2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)最新文献_第2页

Poster Abstract: A Wearable Diagnostic Assessment System for Attention Deficit Hyperactivity Disorder 摘要:一种可穿戴的注意力缺陷多动障碍诊断评估系统

2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) Pub Date : 2019-09-01 DOI: 10.1109/CHASE48038.2019.00012

Xinlong Jiang, Yunbing Xing, Teng Zhang, Wuliang Huang, Chenlong Gao, Yiqiang Chen

{"title":"Poster Abstract: A Wearable Diagnostic Assessment System for Attention Deficit Hyperactivity Disorder","authors":"Xinlong Jiang, Yunbing Xing, Teng Zhang, Wuliang Huang, Chenlong Gao, Yiqiang Chen","doi":"10.1109/CHASE48038.2019.00012","DOIUrl":"https://doi.org/10.1109/CHASE48038.2019.00012","url":null,"abstract":"Attention Deficit Hyperactivity Disorder (ADHD) is a mental disorder of the neurodevelopmental type. It is characterized by problems of paying attention, excessive activity, or difficulty controlling behavior which is not appropriate for a person’s age. Currently, as ADHD lacks of clear specificity, diagnosis of ADHD still mainly depends on doctors’ experiences and observation. Moreover, the monotonous environment of hospital may makes children feel nervous, which can lead to misdiagnosis. To cope with this problem, we design a contextualized and objective system to support auxiliary diagnosis of ADHD, which has eleven diagnostic scenarios designed according to the description of typical symptoms of ADHD in Diagnostic and Statistical Manual of Mental Disorders (DSM-V). During the testing, multi-source data are acquired, including physiological sensors’ data, motion sensors’ data and tasks related data. Now, Our system is still a primary prototype. In the next, we plan to deploy it in the hospital and collect more data, and research on the auxiliary diagnosis accuracy.","PeriodicalId":137790,"journal":{"name":"2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126583655","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: 1

Poster Abstract: A Machine Learning Approach to Identify High-Cost Elderly Renal Transplant Recipients 摘要:一种机器学习方法识别高成本老年肾移植受者

2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) Pub Date : 2019-09-01 DOI: 10.1109/CHASE48038.2019.00008

Rui Fu, P. Coyte

引用次数: 0

Poster Abstract: Detecting Kratom Intoxication in Wearable Biosensor Data 摘要:在可穿戴生物传感器数据中检测克拉通中毒

2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) Pub Date : 2019-09-01 DOI: 10.1109/CHASE48038.2019.00028

Joshua Rumbut, Darshan Singh, Hua Fang, Honggang Wang, Stephanie Carreiro, E. Boyer

引用次数: 6

An Edge-Assisted and Smart System for Real-Time Pain Monitoring 一种用于实时疼痛监测的边缘辅助智能系统

2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) Pub Date : 2019-09-01 DOI: 10.1109/CHASE48038.2019.00023

Emad Kasaeyan Naeini, Sina Shahhosseini, A. Subramanian, Tingjue Yin, A. Rahmani, N. Dutt

{"title":"An Edge-Assisted and Smart System for Real-Time Pain Monitoring","authors":"Emad Kasaeyan Naeini, Sina Shahhosseini, A. Subramanian, Tingjue Yin, A. Rahmani, N. Dutt","doi":"10.1109/CHASE48038.2019.00023","DOIUrl":"https://doi.org/10.1109/CHASE48038.2019.00023","url":null,"abstract":"In the healthcare sector, there is a strong demand for accurate objective pain assessment as a key for effective pain management. Real-time and accurate objective pain assessment help hospital staffs and caregivers decide the proper dosage of pain medication to be provided to a patient in a timely manner. The state-of-the-art automatic and objective pain assessment techniques in the literature can be classified into two main categories: physiological-based and behavioral-based. The first-class monitors the changes in patients' physiological data such as Electrocardiography (ECG), Electromyography (EMG), Photoplethysmography (PPG) to identify autonomic nervous system reactions to pain, while the second class utilizes behavioral reactions to pain such as techniques using computer vision-based techniques by extracting features from patients' head poses and facial expressions. Recent pain monitoring systems have become multi-modal meaning that they deploy a combination of both approaches to improve pain monitoring accuracy. Although such complex models are highly accurate in pain monitoring, they are more computationally intensive imposing feasibility limitations to implement them on wearable devices in terms of energy efficiency (battery life) as well as computation latency. A smart and self-aware system capable of adaptively making a decision at run-time in response to the changes in pain level and context can minimize energy consumption by dynamically offloading tasks to the gateway devices at the edge layer. For this reason, in this paper, a self-aware system is proposed for the continuous assessment of pain intensity at the edge layer. Using the BioVid heat pain dataset, our approach demonstrates a promising reduction in terms of energy consumption with a negligible accuracy loss compared with its non-adaptive counterpart.","PeriodicalId":137790,"journal":{"name":"2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125201841","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: 20

