Augmented Human Research最新文献_第3页

A Comprehensive Study on Relative Distances of Hand Landmarks Approach for American Sign Language Gesture 美国手语手势的手部地标相对距离方法综合研究

Augmented Human Research Pub Date : 2024-02-09 DOI: 10.1007/s41133-024-00064-w

Shail Shah, Jaynil Vaidya, Kishan Pipariya, Manan Shah

引用次数: 0

A Comprehensive Study on Relative Distances of Hand Landmarks Approach for American Sign Language Gesture 美国手语手势的手部地标相对距离方法综合研究

Augmented Human Research Pub Date : 2024-02-09 DOI: 10.1007/s41133-024-00064-w

Shail Shah, Jaynil Vaidya, Kishan Pipariya, Manan Shah

引用次数: 0

Hybrid WCA–PSO Optimized Ensemble Extreme Learning Machine and Wavelet Transform for Detection and Classification of Epileptic Seizure from EEG Signals 混合 WCA-PSO 优化集合极限学习机和小波变换用于从脑电图信号中检测和分类癫痫发作

Augmented Human Research Pub Date : 2023-12-11 DOI: 10.1007/s41133-023-00059-z

Sreelekha Panda, Satyasis Mishra, Mihir Narayana Mohanty

{"title":"Hybrid WCA–PSO Optimized Ensemble Extreme Learning Machine and Wavelet Transform for Detection and Classification of Epileptic Seizure from EEG Signals","authors":"Sreelekha Panda, Satyasis Mishra, Mihir Narayana Mohanty","doi":"10.1007/s41133-023-00059-z","DOIUrl":"10.1007/s41133-023-00059-z","url":null,"abstract":"<div><p>Epilepsy seizures are sudden, chaotic neurological functions. The complexity of the brain is revealed via electroencephalography (EEG). Visual examination-based EEG signal analysis is time-consuming, expensive, and difficult. Epilepsy-related mortality is a serious concern. In the diagnostic procedure, computer-assisted diagnosis approaches for precise and automatic detection and classification of epileptic seizures play a crucial role. Due to the classifier's high processing time requirements caused by its mathematical complexity and computational time, we propose a hybrid water cycle algorithm (WCA)–particle swarm optimization (PSO) optimized ensemble extreme learning machine (EELM) classification of seizures to improve the classification performance of the classifier. Firstly, we use feature extraction by utilizing the wavelet transform. The extracted features are aligned as input to the WCA–PSO–EELM for classification. The particle swarm optimization (PSO) algorithm is used to initialize the optimization variables of a WCA algorithm, and the WCA algorithm is used to optimize the input weight of the ELM (i.e., the WCA–PSO–ELM (WPELM)) for classification of seizure and non-seizure EEG signals. University of Bonn database is used for the experiment. The performance measures sensitivity, specificity, and accuracy are considered and achieved 98.78%, 99.23%, and 99.12%, that is, higher than those of other conventional algorithms. To validate the robustness of the WCA–PSO algorithm, three benchmark functions are considered for optimization. The comparison results are presented to visualize the uniqueness of the proposed WCA–PSO–EELM classifier. From the comparison results, it was observed that the proposed WCA–PSO–EELM model outperformed in classifying the seizure and non-seizure EEG signals.</p></div>","PeriodicalId":100147,"journal":{"name":"Augmented Human Research","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138627672","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

Improvement in Motor Skills, Attention, and Working Memory in Mild Cognitive Impairment and Alzheimer’s Disease Patients Using COSMA Cognitive App 使用 COSMA 认知应用程序提高轻度认知障碍和阿尔茨海默病患者的运动技能、注意力和工作记忆能力

Augmented Human Research Pub Date : 2023-12-11 DOI: 10.1007/s41133-023-00061-5

Aikaterini Christogianni, Kartheka Bojan, Elizabeta Mukaetova-Ladinska, V. T. Sriramm, G. Murthy, Gopukumar Kumarpillai

