Pub Date : 2012-12-13DOI: 10.1109/HealthCom.2012.6379457
S. Alqassim, M. Ganesh, Shaheen Khoja, M. Zaidi, F. Aloul, A. Sagahyroon
Obstructive Sleep Apnea (OSA) is a sleeping disorder characterized by the repetitive reduction of airflow during sleep. In this paper, we discuss the design and implementation of a user-friendly mobile application developed on multiple platforms (Windows and Android) to monitor and detect symptoms of sleep apnea using the smart phone's built-in sensors. The purpose of the application, Sleep Apnea Monitor (SAM), is to allow users to get a sense of whether or not they are likely to have sleep apnea, before continuing with more expensive and advanced sleep tests. In addition, SAM provides doctors and sleep specialists with remote access to patients' records and allows them to confirm their initial diagnosis. The parameters measured by this application are breathing patterns and movement patterns, which are recorded respectively using the built-in microphone and accelerometer. The recorded data is sent to a server for analysis in order to diagnose patients and maintain geographical studies of areas with sleep apnea patterns. The application is successfully tested among a number of users in the UAE. The system diagnoses and reports the level of the user's sleep apnea. In addition, doctors can remotely monitor users through the website, which is interfaced with Google Maps to keep track of user locations, and keep track of their analysed records.
{"title":"Sleep Apnea Monitoring using mobile phones","authors":"S. Alqassim, M. Ganesh, Shaheen Khoja, M. Zaidi, F. Aloul, A. Sagahyroon","doi":"10.1109/HealthCom.2012.6379457","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379457","url":null,"abstract":"Obstructive Sleep Apnea (OSA) is a sleeping disorder characterized by the repetitive reduction of airflow during sleep. In this paper, we discuss the design and implementation of a user-friendly mobile application developed on multiple platforms (Windows and Android) to monitor and detect symptoms of sleep apnea using the smart phone's built-in sensors. The purpose of the application, Sleep Apnea Monitor (SAM), is to allow users to get a sense of whether or not they are likely to have sleep apnea, before continuing with more expensive and advanced sleep tests. In addition, SAM provides doctors and sleep specialists with remote access to patients' records and allows them to confirm their initial diagnosis. The parameters measured by this application are breathing patterns and movement patterns, which are recorded respectively using the built-in microphone and accelerometer. The recorded data is sent to a server for analysis in order to diagnose patients and maintain geographical studies of areas with sleep apnea patterns. The application is successfully tested among a number of users in the UAE. The system diagnoses and reports the level of the user's sleep apnea. In addition, doctors can remotely monitor users through the website, which is interfaced with Google Maps to keep track of user locations, and keep track of their analysed records.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"149 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":"132179227","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.2012.6380071
M. Yeh, Hao-Feng Luo, Nai-Wei Lin, Zen Chen, C. Yeh
Allergic rhinitis is a prevalent disease throughout the world. Electrodermal screening devices (EDSD) are devices that can measure the electrical properties of acupuncture points. This paper performs a series of experiments based on machine learning algorithms to study the feasibility of utilizing EDSD to diagnose allergic rhinitis. The experimental result shows that, to assess the presence of allergic rhinitis, using the k-nearest neighbor classification algorithm, the accuracy can achieve 93.26%, and using the support vector machine classification algorithm, the average accuracy can achieve 97.78%. The experimental result also shows that using, respectively, the k-means clustering algorithm and the Ward's hierarchical clustering algorithm to cluster the data into three clusters, 87% of the data are consistently clustered. The average total symptom scores in these three clusters are also very consistent. Based on the 87% consistently clustered data, using the support vector machine algorithm to assess the severity (mild and moderate/severe) of allergic rhinitis, the average accuracy can achieve 99.57%. In particular, the experimental result also shows that the disordered EDSD values at acupuncture points of spleen meridian and liver meridian coincides with the clinic experiences of standard traditional Chinese medicine.
