Pub Date : 2012-12-13DOI: 10.1109/HealthCom.2012.6379408
Mostafa M. A. Mohamed, B. Far
One of the most important clinical examination tests is the blood test. In a clinical laboratory, counting different blood cells is important. Manual microscopic inspection is time-consuming and requires technical knowledge. Therefore, automatic medical diagnosis systems are required to help physicians to diagnose diseases in a fast and yet efficient way. Cell automatic classification has larger interest especially for clinics and laboratories; the most important step in automatic classification success is segmentation. This paper shows an efficient technique for automatic blood cell nuclei segmentation. This technique is relying on enhancing and filtering the gray scale image contrast. False objects are removed utilizing minimum segment size. 365 blood images were used to examine this segmentation technique. Quantitative analysis of the proposed segmentation technique on the blood image set gives 80.6% accuracy. In comparison to other techniques the proposed segmentation technique performance was found to be superior. The five normal white blood cells types were used for evaluation to compare isolated performance. Eosinophil was found to have the lowest segmentation accuracy which is 71.0% and Monocyte was the highest one with 85.9%. The blood images dataset and the source code are published on MATLAB file exchange website for comparison and re-production.
{"title":"An enhanced threshold based technique for white blood cells nuclei automatic segmentation","authors":"Mostafa M. A. Mohamed, B. Far","doi":"10.1109/HealthCom.2012.6379408","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379408","url":null,"abstract":"One of the most important clinical examination tests is the blood test. In a clinical laboratory, counting different blood cells is important. Manual microscopic inspection is time-consuming and requires technical knowledge. Therefore, automatic medical diagnosis systems are required to help physicians to diagnose diseases in a fast and yet efficient way. Cell automatic classification has larger interest especially for clinics and laboratories; the most important step in automatic classification success is segmentation. This paper shows an efficient technique for automatic blood cell nuclei segmentation. This technique is relying on enhancing and filtering the gray scale image contrast. False objects are removed utilizing minimum segment size. 365 blood images were used to examine this segmentation technique. Quantitative analysis of the proposed segmentation technique on the blood image set gives 80.6% accuracy. In comparison to other techniques the proposed segmentation technique performance was found to be superior. The five normal white blood cells types were used for evaluation to compare isolated performance. Eosinophil was found to have the lowest segmentation accuracy which is 71.0% and Monocyte was the highest one with 85.9%. The blood images dataset and the source code are published on MATLAB file exchange website for comparison and re-production.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121557588","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}
Pub Date : 2012-12-13DOI: 10.1109/HealthCom.2012.6379433
Lei Chen, Jijiang Yang, Qing Wang, Yu Niu
As healthcare data is quite valuable to many organizations for scientific research or analysis, the demand of sharing healthcare data have been growing rapidly. Nevertheless, health care data usually contains a lot of patient privacy. Sharing that data directly would bring huge threaten to patient privacy. It's necessary to develop practical methods to balance health care data sharing and privacy protection. Although many approaches have been developed to deal with these problems, most of them are focusing on a small scope of the problem with single theory. In this paper, we'd like to introduce a framework for privacy preserving data sharing with the view of practical application in more comprehensive way. The framework focuses on three key problems of privacy protection during data sharing which are privacy definition and detection, privacy protection policy management, privacy preserving health care data sharing. And solutions to these three problems are discussed in details. A simple implementation of the framework would be introduced to solve the problems of privacy-preserving electronic medical records publishing.