{"title":"Improvement in Motor Skills, Attention, and Working Memory in Mild Cognitive Impairment and Alzheimer’s Disease Patients Using COSMA Cognitive App","authors":"Aikaterini Christogianni, Kartheka Bojan, Elizabeta Mukaetova-Ladinska, V. T. Sriramm, G. Murthy, Gopukumar Kumarpillai","doi":"10.1007/s41133-023-00061-5","DOIUrl":"10.1007/s41133-023-00061-5","url":null,"abstract":"<div><p>There are a rapid growth of adults with cognitive impairments and an increasing need for cognitive stimulation and rehabilitation to delay cognitive deterioration. COSMA, a cognitive gaming app, was developed to assist cognitive stimulation in people with cognitive decline and dementia. Therefore, the study was conducted to investigate the effectiveness of COSMA in people with mild cognitive impairment (MCI) and early Alzheimer’s disease (AD). The study involved a treatment group who played COSMA at home and during laboratory visits for 28 days and a control group who played only during laboratory visits. Each group was measured on days 1–14–28, where recordings of playing COSMA and Cambridge Neuropsychological Test Automated Battery (CANTAB) tests were taken. The results showed that the MCI treatment group improved sensorimotor skills in 14 days, sustained attention, spatial planning, working and visual memory, and learning in 28 days. The AD treatment group improved in sustained attention in 14 and 28 days and showed a lower cognitive decline in working memory compared to the AD control group in 28 days. Both control groups did not show any level of improvement. Even though the progression of the MCI was faster than that of the early AD, the study showed inspired results of cognitive improvement in both groups. COSMA showed evidence that cognitive stimulation and rehabilitation are possible in MCI and AD and that it is an effective and efficient non-pharmacological therapeutic tool in these groups of patients.</p></div>","PeriodicalId":100147,"journal":{"name":"Augmented Human Research","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138610880","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

ECG Data Compression Using of Empirical Wavelet Transform for Telemedicine and e-Healthcare Systems 利用经验小波变换压缩心电图数据，用于远程医疗和电子保健系统

Augmented Human Research Pub Date : 2023-12-09 DOI: 10.1007/s41133-023-00063-3

Agya Ram Verma, Shanti Chandra, G. K. Singh, Yatendra Kumar, Manoj Kumar Panda, Suresh Kumar Panda

{"title":"ECG Data Compression Using of Empirical Wavelet Transform for Telemedicine and e-Healthcare Systems","authors":"Agya Ram Verma, Shanti Chandra, G. K. Singh, Yatendra Kumar, Manoj Kumar Panda, Suresh Kumar Panda","doi":"10.1007/s41133-023-00063-3","DOIUrl":"10.1007/s41133-023-00063-3","url":null,"abstract":"<div><p>In this article, a highly adaptable method the empirical wavelet transform (EWT) is utilized to compress electrocardiogram (ECG) data. EWT and run-length encoding (RLE)-based technique is used for data compression of ECG rhythms. EWT is chosen because it is highly adaptable and can decompose a non-stationary signal into different frequency modes efficiently. The modified RLE is used to acquire the high reduction performance. The projected method is tested with MIT-BIH arrhythmia database and experiments are carried out in MATLAB R2016b. Performance of the proposed algorithm is evaluated in terms of compression ratio (CR), percent root mean squire difference (PRD), signal-to-noise ratio (SNR), retained energy (RE) and quality score (QS). Result shows a high CR (31%), low PRD (0.0750) and high QS (414). Comparative analysis of the performance of projected technique with several existing techniques is also done, which shows that the proposed technique is superior in terms of PRD and CR. WT is also used to detect the R-peaks (location and amplitude) using amplitude thresholding. The program took 4.452793 s to run.</p></div>","PeriodicalId":100147,"journal":{"name":"Augmented Human Research","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138609015","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

Timely Prediction of Diabetes by Means of Machine Learning Practices 通过机器学习实践及时预测糖尿病

Augmented Human Research Pub Date : 2023-12-09 DOI: 10.1007/s41133-023-00062-4

Rajan Prasad Tripathi, Manvinder Sharma, Anuj Kumar Gupta, Digvijay Pandey, Binay Kumar Pandey, Aakifa Shahul, A. S. Hovan George

引用次数: 0

Machine Vision for Device Tracking in a Smart Manufacturing Environment Based on Augmented Reality 基于增强现实技术的智能制造环境中设备跟踪机器视觉技术