{"title":"A study on electrical properties of acupuncture points in allergic rhinitis","authors":"M. Yeh, Hao-Feng Luo, Nai-Wei Lin, Zen Chen, C. Yeh","doi":"10.1109/HealthCom.2012.6380071","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6380071","url":null,"abstract":"Allergic rhinitis is a prevalent disease throughout the world. Electrodermal screening devices (EDSD) are devices that can measure the electrical properties of acupuncture points. This paper performs a series of experiments based on machine learning algorithms to study the feasibility of utilizing EDSD to diagnose allergic rhinitis. The experimental result shows that, to assess the presence of allergic rhinitis, using the k-nearest neighbor classification algorithm, the accuracy can achieve 93.26%, and using the support vector machine classification algorithm, the average accuracy can achieve 97.78%. The experimental result also shows that using, respectively, the k-means clustering algorithm and the Ward's hierarchical clustering algorithm to cluster the data into three clusters, 87% of the data are consistently clustered. The average total symptom scores in these three clusters are also very consistent. Based on the 87% consistently clustered data, using the support vector machine algorithm to assess the severity (mild and moderate/severe) of allergic rhinitis, the average accuracy can achieve 99.57%. In particular, the experimental result also shows that the disordered EDSD values at acupuncture points of spleen meridian and liver meridian coincides with the clinic experiences of standard traditional Chinese medicine.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"3 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":"133776409","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.2012.6379432
F. Rahman, Sheikh Iqbal Ahamed, Jijiang Yang, Qing Wang
RFID has received considerable attention within the healthcare for almost a decade now. The technology's promise to efficiently track hospital supplies, medical equipment, medications and patients is an attractive proposition to the healthcare industry. However, the prospect of wide spread use of RFID tags in healthcare has also triggered discussions regarding privacy, particularly because RFID data in transit may easily be intercepted. In a nutshell, this technology has not really seen its true potential in healthcare since privacy concerns raised by the tag bearers are not properly addressed by existing protocols and frameworks. The two major types of privacy preservation techniques that are required in an RFID based healthcare are: 1) a privacy preserving authentication protocol is required while sensing RFID tags for different identification and monitoring purposes 2) a privacy preserving access control mechanism is required to restrict unauthorized access of private information while providing healthcare services using the tag ID. In this paper, we propose a component based framework (PriSens-HSAC) that makes an effort to address the above mentioned two privacy issues. To the best of our knowledge, this is the first framework to provide better privacy in RFID based healthcare systems, using authentication and access control technique.
{"title":"I am not a goldfish in a bowl: A privacy preserving framework for RFID based healthcare systems","authors":"F. Rahman, Sheikh Iqbal Ahamed, Jijiang Yang, Qing Wang","doi":"10.1109/HealthCom.2012.6379432","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379432","url":null,"abstract":"RFID has received considerable attention within the healthcare for almost a decade now. The technology's promise to efficiently track hospital supplies, medical equipment, medications and patients is an attractive proposition to the healthcare industry. However, the prospect of wide spread use of RFID tags in healthcare has also triggered discussions regarding privacy, particularly because RFID data in transit may easily be intercepted. In a nutshell, this technology has not really seen its true potential in healthcare since privacy concerns raised by the tag bearers are not properly addressed by existing protocols and frameworks. The two major types of privacy preservation techniques that are required in an RFID based healthcare are: 1) a privacy preserving authentication protocol is required while sensing RFID tags for different identification and monitoring purposes 2) a privacy preserving access control mechanism is required to restrict unauthorized access of private information while providing healthcare services using the tag ID. In this paper, we propose a component based framework (PriSens-HSAC) that makes an effort to address the above mentioned two privacy issues. To the best of our knowledge, this is the first framework to provide better privacy in RFID based healthcare systems, using authentication and access control technique.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"56 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":"115659526","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.2012.6379381
Min-Hui Foo, J. C. Chua, C. Toh, J. Ng
Medication non-adherence is a major problem to all stakeholders, posing escalating costs and risks to patients as well as substantial economic burden to the health care industry. Solutions that attempt to broaden the functions and capabilities of medication management have hitherto been employing a narrow-focused approach, often failing to address the multitude of factors that leads to the phenomena. In this paper, we present an experimental comparison of user attitude towards medication adherence using a single-focused versus a multifaceted personalized medication management system that has been implemented with elements of motivational and educational strategies. The findings from this research suggest evidence of the significance and usefulness of applying a multifaceted approach, in particular, the implementation of motivational and educational strategies in the design of a personalized medication management system in addressing medication non-adherence.