{"title":"A framework for privacy-preserving healthcare data sharing","authors":"Lei Chen, Jijiang Yang, Qing Wang, Yu Niu","doi":"10.1109/HealthCom.2012.6379433","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379433","url":null,"abstract":"As healthcare data is quite valuable to many organizations for scientific research or analysis, the demand of sharing healthcare data have been growing rapidly. Nevertheless, health care data usually contains a lot of patient privacy. Sharing that data directly would bring huge threaten to patient privacy. It's necessary to develop practical methods to balance health care data sharing and privacy protection. Although many approaches have been developed to deal with these problems, most of them are focusing on a small scope of the problem with single theory. In this paper, we'd like to introduce a framework for privacy preserving data sharing with the view of practical application in more comprehensive way. The framework focuses on three key problems of privacy protection during data sharing which are privacy definition and detection, privacy protection policy management, privacy preserving health care data sharing. And solutions to these three problems are discussed in details. A simple implementation of the framework would be introduced to solve the problems of privacy-preserving electronic medical records publishing.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126297189","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}
Pub Date : 2012-12-13DOI: 10.1109/HealthCom.2012.6379453
I. Achumba, Sebastin Bersch, R. Khusainov, D. Azzi, U. Kamalu
The vast amount of literature on human ambulation and Activities of Daily Living (ADL) events classification has highlighted significant details on most aspects of the research area including: monitoring techniques, Wearable Sensor-based Monitoring Device (WSMD) placement on human body parts, and ambulation and ADL data collection methods, among others. However literature has failed to highlight meaningful details on one of the most important aspects of such studies, sensor data segmentation for feature extraction. The choice of segmentation techniques is in general very important, because inappropriate segmentation will most likely result in features without discriminant power. No classifier of whatever sophistication will give meaningful results with features that have no discriminant power. The optimal segmentation technique has been empirically investigated using sensor data from a bi-axial accelerometer. Results of the empirical investigation are presented.
{"title":"On time series sensor data segmentation for fall and activity classification","authors":"I. Achumba, Sebastin Bersch, R. Khusainov, D. Azzi, U. Kamalu","doi":"10.1109/HealthCom.2012.6379453","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379453","url":null,"abstract":"The vast amount of literature on human ambulation and Activities of Daily Living (ADL) events classification has highlighted significant details on most aspects of the research area including: monitoring techniques, Wearable Sensor-based Monitoring Device (WSMD) placement on human body parts, and ambulation and ADL data collection methods, among others. However literature has failed to highlight meaningful details on one of the most important aspects of such studies, sensor data segmentation for feature extraction. The choice of segmentation techniques is in general very important, because inappropriate segmentation will most likely result in features without discriminant power. No classifier of whatever sophistication will give meaningful results with features that have no discriminant power. The optimal segmentation technique has been empirically investigated using sensor data from a bi-axial accelerometer. Results of the empirical investigation are presented.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128009653","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}
Pub Date : 2012-12-13DOI: 10.1109/HealthCom.2012.6379454
L. Cavalini, T. Cook
The long-term maintenance of electronic health records within their original context of information is an ethical requirement that conflicts with the constant need to migrate the information into new systems as they are developed and improved. The specifics of every particular healthcare setting preclude the feasibility of a monolithic health record, and the achievement of interoperability between systems is the primary challenge faced by health informatics researchers. Different multilevel modeling approaches have been studied to deal with this complexity. Nevertheless, the original multilevel modeling specifications are targeted to the development of hospital-based electronic medical records, which adds complexity to the development of simpler purpose-specific applications for extra-hospital healthcare situations. This paper presents the knowledge engineering of a minimalist multilevel model that can be implemented by developers across the broader spectrum of healthcare applications. By using industry standard technologies, this approach enables the wider adoption of interoperable technology for healthcare.
{"title":"Knowledge engineering of healthcare applications based on minimalist multilevel models","authors":"L. Cavalini, T. Cook","doi":"10.1109/HealthCom.2012.6379454","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379454","url":null,"abstract":"The long-term maintenance of electronic health records within their original context of information is an ethical requirement that conflicts with the constant need to migrate the information into new systems as they are developed and improved. The specifics of every particular healthcare setting preclude the feasibility of a monolithic health record, and the achievement of interoperability between systems is the primary challenge faced by health informatics researchers. Different multilevel modeling approaches have been studied to deal with this complexity. Nevertheless, the original multilevel modeling specifications are targeted to the development of hospital-based electronic medical records, which adds complexity to the development of simpler purpose-specific applications for extra-hospital healthcare situations. This paper presents the knowledge engineering of a minimalist multilevel model that can be implemented by developers across the broader spectrum of healthcare applications. By using industry standard technologies, this approach enables the wider adoption of interoperable technology for healthcare.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127081313","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}
Pub Date : 2012-12-13DOI: 10.1109/HealthCom.2012.6379437
L. Schwarz, H. Gamba, Fabio Cabral Pacheco, M. A. Sovierzoski
This paper describes the design of a hardware based system to locate and measure the pupil size using FPGA. The system was implemented in a Cyclone 4E EP4CE115F29C7, from Altera. The component has 114,480 logic elements, although only 8% of the component was used. To detect the pupil the system uses the Greedy Snakes Algorithm at 50 MHz input clock. The system was tested on a video with 30 fps, however, it is possible to process videos in real-time up to 60 fps.
