momoko Nagai-Tanima , Tomoki Aoyama

{"title":"Differences in gait parameters between supervised laboratory and unsupervised daily assessments of healthy adults measured with an in-shoe motion sensor system","authors":"Hiroki Shimizu , Takanobu Saito , Shione Kashiyama , Shinichi Kawamoto , Saori Morino , Momoko Nagai-Tanima , Tomoki Aoyama","doi":"10.1016/j.smhl.2024.100526","DOIUrl":"10.1016/j.smhl.2024.100526","url":null,"abstract":"<div><div>This cross-sectional study compared the gait parameters between supervised laboratory and unsupervised daily life assessments in healthy adults. Gait was evaluated in 24 healthy young adults during 72 h of daily life and a 6-min laboratory gait at a comfortable speed. An in-shoe motion sensor system recorded gait data every 2 min, automatically detected stable gait segments by identifying repetitive movement patterns, and calculated the average of three consecutive valid gait cycles during each measurement period. Significant differences were found in walking speed (stride length divided by stride time; laboratory: 4.60 km/h vs. daily-life: 4.38 km/h), maximum (peak) dorsiflexion angle (laboratory: 29.71° vs. daily-life: 26.65°), maximum (peak) plantar flexion angle (laboratory: 74.54° vs. daily-life: 71.91°), roll angle of heel contact (laboratory: 7.46° vs. daily-life: 6.70°), maximum speed during the swing phase (laboratory: 14.49 km/h vs. daily-life: 12.68 km/h), circumduction (lateral displacement during the swing phase; laboratory: 2.68 cm vs. daily-life: 3.69 cm), toe-in/out angle (laboratory: 13.87° vs. daily-life: 15.32°), stance time (laboratory: 0.62 s vs. daily-life: 0.65 s), and pushing time (time between heel leaving and toe leaving the ground; laboratory: 0.20 s vs. daily-life: 0.21 s). The innovative aspect of this study is the comprehensive evaluation of foot-related gait parameters in real-world environments using an in-shoe motion sensor system. This approach provides ecologically valid insights into gait dynamics during daily activities, emphasizing the importance of real-world assessments for accurately evaluating gait performance and predicting adverse events such as falls. Keywords: Gait, Foot, Laboratory, Daily Life, Unsupervised Assessment, Shoe Motion Sensors.</div></div>","PeriodicalId":37151,"journal":{"name":"Smart Health","volume":"35 ","pages":"Article 100526"},"PeriodicalIF":0.0,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142757705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Gamifying the exploration of home mobility barriers for individuals with limited mobility: Scoping review 游戏化探索行动不便者的家庭行动障碍：范围界定审查

Smart Health Pub Date : 2024-11-09 DOI: 10.1016/j.smhl.2024.100523

Luis Villarreal Laguna , Carla Sílvia Fernandes , Joana Campos , Marta Campos Ferreira

{"title":"Gamifying the exploration of home mobility barriers for individuals with limited mobility: Scoping review","authors":"Luis Villarreal Laguna , Carla Sílvia Fernandes , Joana Campos , Marta Campos Ferreira","doi":"10.1016/j.smhl.2024.100523","DOIUrl":"10.1016/j.smhl.2024.100523","url":null,"abstract":"<div><div>As advancements in the health sector continue to improve, people are living longer and increasingly aging in place. However, aging is often accompanied by disabilities and mobility issues. Whether these issues develop gradually or suddenly, many homes are not equipped to accommodate such changes, resulting in significant mobility barriers. This document presents a systematic review focusing on three key areas: “Home Barriers and Modification”, “Accessibilities and Disabilities”, and “Gamification and Assistive Technologies”. The aim is to synthesize existing knowledge and explore the interconnections among these topics. The primary objective of this review is to examine how gamification can be utilized to identify barriers within the homes of individuals with disabilities. Despite numerous advancements and available technologies, the review reveals a paucity of research on the application of gamification in this context, highlighting a promising area for future investigation. Additionally, the review underscores the benefits of home modifications to enhance accessibility, emphasizing the potential for significant improvements in the quality of life for individuals with disabilities.</div></div>","PeriodicalId":37151,"journal":{"name":"Smart Health","volume":"34 ","pages":"Article 100523"},"PeriodicalIF":0.0,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142652725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving health awareness with real-time monitoring through a three-dimensional visualized digital health avatar 通过三维可视化数字健康头像进行实时监测，提高健康意识

Smart Health Pub Date : 2024-11-06 DOI: 10.1016/j.smhl.2024.100522

Chaturapron Chokphukhiao , Pattrawan Pattaranit , Wonn Shweyi Thet Tun , Sakaowrat Masa , Rattikorn Leemananil , Nuttaphorn Natteerapong , Jutarop Phetcharaburanin , Sophon Boonlue , Khamron Sunat , Rina Patramanon

{"title":"Improving health awareness with real-time monitoring through a three-dimensional visualized digital health avatar","authors":"Chaturapron Chokphukhiao , Pattrawan Pattaranit , Wonn Shweyi Thet Tun , Sakaowrat Masa , Rattikorn Leemananil , Nuttaphorn Natteerapong , Jutarop Phetcharaburanin , Sophon Boonlue , Khamron Sunat , Rina Patramanon","doi":"10.1016/j.smhl.2024.100522","DOIUrl":"10.1016/j.smhl.2024.100522","url":null,"abstract":"<div><h3>Introduction</h3><div>The use of modern technologies has become crucial for enhancing people's awareness of health problems. By early health risk detection, there will be better treatment outcomes, the severity of illness will decrease, and costs for treatment will also reduce. Performing routine checkups could help patients feel less anxious about their health in the future. In this study, the innovation of “Digital Health Avatar” enables users to monitor physical changes, raise awareness of medical conditions, and encourage healthy behaviors by visualizing health status as a 3D figure.</div></div><div><h3>Methods</h3><div>Health data were collected using medical devices like blood test strips, body composition meters, and automatic blood pressure monitors. API technology and cloud computing systems were used to process these collected data and produced a three-dimensional avatar that indicated the user's health status. User satisfaction survey on using the health avatar system was assessed through a survey of 61 participants.</div></div><div><h3>Results</h3><div>Health avatar system successfully generate the data and display the measurement results on the health report page of the system. Users can easily check and record their physiological conditions through the avatar. Moreover, users showed satisfaction on the use of the health avatar system and its effectiveness in health check-ups in the survey.</div></div><div><h3>Conclusions</h3><div>The ‘Digital Health Avatar’ has the potential to significantly promote individual well-being and health awareness. Its development will be improved by user feedback and continued study, ensuring it becomes an efficient tool for promoting healthier lifestyles.</div></div>","PeriodicalId":37151,"journal":{"name":"Smart Health","volume":"34 ","pages":"Article 100522"},"PeriodicalIF":0.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142704237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0