2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech)最新文献

Design of Respiratory Assist Devices: Critical Review of Global Response to COVID-19 Crisis 呼吸辅助装置的设计:全球应对COVID-19危机的关键回顾

2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech) Pub Date : 2020-08-01 DOI: 10.1109/iCareTech49914.2020.00034

Y. Kadah

引用次数: 0

IoT-Based Healthcare and Monitoring Systems for the Elderly: A Literature Survey Study 基于物联网的老年人医疗和监测系统:文献调查研究

2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech) Pub Date : 2020-08-01 DOI: 10.1109/iCareTech49914.2020.00025

Mohammed Elkahlout, Mohammed M. Abu-Saqer, A. F. Aldaour, Ahmed Issa, M. Debeljak

{"title":"IoT-Based Healthcare and Monitoring Systems for the Elderly: A Literature Survey Study","authors":"Mohammed Elkahlout, Mohammed M. Abu-Saqer, A. F. Aldaour, Ahmed Issa, M. Debeljak","doi":"10.1109/iCareTech49914.2020.00025","DOIUrl":"https://doi.org/10.1109/iCareTech49914.2020.00025","url":null,"abstract":"The world is turning to Internet of Things (IoT) technologies to remotely monitor and control things faster and more accurately. IoT can be very beneficial in the medical and healthcare fields as it enables remote follow-up of chronic illnesses, monitoring of vital signs, emergency detection, diagnosis and prognosis of patient status or illnesses. IoT becomes evidently useful in the case of elderly healthcare and monitoring, which, in many cases, are tasks requiring full attendance of a caregiver or medical staff. The aim of this survey study is to shed light on the importance and classification of IoT-based elderly healthcare systems. The paper includes a review of research studies that report developments and utilization of IoT-based healthcare systems of elderly. The paper also includes a description of basic IoT-based healthcare systems architecture and ways of its implementation, including wearables, at hospitals and at home. The paper concludes with a presentation of the security challenges imposed by the nature of IoT systems implementation that require remote access to personal data and data storage. It is recommended from the surveyed studies that IoT will continue to expand as a technology trend that allows for development of inexpensive, reliable and secure elderly healthcare and monitoring systems.","PeriodicalId":164473,"journal":{"name":"2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115470639","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: 5

Scheduling of Elective Surgery in Al-Shifa Hospital Using an Integrated AHP-LP Approach 利用综合AHP-LP方法安排Al-Shifa医院的择期手术

2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech) Pub Date : 2020-08-01 DOI: 10.1109/iCareTech49914.2020.00015

S. Abdelall, Amal Atallah, Fatma Elghazalli, H. Daoud, S. Agha

{"title":"Scheduling of Elective Surgery in Al-Shifa Hospital Using an Integrated AHP-LP Approach","authors":"S. Abdelall, Amal Atallah, Fatma Elghazalli, H. Daoud, S. Agha","doi":"10.1109/iCareTech49914.2020.00015","DOIUrl":"https://doi.org/10.1109/iCareTech49914.2020.00015","url":null,"abstract":"Al-Shifa Medical Complex is the largest central hospital in Gaza Strip. Al-Shifa Hospital has sixteen surgery rooms, six of them are used for elective surgeries that include general and specialized surgeries. Approximately, 35 elective surgeries are booked per day, while on average, 27 elective surgeries are performed daily. The surgeries scheduling in Al- Shifa Hospital follows the First Come First Served (FCFS) rule, which means a patient who first comes is assigned the first available time slot. A quick analysis of the available data shows that only 8% of elective surgeries are performed as scheduled. This research aims to prioritize the patients surgery schedules based on their health status as represented by given criteria/sub-criteria and not only on FCFS bases. Criteria/sub-criteria were identified and a final list was obtained. Criteria included: disease severity, difficulty in performing daily activities, hospital readmissions, patient having other diseases, and the patient age. Analytic Hierarchy Process (AHP) tool was used to rank each criteria/sub-criteria. AHP findings show that disease severity, difficulty in performing daily activities are the most important criteria followed by hospital readmissions, patient having other diseases, and patient age respectively. A Linear Programing model (LP) is formulated to schedule surgeries for each department with an objective function of maximizing the number of surgeries of each department. As a result of LP analysis, it was observed that some of those patients whose surgeries were performed ahead of schedule based on FCFS have the highest priority. Further, some patients whose surgeries were behind schedule ranked lowest. Also the results show that the department whose patients have the highest priority is neurosurgery.","PeriodicalId":164473,"journal":{"name":"2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134211817","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

Vision-based Automatic Detection of Compensatory Postures of after-Stroke Patients During Upper-extremity Robot-assisted Rehabilitation: A Pilot Study in Reaching Movement 基于视觉的脑卒中患者上肢机器人辅助康复过程中代偿姿势的自动检测:伸手运动的初步研究

2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech) Pub Date : 2020-08-01 DOI: 10.1109/iCareTech49914.2020.00019