本文介绍了利用 FPGA 定位和测量瞳孔大小的硬件系统设计。该系统由 Altera 公司的 Cyclone 4E EP4CE115F29C7 实现。该组件有 114,480 个逻辑元件，但只使用了其中的 8%。为了检测瞳孔，系统使用了 50 MHz 输入时钟的贪婪之蛇算法。该系统在 30 帧/秒的视频上进行了测试，但也可以实时处理高达 60 帧/秒的视频。
{"title":"Pupil detection in hardware using FPGA","authors":"L. Schwarz, H. Gamba, Fabio Cabral Pacheco, M. A. Sovierzoski","doi":"10.1109/HealthCom.2012.6379437","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379437","url":null,"abstract":"This paper describes the design of a hardware based system to locate and measure the pupil size using FPGA. The system was implemented in a Cyclone 4E EP4CE115F29C7, from Altera. The component has 114,480 logic elements, although only 8% of the component was used. To detect the pupil the system uses the Greedy Snakes Algorithm at 50 MHz input clock. The system was tested on a video with 30 fps, however, it is possible to process videos in real-time up to 60 fps.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127550396","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}
Pub Date : 2012-12-13DOI: 10.1109/HealthCom.2012.6379461
Salah Ibrahim, Guixia Kang
Possessing dependable communications throughout large-scale disaster circumstances is of principal significance in today's world. Especially, propagation of vital information to the survivors and the rescue groups is an essential part of crisis communications. Given that the normal communication channels generally turn into non-functional in large-scale disasters, a provisional communication is required. Thus, relay networks are proper for such situations where forward stations can be suitably situated within the disaster district to increase the coverage of the stations and enhance communication dependability. Recently, the performance analysis of the wireless communication systems that deteriorated by fading, and noise has received great attention. We propose square quadrature amplitude modulation (S-QAM) for consumed power enhancement and Cooperative communication for Ad hoc and sensor networks (WASN) to combat Rician fading. The proposed modulation technique in co-operative communication situation is evaluated by an analytical approach and simulations. The performance analysis with different Rician k-factor and diversity order with Matlab simulation is done. We observe bit error rate gain performance, in which there is a considerable gain in performance accomplished by increasing diversity order L, while the gain in performance that achieved by the increase in k is extremely small without diversity order. We conclude that using of cooperating communication can enhance the Rician fading in disaster situation and helps to save human lives.
{"title":"Error rate analysis and co-operative communication for ad-hoc and sensor network to combat Rician fading based on disaster healthcare","authors":"Salah Ibrahim, Guixia Kang","doi":"10.1109/HealthCom.2012.6379461","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379461","url":null,"abstract":"Possessing dependable communications throughout large-scale disaster circumstances is of principal significance in today's world. Especially, propagation of vital information to the survivors and the rescue groups is an essential part of crisis communications. Given that the normal communication channels generally turn into non-functional in large-scale disasters, a provisional communication is required. Thus, relay networks are proper for such situations where forward stations can be suitably situated within the disaster district to increase the coverage of the stations and enhance communication dependability. Recently, the performance analysis of the wireless communication systems that deteriorated by fading, and noise has received great attention. We propose square quadrature amplitude modulation (S-QAM) for consumed power enhancement and Cooperative communication for Ad hoc and sensor networks (WASN) to combat Rician fading. The proposed modulation technique in co-operative communication situation is evaluated by an analytical approach and simulations. The performance analysis with different Rician k-factor and diversity order with Matlab simulation is done. We observe bit error rate gain performance, in which there is a considerable gain in performance accomplished by increasing diversity order L, while the gain in performance that achieved by the increase in k is extremely small without diversity order. We conclude that using of cooperating communication can enhance the Rician fading in disaster situation and helps to save human lives.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130349797","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}
Pub Date : 2012-12-13DOI: 10.1109/HealthCom.2012.6379376
Qian Wang, Xiang Chen, De Wu, Lingling Qian, Xu Zhang
This paper presents a framework of gait analysis for children with cerebral palsy (CP) using electromyography (EMG) and acceleration (ACC) signals. In this framework, ACC signals are firstly processed for stride cycle detection and segmentation, and then utilized to reveal kinematic information associated with gait abnormality, whereas the EMG signals are adopted to assess abnormal muscle activation patterns during gait movement. Six CP children with gait abnormalities were recruited to form the CP group , and two children with TD (typical development) were also recruited as the control group for gait analysis experiments. EMG signals from four typical muscles of both legs and vertical acceleration of shanks were collected simultaneously. It can be demonstrated from the experimental results that the proposed method is able to extract ACC and EMG patterns, indicating its clinical potential for the assessment and therapy of lower extremity functions for children with CP.