Augmented Human Research Pub Date : 2023-12-09 DOI: 10.1007/s41133-023-00060-6

Tshepo Godfrey Kukuni, Ben Kotze, William Hurst

{"title":"Machine Vision for Device Tracking in a Smart Manufacturing Environment Based on Augmented Reality","authors":"Tshepo Godfrey Kukuni, Ben Kotze, William Hurst","doi":"10.1007/s41133-023-00060-6","DOIUrl":"10.1007/s41133-023-00060-6","url":null,"abstract":"<div><p>In a controlled network environment, such as the smart indoor manufacturing environment, the device identification and detection of components is challenging without prior knowledge of the design and implementation process. Thus, the concept of device identification for diagnosis and equipment maintenance by means of markerless augmented reality (AR) merits investigation. AR, when coupled with machine vision, caters for obtaining real-time device information regarding the position and features of the robotic elements within indoor manufacturing plants. Thus, this article proposes an efficient machine vision model to detect and identify devices based within a manufacturing plant, with the aid of AR for extending the device operational details. This offers an alternative solution in the absence of user built-in maps for the calculation of device positions based on uncertainties of the exact locations. To achieve this, a two-part validation is conducted involving (1) device recognition based on position and (2) Data integration to A Supervisory Control and Data Acquisition (SCADA) model developed in National Instruments Labview. The findings demonstrate that the AR application can detect devices within the manufacturing plant without the need for alteration. The results also indicate that the application can be integrated into a SCADA model without the need to alter the application, provided that the array index is the same. Only when the array index differs are alterations necessary for utilising the AR application.</p></div>","PeriodicalId":100147,"journal":{"name":"Augmented Human Research","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138612217","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

Computing Run-out Decisions Using Object Detection and Support Vector Machine Algorithm 使用目标检测和支持向量机算法计算运行决策

Augmented Human Research Pub Date : 2022-11-22 DOI: 10.1007/s41133-022-00058-6

Mihir Maulik Palkhiwala, Dev Punitkumar Mehta

引用次数: 0

Harnessing Augmented Reality for Increasing the Awareness of Food Waste Amongst Dutch Consumers 利用增强现实技术提高荷兰消费者对食物浪费的认识

Augmented Human Research Pub Date : 2022-07-01 DOI: 10.1007/s41133-022-00057-7

Dolf Honee, William Hurst, Antonius Johannus Luttikhold

引用次数: 1

Covid-19 Travel Planner Mobile Application Design with Lean Product Process Framework 基于精益产品流程框架的Covid-19 Travel Planner移动应用程序设计

Augmented Human Research Pub Date : 2022-02-21 DOI: 10.1007/s41133-022-00056-8

Nicha Tavichaiyuth, Nutchanant Foojinphan, Pantira Leelahakorn, Supparanun Kanchanakul, Thitirat Siriborvornratanakul

{"title":"Covid-19 Travel Planner Mobile Application Design with Lean Product Process Framework","authors":"Nicha Tavichaiyuth, Nutchanant Foojinphan, Pantira Leelahakorn, Supparanun Kanchanakul, Thitirat Siriborvornratanakul","doi":"10.1007/s41133-022-00056-8","DOIUrl":"10.1007/s41133-022-00056-8","url":null,"abstract":"<div><p>Our travel planner mobile application was designed to fit the traveling post to COVID-19 outbreak following the lean product process principle. We intend to develop a travel application that brings back the joy of traveling. The objective of this study is to design a travel planner application that satisfies the user’s needs. In the first stage of the lean product process, we first determine our target customer by interviewing eight millennials. Once the persona was clarified, we explored the problem space, identified underserved customer needs, and prioritized those needs. The features with high importance but were underserved are COVID-19 guideline information, place recommendation, route optimization, and price comparison, which we believe could offer excellent opportunities to create customer value. The value proposition and feature set were also identified before creating the first MVP prototype. The detailed navigation flow and interactive MVP prototype were created and then tested with users. As a result, in the last iteration of usability testing, the value rating was increased from 6 to 9, and the ease of use rating was increased from 6 to 8 compared to the first rounds.</p></div>","PeriodicalId":100147,"journal":{"name":"Augmented Human Research","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50040471","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