Poster Abstract: Analysis of Cyber-Security Vulnerabilities of Interconnected Medical Devices 摘要:互联医疗设备网络安全漏洞分析

2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) Pub Date : 2019-09-01 DOI: 10.1109/CHASE48038.2019.00017

Yanchen Xu, Daniel Tran, Yuan Tian, H. Alemzadeh

引用次数: 11

Poster Abstract: A Comprehensive Approach for Cough Type Detection 摘要:一种综合的咳嗽类型检测方法

2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) Pub Date : 2019-09-01 DOI: 10.1109/CHASE48038.2019.00013

Ebrahim Nemati, Md. Mahbubur Rahman, Viswam Nathan, K. Vatanparvar, Jilong Kuang

{"title":"Poster Abstract: A Comprehensive Approach for Cough Type Detection","authors":"Ebrahim Nemati, Md. Mahbubur Rahman, Viswam Nathan, K. Vatanparvar, Jilong Kuang","doi":"10.1109/CHASE48038.2019.00013","DOIUrl":"https://doi.org/10.1109/CHASE48038.2019.00013","url":null,"abstract":"Presence of sputum in pulmonary system is an important bio-marker, critical in determining the existence of many disease such as lung infection, pneumonia, cancer, etc. While there has been many reports of successful algorithms to automatically detect cough instances, there has been not much work in identifying the cough type, or equivalently detection of sputum presence. Cough type detection is traditionally done by physical examination through hearing patients coughs in a clinical visit which is subjective and costly. This work tries to provide an objective comprehensive approach for cough type detection using an extensive set of acoustic features applied to the recorded audio from a relatively large population of both healthy subjects and patient with various pulmonary diseases and healthy controls. A total number of 5971 coughs (5242 dry and 729 wet) were collected from 131 subjects using Smartphone. Annotation was done using a crowd-source platform. Classification sensitivity and specificity values of 86% and 84% was achieved respectively which is the highest in literature to the best of our knowledge.","PeriodicalId":137790,"journal":{"name":"2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129015888","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: 30

Poster Abstract: Augmented Reality Based Therapy System for Social Skill Deficits 摘要:基于增强现实的社交技能缺陷治疗系统

2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) Pub Date : 2019-09-01 DOI: 10.1109/CHASE48038.2019.00015

Kewei Sha, Zhandong Liu, J. Dempsey

引用次数: 1

[Title page iii] [标题页iii]

2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) Pub Date : 2019-09-01 DOI: 10.1109/chase48038.2019.00002

引用次数: 0

Poster Abstract: Unobtrusive Sleep Monitoring with Low-Cost Pressure Sensor Array 摘要:低成本压力传感器阵列的睡眠监测

2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) Pub Date : 2019-09-01 DOI: 10.1109/CHASE48038.2019.00014

Haoyan Liu, E. Sanchez, J. Parkerson, Alexander Nelson

引用次数: 0

Implementing Real-Time Clinical Decision Support Applications on OpenICE: A Case Study Using the National Early Warning System Algorithm 在OpenICE上实现实时临床决策支持应用:使用国家预警系统算法的案例研究

2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) Pub Date : 2019-09-01 DOI: 10.1109/CHASE48038.2019.00021

D. Arney, Yi Zhang, J. Goldman, Barbara Dumas

{"title":"Implementing Real-Time Clinical Decision Support Applications on OpenICE: A Case Study Using the National Early Warning System Algorithm","authors":"D. Arney, Yi Zhang, J. Goldman, Barbara Dumas","doi":"10.1109/CHASE48038.2019.00021","DOIUrl":"https://doi.org/10.1109/CHASE48038.2019.00021","url":null,"abstract":"This paper presents the design and implementation of a software application, called MEWS, that implements the Royal College of Physician’s National Early Warning (scoring) System on the OpenICE interoperable platform. The MEWS app, as a real-time clinical decision support (RT-CDS) application, does not require the use of an Electronic Health Record System to support its operation. Instead, it is able to receive patient vital sign measurements from any patient physiological monitoring device connected to OpenICE, irrespective of the device manufacturer. Based on the received vital signs, MEWS calculates an overall score indicating the monitored patient’s current status and is intended to direct clinicians to patients showing signs of deteriorating conditions and hence needing immediate intervention. The implementation and deployment of the MEWS app on OpenICE presents a preliminary step to understand the challenge of establishing (data) interface protocols to enable medical device interoperability generally, and for RT-CDS applications in particular, and to establish requirements for bridging the gap of current industrial standardization activities in addressing this challenge.","PeriodicalId":137790,"journal":{"name":"2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128956563","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: 1