{"title":"Acceleration and electromyography (EMG) pattern analysis for children with cerebral palsy","authors":"Qian Wang, Xiang Chen, De Wu, Lingling Qian, Xu Zhang","doi":"10.1109/HealthCom.2012.6379376","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379376","url":null,"abstract":"This paper presents a framework of gait analysis for children with cerebral palsy (CP) using electromyography (EMG) and acceleration (ACC) signals. In this framework, ACC signals are firstly processed for stride cycle detection and segmentation, and then utilized to reveal kinematic information associated with gait abnormality, whereas the EMG signals are adopted to assess abnormal muscle activation patterns during gait movement. Six CP children with gait abnormalities were recruited to form the CP group , and two children with TD (typical development) were also recruited as the control group for gait analysis experiments. EMG signals from four typical muscles of both legs and vertical acceleration of shanks were collected simultaneously. It can be demonstrated from the experimental results that the proposed method is able to extract ACC and EMG patterns, indicating its clinical potential for the assessment and therapy of lower extremity functions for children with CP.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128413802","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}
Pub Date : 2012-12-13DOI: 10.1109/HealthCom.2012.6379438
Z. Fang, Zhan Zhao, Fangmin Sun, Xianxiang Chen, L. Du, Huaiyong Li, Lili Tian
We developed and tested the Institute of Electronics, Chinese Academy of Sciences (IECAS) 3AHcare node, a health monitoring device capable of measuring a subject's ECG, blood pressure, blood oxygenation, respiration, temperature and motion - almost equivalent to the feature set of a hospital bedside patient monitor. The main contribution of this paper include: the device has been a highly integrated design incorporating the radio and all associated circuitry on a single PCB; a new noninvasive and cuff-less measurement of blood pressure using pulse wave transit time has been designed and validated. The device stores data locally on microSD flash and /or transmits via Bluetooth and/or Zigbee. We have developed a bandage vest which embeds reusable electrodes for data acquisition as well as a desktop and mobile application for real-time data telemetry. We have evaluated the performance of the device in capturing and recording ambulatory data and found the device easy to use and with high precision.
{"title":"The 3AHcare node: Health monitoring continuously","authors":"Z. Fang, Zhan Zhao, Fangmin Sun, Xianxiang Chen, L. Du, Huaiyong Li, Lili Tian","doi":"10.1109/HealthCom.2012.6379438","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379438","url":null,"abstract":"We developed and tested the Institute of Electronics, Chinese Academy of Sciences (IECAS) 3AHcare node, a health monitoring device capable of measuring a subject's ECG, blood pressure, blood oxygenation, respiration, temperature and motion - almost equivalent to the feature set of a hospital bedside patient monitor. The main contribution of this paper include: the device has been a highly integrated design incorporating the radio and all associated circuitry on a single PCB; a new noninvasive and cuff-less measurement of blood pressure using pulse wave transit time has been designed and validated. The device stores data locally on microSD flash and /or transmits via Bluetooth and/or Zigbee. We have developed a bandage vest which embeds reusable electrodes for data acquisition as well as a desktop and mobile application for real-time data telemetry. We have evaluated the performance of the device in capturing and recording ambulatory data and found the device easy to use and with high precision.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129219768","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}
Pub Date : 2012-12-13DOI: 10.1109/HealthCom.2012.6379413
S. Chatterjee, Qi Xie, K. Dutta
Diabetes is a common but serious chronic disease. Nearly 8% of Americans who are aged 65 and older (about 10.9 million) suffer from this deadly disease. Self-management of this disease is possible, yet the older population lack knowledge, have denial and often lack motivation to do so. Recently we have demonstrated sensor-based network architecture within the home to monitor daily activities and biological vital parameters [25]. The data is mined to find patterns and abnormal values. Through daily text messages that are sent to the subjects, we have achieved to influence behavior change using persuasive principles. In this paper, we analyze the daily data and demonstrate that a model to profile the subject's daily behavior is possible using Artificial Neural Networks (ANN). Such a profiling has the advantage of knowing the situations, when the subject's daily activity deviates from its “normal profile”, which may be a possible indication of an onset of some health condition or disease. Lastly we develop an ANN based model to predict blood sugar level based on previous day's activity and diet intake. Such a model can be used to help a subject with high blood sugar to adjust daily activity to reach a target blood sugar level and also gives a care-giver advance notice to intervene in adverse situations.
