Pub Date : 2014-10-01DOI: 10.1109/HealthCom.2014.7001818
F. Vannieuwenborg, F. Ongenae, P. Demyttenaere, L. V. Poucke, J. V. Ooteghem, S. Verstichel, S. Verbrugge, D. Colle, F. Turck, M. Pickavet
Current nurse call systems hinder the efficiency of nurses as the systems are not aware of the type of requested help and the context in which their help is required. To tackle these issues, we have developed an ontology-based nurse call system that automatically takes the patients' and caregivers' profiles and context into account when assigning calls to nurses by modelling this information in an ontology, i.e., a formal domain model. For example, current tasks of the nurses and trust relationship with patients are considered while allocating calls to caregivers. Focus is not only on creating a higher quality patient care, but also on distributing the workload more evenly over all caregivers. However, not in all hospital departments such a smart nurse call system will have a significant impact, e.g., geriatric versus emergency care. To gain insights into the total impact of a smart nurse call system, a dedicated discrete event simulation (DES) model is presented that tests its performance. Based on realistic nurse call logs and information gathered at representative hospital departments through interviews and observations, the simulation model allows optimizing decisions, modelled as rules based on the information captured in the ontology, to allocate calls to the best suited nurse. Several scenarios with a varying number of calls, staff members, etc. are tested to be able to define the effectiveness and the (dis)advantages of the ontology-based system with respect to the current one. In conclusion, recommendations are made towards improving the currently employed nurse call systems in hospitals.
{"title":"Techno-economic evaluation of an ontology-based nurse call system via discrete event simulations","authors":"F. Vannieuwenborg, F. Ongenae, P. Demyttenaere, L. V. Poucke, J. V. Ooteghem, S. Verstichel, S. Verbrugge, D. Colle, F. Turck, M. Pickavet","doi":"10.1109/HealthCom.2014.7001818","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001818","url":null,"abstract":"Current nurse call systems hinder the efficiency of nurses as the systems are not aware of the type of requested help and the context in which their help is required. To tackle these issues, we have developed an ontology-based nurse call system that automatically takes the patients' and caregivers' profiles and context into account when assigning calls to nurses by modelling this information in an ontology, i.e., a formal domain model. For example, current tasks of the nurses and trust relationship with patients are considered while allocating calls to caregivers. Focus is not only on creating a higher quality patient care, but also on distributing the workload more evenly over all caregivers. However, not in all hospital departments such a smart nurse call system will have a significant impact, e.g., geriatric versus emergency care. To gain insights into the total impact of a smart nurse call system, a dedicated discrete event simulation (DES) model is presented that tests its performance. Based on realistic nurse call logs and information gathered at representative hospital departments through interviews and observations, the simulation model allows optimizing decisions, modelled as rules based on the information captured in the ontology, to allocate calls to the best suited nurse. Several scenarios with a varying number of calls, staff members, etc. are tested to be able to define the effectiveness and the (dis)advantages of the ontology-based system with respect to the current one. In conclusion, recommendations are made towards improving the currently employed nurse call systems in hospitals.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130244692","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001826
Leonardo Severo Alves de Melo, A. A. D. Melo, Julio Cesar Dalbello, E. R. Vale
The international standard of transport and storage of radiological images - DICOM, the National Electrical Manufacturers Association (NEMA) - was formed to integrate the industry segment in favor of a single model of operation, aiming above all integration, customization and possible economy. This methodology combines virtues, mainly by excluding the proprietary view of previous systems. The images of a radiological examination must be transmitted from source to receiver without interruption or delay, have a large volume of files and large size together (in megabytes). The international standard is designed to operate at optimum telecommunications environments - stable, secure and transmission rates of local networks. In order to enable the practice of medicine where there is the presence of health professionals, Telemedicine seeks the creation of technologies that enable its activity. Conventionally, these physical environments also lack virtuous telecommunications systems. The telecom environment in the State of Amazonas to clinical and hospital environments of the State Secretariat of Health of the Amazon is distributed via satellite to 128 kbps connections. The 62 cities of this state are in dense forest environments with high humidity, heavy rainfall and high rate of electrical storms. Currently, even in the state of Amazonas, is in use in 44 units and in installation phase in the remaining 21 hospitals of the State Government, transmitting full digital mammograms beyond satellite to the Medical Report Center, located at the Hospital Francisca Mendes (Manaus/AM) of Federal University of Amazonas. The system has been customized to the case and is able to carry more than 380,000 exams per year, coming from the State Hospitals for Medical Reports Center. A simulator of deployed communications equipment will be presented at the Congress, demonstrating its practicality and dynamism when compared to international systems.