{"title":"Evaluating the influence of motivational and educational strategies in personalized medication management","authors":"Min-Hui Foo, J. C. Chua, C. Toh, J. Ng","doi":"10.1109/HealthCom.2012.6379381","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379381","url":null,"abstract":"Medication non-adherence is a major problem to all stakeholders, posing escalating costs and risks to patients as well as substantial economic burden to the health care industry. Solutions that attempt to broaden the functions and capabilities of medication management have hitherto been employing a narrow-focused approach, often failing to address the multitude of factors that leads to the phenomena. In this paper, we present an experimental comparison of user attitude towards medication adherence using a single-focused versus a multifaceted personalized medication management system that has been implemented with elements of motivational and educational strategies. The findings from this research suggest evidence of the significance and usefulness of applying a multifaceted approach, in particular, the implementation of motivational and educational strategies in the design of a personalized medication management system in addressing medication non-adherence.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"486 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":"124421477","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.2012.6379441
Guixia Kang
Recently, the R&D and applications of M2M systems are booming in China, especially after it is written in the 2010 Government Work Report. In this paper, the R&D works of wireless eHealth (WeHealth) are overviewed, the concept of which was proposed by our group in 2005. Some key techniques of WeHealth system are discussed, and some practices based on the concept of WeHealth are introduced. Besides, a recent WeHealth pilot trial on chronic disease monitoring is also introduced, which is reported as “The First Wireless Healthcare Chronic Disease Monitoring Project in China Based on Internet of Things Technology”. There are 30 community hospitals up to now applying our WeHealth blood pressure monitoring system for chronic disease management. The practical data clearly demonstrate the effectiveness of our WeHealth system in hypertension disease control.
{"title":"Wireless eHealth (WeHealth) — From concept to practice","authors":"Guixia Kang","doi":"10.1109/HealthCom.2012.6379441","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379441","url":null,"abstract":"Recently, the R&D and applications of M2M systems are booming in China, especially after it is written in the 2010 Government Work Report. In this paper, the R&D works of wireless eHealth (WeHealth) are overviewed, the concept of which was proposed by our group in 2005. Some key techniques of WeHealth system are discussed, and some practices based on the concept of WeHealth are introduced. Besides, a recent WeHealth pilot trial on chronic disease monitoring is also introduced, which is reported as “The First Wireless Healthcare Chronic Disease Monitoring Project in China Based on Internet of Things Technology”. There are 30 community hospitals up to now applying our WeHealth blood pressure monitoring system for chronic disease management. The practical data clearly demonstrate the effectiveness of our WeHealth system in hypertension disease control.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"23 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":"116347220","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.2012.6380069
Hao Chen, D. Xiang, Qin Wei-yi, Minwei Zhou, Tian Yan, Liu Jian, Mingyu Wang, Jijiang Yang, Wang Qing, Haifeng Yang, Xianjun Sun, Haixiao Gao, Li Geng, Gao Qiang
We established a regional cooperative emergency care system of ST-elevation myocardial infarction patients based on the internet of things. In this article, the current status and problems of ST-elevation myocardial infarction patient emergency care have been studied and key influence factors are found. As the results, a shorter time from symptom onset to reperfusion is achieved with improved outcomes for patients with ST-segment elevation myocardial infarction (STEMI). Primary percutaneous coronary intervention (PCI) in patients with STEMI significantly reduces mortality and morbidity, particularly when door-to-balloon (D2B) time is <; 90 min. An expedited pre-hospital diagnosis and transfer pathway was developed, with rapid reperfusion times and favorable outcomes.
{"title":"A study of regional cooperative emergency care system for ST-elevation myocardial infarction patients based on the internet of things","authors":"Hao Chen, D. Xiang, Qin Wei-yi, Minwei Zhou, Tian Yan, Liu Jian, Mingyu Wang, Jijiang Yang, Wang Qing, Haifeng Yang, Xianjun Sun, Haixiao Gao, Li Geng, Gao Qiang","doi":"10.1109/HEALTHCOM.2012.6380069","DOIUrl":"https://doi.org/10.1109/HEALTHCOM.2012.6380069","url":null,"abstract":"We established a regional cooperative emergency care system of ST-elevation myocardial infarction patients based on the internet of things. In this article, the current status and problems of ST-elevation myocardial infarction patient emergency care have been studied and key influence factors are found. As the results, a shorter time from symptom onset to reperfusion is achieved with improved outcomes for patients with ST-segment elevation myocardial infarction (STEMI). Primary percutaneous coronary intervention (PCI) in patients with STEMI significantly reduces mortality and morbidity, particularly when door-to-balloon (D2B) time is <; 90 min. An expedited pre-hospital diagnosis and transfer pathway was developed, with rapid reperfusion times and favorable outcomes.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"108 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":"121174414","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.2012.6379404
Shoichiro Tomii, T. Ohtsuki
Recently, various kinds of healthcare systems for the elderly have been developed. Falling detection is one of the important tasks to protect them from crucial accidents. Cameras, acoustic sensors, and accelerometers are mainly used to detect the falling. However, from the viewpoint of false alarm rate, privacy issues, and intrusiveness of the devices, each method has its own shortcomings. Doppler sensor is a palm-sized device, and can be implemented for highly accurate human activity recognition without wearable sensors. Doppler sensor is less sensitive to the movements orthogonal to the irradiation direction. Thus, a method to compensate this characteristic is needed. We propose falling detection using multiple Doppler sensors to raise the precision of falling detection covering the multi-directions of the target movement. Two or three sensors are exploited, and the extracted sensor data is processed by a feature combination or selection method. The resulting data are classified by support vector machine (SVM) or k-nearest neighbors (k-NN). We evaluate several kinds of falling, “Standing - Falling,” “Walking - Falling,” and “Standing up - Falling,” and non-falling like “Walking,” “Lying on floor,” “Picking up,” and “Sitting on a chair.” These activities are tested toward 8 directions spaced at respective intervals of 45 degrees. The results show that the combination method, using three sensors, achieves 95.5 % accuracy of falling detection, and the selection method, using three sensors, achieves 93.3 % accuracy. We also discuss the accuracy of each activity direction and the viability of these methods for the practical use.