{"title":"A predictive modeling engine using neural networks: Diabetes management from sensor and activity data","authors":"S. Chatterjee, Qi Xie, K. Dutta","doi":"10.1109/HealthCom.2012.6379413","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379413","url":null,"abstract":"Diabetes is a common but serious chronic disease. Nearly 8% of Americans who are aged 65 and older (about 10.9 million) suffer from this deadly disease. Self-management of this disease is possible, yet the older population lack knowledge, have denial and often lack motivation to do so. Recently we have demonstrated sensor-based network architecture within the home to monitor daily activities and biological vital parameters [25]. The data is mined to find patterns and abnormal values. Through daily text messages that are sent to the subjects, we have achieved to influence behavior change using persuasive principles. In this paper, we analyze the daily data and demonstrate that a model to profile the subject's daily behavior is possible using Artificial Neural Networks (ANN). Such a profiling has the advantage of knowing the situations, when the subject's daily activity deviates from its “normal profile”, which may be a possible indication of an onset of some health condition or disease. Lastly we develop an ANN based model to predict blood sugar level based on previous day's activity and diet intake. Such a model can be used to help a subject with high blood sugar to adjust daily activity to reach a target blood sugar level and also gives a care-giver advance notice to intervene in adverse situations.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117169936","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}
Pub Date : 2012-12-13DOI: 10.1109/HealthCom.2012.6379428
Qiang Lin, Hongbo Ni, Xingshe Zhou
With the rapidly ageing population in most countries, the health and safety issues become the primary concern for elderly people because ageing is often associated with physical and cognitive impairments. In order to provide intelligent assistive health services for elders, in this paper, we propose an integrated OSGi-based service platform that can aggregate a variety of health assistive services, including health status monitoring, automated diagnosis and prognosis, and personalized health instruction by leveraging either stationary biosensors deployed in domestic settings or mobile sensing artifacts carried by elders. The assistive services in this integrated platform are able to help elders sustain and enhance health condition and quality of life with personalized health support. Our proposed platform is highly scalable and reusable by exploiting the component-based architecture of OSGI service framework, new services can be easily added into the platform according to individuals' needs and requirements. An implemented prototype system and the relevant performance evaluation are also presented.
{"title":"An OSGi-based heath service platform for elderly people","authors":"Qiang Lin, Hongbo Ni, Xingshe Zhou","doi":"10.1109/HealthCom.2012.6379428","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379428","url":null,"abstract":"With the rapidly ageing population in most countries, the health and safety issues become the primary concern for elderly people because ageing is often associated with physical and cognitive impairments. In order to provide intelligent assistive health services for elders, in this paper, we propose an integrated OSGi-based service platform that can aggregate a variety of health assistive services, including health status monitoring, automated diagnosis and prognosis, and personalized health instruction by leveraging either stationary biosensors deployed in domestic settings or mobile sensing artifacts carried by elders. The assistive services in this integrated platform are able to help elders sustain and enhance health condition and quality of life with personalized health support. Our proposed platform is highly scalable and reusable by exploiting the component-based architecture of OSGI service framework, new services can be easily added into the platform according to individuals' needs and requirements. An implemented prototype system and the relevant performance evaluation are also presented.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117304935","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}
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