Yan Fu, Xiaoyi Wang, Zeqiang Zhu, Jie Tan, Yan Zhao, Yong Ding, Weiya Chen

{"title":"Vision-based Automatic Detection of Compensatory Postures of after-Stroke Patients During Upper-extremity Robot-assisted Rehabilitation: A Pilot Study in Reaching Movement","authors":"Yan Fu, Xiaoyi Wang, Zeqiang Zhu, Jie Tan, Yan Zhao, Yong Ding, Weiya Chen","doi":"10.1109/iCareTech49914.2020.00019","DOIUrl":"https://doi.org/10.1109/iCareTech49914.2020.00019","url":null,"abstract":"Objectives: Compensations are commonly employed by stroke patients during robot-assisted rehabilitation, leading to suboptimal recovery outcomes. This study investigated the feasibility of vision-based detection on compensatory postures in stroke patients by using kinematic data and machine learning algorithms.Methods: Ten stroke survivors did a scripted reaching movement using the affected side with an end-effector robot assistance while three dimensional(3D) trajectories of upper body joint positions were recorded based on a vision-based tracking system.Algorithms: A set of discriminating features which correlated with various compensatory postures were extracted based on the kinematic data. Two multi-label classifiers were trained to identify and categorize the postures of the participants.Results: The most obvious compensatory postures in the scripted reaching movement are forward trunk displacement and trunk rotation, followed by shoulder elevation, and less insufficient elbow extension. The two multi-label classifiers trained achieved a fair compensation detection performance: Multi-Label k-Nearest Neighbor (ML-KNN) classifier (Hamming loss: 0.16, Macro-average: 0.642, Micro-average: 0.85), Multi-Label Decision Tree (ML-DT) classifier (Hamming loss: 0.15, Macro-average: 0.654, Micro-average:0.85).Conclusions: It is feasible to realize automatic detection of compensatory postures during the upper-limb robot-assisted rehabilitation based on the low-cost vision system. It is expected to complement real time compensatory postures recognition of clinical faculty and be integrated into a rehabilitation robot system to reduce compensations in stroke patients.","PeriodicalId":164473,"journal":{"name":"2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130069880","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: 2

Emerging Technology Trends in Point-of-Care Diagnostics 即时诊断的新兴技术趋势

2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech) Pub Date : 2020-08-01 DOI: 10.1109/iCareTech49914.2020.00028

Cian Hughes, S. Sreenilayam, Yalda Afkham, D. Brabazon

引用次数: 0

Brain Tumor Classification Using Deep Learning 使用深度学习的脑肿瘤分类

2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech) Pub Date : 2020-08-01 DOI: 10.1109/iCareTech49914.2020.00032

A. Saleh, Rozana Sukaik, Samy S. Abu-Naser

引用次数: 2

Clinical Case Study: Total Reverse Shoulder Replacement-Major Features of Physiotherapy in Early and Late Postoperative Period 临床病例研究:全反向肩关节置换术-术后早期和晚期物理治疗的主要特点

2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech) Pub Date : 2020-08-01 DOI: 10.1109/iCareTech49914.2020.00018

A. Andreev, T. Sokolov, K. Panayotov

引用次数: 0

Tele-Occupational Therapy: Experience with Bulgarian Children During COVID-19 Pandemic 远程职业治疗:COVID-19大流行期间保加利亚儿童的经验

2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech) Pub Date : 2020-08-01 DOI: 10.1109/iCareTech49914.2020.00020

Petya Mincheva, Ruslana Anastasova

引用次数: 0

The Experience Behind The REHAROB Project – A New Robotic System For Simultaneous Rehabilitation Of Upper And Lower Human Limbs REHAROB项目背后的经验-一种同时康复上肢和下肢的新型机器人系统

2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech) Pub Date : 2020-08-01 DOI: 10.1109/iCareTech49914.2020.00010

D. Bratanov, P. Vitliemov

引用次数: 1

Chest Pathology Detection in X-Ray Scans Using Social Spider Optimization Algorithm with Generalization Deep Learning 基于泛化深度学习的社交蜘蛛优化算法在x射线扫描中的胸部病理检测

2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech) Pub Date : 2020-08-01 DOI: 10.1109/iCareTech49914.2020.00031

Haneen AlTalli, M. Alhanjouri

{"title":"Chest Pathology Detection in X-Ray Scans Using Social Spider Optimization Algorithm with Generalization Deep Learning","authors":"Haneen AlTalli, M. Alhanjouri","doi":"10.1109/iCareTech49914.2020.00031","DOIUrl":"https://doi.org/10.1109/iCareTech49914.2020.00031","url":null,"abstract":"Nowadays, medical diagnosis field using artificial intelligence is state of the art technology, which is growing and covering a lot of technical approaches to build pathology detection models. In our work, we used a new optimizer using Social Spider Optimization (SSO) algorithm with convolutional layer in deep neural network for chest X-ray pathology detection. SSO is one of the newest optimization algorithms. It is related to simulate the behavior of social spiders living in groups. Three main phases are used in this work to overcome the limited resources, the first phase is to build Convolutional Neural Network (CNN) with the benefits of transfer learning to reuse two blocks from VGG16 model (Visual Geometry Group), while the second one is to train CNN using gradient-based optimizer to extract feature vectors from the input images, and the third phase is to feed these vectors to two-fully connected layers and train it using SSO. These three phases reduce the number of trainable parameters, and get results that is much smaller and easy to handle network. We used SSO with deep neural network to achieve an accuracy of 89% and recall 98%, that leads to success of SSO optimizer to detect pathology of chest X-ray.","PeriodicalId":164473,"journal":{"name":"2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124684887","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: 3