{"title":"Falling detection using multiple doppler sensors","authors":"Shoichiro Tomii, T. Ohtsuki","doi":"10.1109/HealthCom.2012.6379404","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379404","url":null,"abstract":"Recently, various kinds of healthcare systems for the elderly have been developed. Falling detection is one of the important tasks to protect them from crucial accidents. Cameras, acoustic sensors, and accelerometers are mainly used to detect the falling. However, from the viewpoint of false alarm rate, privacy issues, and intrusiveness of the devices, each method has its own shortcomings. Doppler sensor is a palm-sized device, and can be implemented for highly accurate human activity recognition without wearable sensors. Doppler sensor is less sensitive to the movements orthogonal to the irradiation direction. Thus, a method to compensate this characteristic is needed. We propose falling detection using multiple Doppler sensors to raise the precision of falling detection covering the multi-directions of the target movement. Two or three sensors are exploited, and the extracted sensor data is processed by a feature combination or selection method. The resulting data are classified by support vector machine (SVM) or k-nearest neighbors (k-NN). We evaluate several kinds of falling, “Standing - Falling,” “Walking - Falling,” and “Standing up - Falling,” and non-falling like “Walking,” “Lying on floor,” “Picking up,” and “Sitting on a chair.” These activities are tested toward 8 directions spaced at respective intervals of 45 degrees. The results show that the combination method, using three sensors, achieves 95.5 % accuracy of falling detection, and the selection method, using three sensors, achieves 93.3 % accuracy. We also discuss the accuracy of each activity direction and the viability of these methods for the practical use.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"273 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":"122937336","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.2012.6380065
Lanxin Bi, Xuezhong Zhou, Lei Zhang, Runshun Zhang
Traditional Chinese Medicine (TCM) has been widely used to treat various diseases like infectious diseases. Treatment Based on Syndrome Differentiation (TBSD) is the main principle in TCM clinical practice. So exploring the relationships between diagnoses and treatments from successful cases is important and valuable for better treating hepatitis diseases, which is a decision support problem based on data warehouse in nature. In this paper, using the multidimensional analysis techniques of BusinessObjects (BO) platform, we introduce a series of online analytical processing (OLAP) reports which cover different subjects of TCM on hepatitis diseases and a corresponding system used to manage the reports. It has been found that these OLAP reports are useful in experience sharing of making diagnoses and giving treatments on hepatitis diseases.
{"title":"Multidimensional analysis for Traditional Chinese Medicine diagnosis and treatment on hepatitis diseases","authors":"Lanxin Bi, Xuezhong Zhou, Lei Zhang, Runshun Zhang","doi":"10.1109/HealthCom.2012.6380065","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6380065","url":null,"abstract":"Traditional Chinese Medicine (TCM) has been widely used to treat various diseases like infectious diseases. Treatment Based on Syndrome Differentiation (TBSD) is the main principle in TCM clinical practice. So exploring the relationships between diagnoses and treatments from successful cases is important and valuable for better treating hepatitis diseases, which is a decision support problem based on data warehouse in nature. In this paper, using the multidimensional analysis techniques of BusinessObjects (BO) platform, we introduce a series of online analytical processing (OLAP) reports which cover different subjects of TCM on hepatitis diseases and a corresponding system used to manage the reports. It has been found that these OLAP reports are useful in experience sharing of making diagnoses and giving treatments on hepatitis diseases.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"11 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":"126214014","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.2012.6380061
Longfeng Chen, Guixia Kang, Xidong Zhang, Lichen Lee, Xiangyi Li
In the intelligent monitoring of the hypertensive patients, it's necessary to assess their treatment effect and give corresponding diagnostic feedback automatically. This paper proposed a hybrid decision support system (DSS) combining several data mining techniques using an improved weighted majority voting scheme (iWMV). The mass health data of hypertensive patients were used as data source of the data mining techniques, and iWMV was used to produce a proper final judgement on patients' control condition on the basis of the individual classifier results. The proposed system was trained and evaluated using data from 167 hypertensive patients. Performance analysis showed that the hybrid system could reach classification rate (CR) of 95.34% and kappa coefficient (KC) of 92.54%, much better than systems with a single classification algorithm or combining using the simple weighted majority voting scheme (WMV). Moreover, the proposed DSS showed high stability.
{"title":"Hybrid decision making in the monitoring of hypertensive patients","authors":"Longfeng Chen, Guixia Kang, Xidong Zhang, Lichen Lee, Xiangyi Li","doi":"10.1109/HealthCom.2012.6380061","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6380061","url":null,"abstract":"In the intelligent monitoring of the hypertensive patients, it's necessary to assess their treatment effect and give corresponding diagnostic feedback automatically. This paper proposed a hybrid decision support system (DSS) combining several data mining techniques using an improved weighted majority voting scheme (iWMV). The mass health data of hypertensive patients were used as data source of the data mining techniques, and iWMV was used to produce a proper final judgement on patients' control condition on the basis of the individual classifier results. The proposed system was trained and evaluated using data from 167 hypertensive patients. Performance analysis showed that the hybrid system could reach classification rate (CR) of 95.34% and kappa coefficient (KC) of 92.54%, much better than systems with a single classification algorithm or combining using the simple weighted majority voting scheme (WMV). Moreover, the proposed DSS showed high stability.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"89 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":"127115060","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.2012.6379419
Zhisheng Yan, B. Liu, C. Chen
Wireless Body Area Network (WBAN) is a promising type of networks that mainly targets at applications in ubiquitous communication and e-Health services. Different from other types of networks, one important challenge for WBAN is that its quality of service (QoS) requirement, in terms of delivery probability and data rate, will be time varying since human body is a highly dynamic physical environment. Another significant challenge for WBAN is that energy efficiency needs to be guaranteed in such a resource-limited network. In this paper, a QoS-driven scheduling approach is proposed to address these challenges. We model the WBAN channel as a Markov model as suggested by the emerging IEEE 802.15.6 BAN standard and propose a threshold-based scheme to adjust the transmission order of nodes. The number of slots for each node is optimally assigned according to the QoS requirement while minimizing the energy consumption of nodes. The results from extensive simulations show that the proposed approach can provide high QoS and energy efficiency under different network conditions, especially in highly heterogeneous ones in WBAN.
{"title":"QoS-driven scheduling approach using optimal slot allocation for Wireless Body Area Networks","authors":"Zhisheng Yan, B. Liu, C. Chen","doi":"10.1109/HealthCom.2012.6379419","DOIUrl":"https://doi.org/10.1109/HealthCom.2012.6379419","url":null,"abstract":"Wireless Body Area Network (WBAN) is a promising type of networks that mainly targets at applications in ubiquitous communication and e-Health services. Different from other types of networks, one important challenge for WBAN is that its quality of service (QoS) requirement, in terms of delivery probability and data rate, will be time varying since human body is a highly dynamic physical environment. Another significant challenge for WBAN is that energy efficiency needs to be guaranteed in such a resource-limited network. In this paper, a QoS-driven scheduling approach is proposed to address these challenges. We model the WBAN channel as a Markov model as suggested by the emerging IEEE 802.15.6 BAN standard and propose a threshold-based scheme to adjust the transmission order of nodes. The number of slots for each node is optimally assigned according to the QoS requirement while minimizing the energy consumption of nodes. The results from extensive simulations show that the proposed approach can provide high QoS and energy efficiency under different network conditions, especially in highly heterogeneous ones in WBAN.","PeriodicalId":138952,"journal":{"name":"2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"38 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":"127379943","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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