{"title":"Specialized telecommunications system in the transmission of digital radiological images in hostile environments","authors":"Leonardo Severo Alves de Melo, A. A. D. Melo, Julio Cesar Dalbello, E. R. Vale","doi":"10.1109/HealthCom.2014.7001826","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001826","url":null,"abstract":"The international standard of transport and storage of radiological images - DICOM, the National Electrical Manufacturers Association (NEMA) - was formed to integrate the industry segment in favor of a single model of operation, aiming above all integration, customization and possible economy. This methodology combines virtues, mainly by excluding the proprietary view of previous systems. The images of a radiological examination must be transmitted from source to receiver without interruption or delay, have a large volume of files and large size together (in megabytes). The international standard is designed to operate at optimum telecommunications environments - stable, secure and transmission rates of local networks. In order to enable the practice of medicine where there is the presence of health professionals, Telemedicine seeks the creation of technologies that enable its activity. Conventionally, these physical environments also lack virtuous telecommunications systems. The telecom environment in the State of Amazonas to clinical and hospital environments of the State Secretariat of Health of the Amazon is distributed via satellite to 128 kbps connections. The 62 cities of this state are in dense forest environments with high humidity, heavy rainfall and high rate of electrical storms. Currently, even in the state of Amazonas, is in use in 44 units and in installation phase in the remaining 21 hospitals of the State Government, transmitting full digital mammograms beyond satellite to the Medical Report Center, located at the Hospital Francisca Mendes (Manaus/AM) of Federal University of Amazonas. The system has been customized to the case and is able to carry more than 380,000 exams per year, coming from the State Hospitals for Medical Reports Center. A simulator of deployed communications equipment will be presented at the Congress, demonstrating its practicality and dynamism when compared to international systems.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131073198","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001889
Fabio Leite, P. Antonino, Paulo Barbosa, S. Kemmann, Raphael Mendonca
We have investigated approaches in the literature to assess the quality of the software architectures of medical devices, and have found evidence that there is a lack of methodologies for evaluating the software architecture design aspects of medical devices that might affect system safety. Such evidences were identified when evaluating the software architecture of the FDA Generic Infusion Pump searching for architectural evaluation approaches available in the literature. In order to fill this gap, we propose a set of quality questions that focus on analyzing software architecture design aspects of medical devices aiming safety. We show arguments on why reference projects such as the FDA Generic Infusion Pump system must satisfy our new quality questions. The quality questions were integrated into a quality model commissioned by the Brazilian Health Ministery for the certification of medical devices.
{"title":"Are the current architectural practices suitable for safety aspects of medical devices? An exploratory investigation","authors":"Fabio Leite, P. Antonino, Paulo Barbosa, S. Kemmann, Raphael Mendonca","doi":"10.1109/HealthCom.2014.7001889","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001889","url":null,"abstract":"We have investigated approaches in the literature to assess the quality of the software architectures of medical devices, and have found evidence that there is a lack of methodologies for evaluating the software architecture design aspects of medical devices that might affect system safety. Such evidences were identified when evaluating the software architecture of the FDA Generic Infusion Pump searching for architectural evaluation approaches available in the literature. In order to fill this gap, we propose a set of quality questions that focus on analyzing software architecture design aspects of medical devices aiming safety. We show arguments on why reference projects such as the FDA Generic Infusion Pump system must satisfy our new quality questions. The quality questions were integrated into a quality model commissioned by the Brazilian Health Ministery for the certification of medical devices.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125876122","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001816
C. Hewage, H. D. Appuhami, M. Martini, Ralph Smith, I. Jourdan, T. Rockall
3D medical video was forecasted to be one of the groundbreaking 3D video applications. These range from tele-consultation to 3D robotics surgery. Enabling 3D video in e-health applications results in the provision of more natural viewing conditions, improved diagnosis and accurate interventions in surgical procedures. The deployment of 3D video services in healthcare is made possible to some extent by the advanced capturing devices (e.g., 3D endoscopes), recent advances in wireless communication technologies (e.g., LTE-Advanced(LTE-A)) and 3D video display technologies. Remote robotic assisted surgery and surgery training (education for surgeons) can benefit in particular from 3D video technologies due to the added dimension of depth. This paper analyzes the quality of compressed 3D surgical video. Moreover, asymmetric encoding of 3D medical video without compromising the medical quality of experience (M-QoE) is investigated in this paper. The quality of the compressed 3D medical video with the proposed method is evaluated using a comprehensive subjective quality evaluation test involving 12 medical surgeons. The results show a slightly better perception with the proposed asymmetric coding method compared to reference symmetric compression method, however the difference is statistically insignificant.
{"title":"Quality evaluation of compressed 3D surgical video","authors":"C. Hewage, H. D. Appuhami, M. Martini, Ralph Smith, I. Jourdan, T. Rockall","doi":"10.1109/HealthCom.2014.7001816","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001816","url":null,"abstract":"3D medical video was forecasted to be one of the groundbreaking 3D video applications. These range from tele-consultation to 3D robotics surgery. Enabling 3D video in e-health applications results in the provision of more natural viewing conditions, improved diagnosis and accurate interventions in surgical procedures. The deployment of 3D video services in healthcare is made possible to some extent by the advanced capturing devices (e.g., 3D endoscopes), recent advances in wireless communication technologies (e.g., LTE-Advanced(LTE-A)) and 3D video display technologies. Remote robotic assisted surgery and surgery training (education for surgeons) can benefit in particular from 3D video technologies due to the added dimension of depth. This paper analyzes the quality of compressed 3D surgical video. Moreover, asymmetric encoding of 3D medical video without compromising the medical quality of experience (M-QoE) is investigated in this paper. The quality of the compressed 3D medical video with the proposed method is evaluated using a comprehensive subjective quality evaluation test involving 12 medical surgeons. The results show a slightly better perception with the proposed asymmetric coding method compared to reference symmetric compression method, however the difference is statistically insignificant.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129167216","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001870
N. Larburu, R. Bults, I. Widya, H. Hermens
Clinical decision-support functions of telemedicine systems use patient's monitored clinical data to support treatment of outpatients. However, the quality of monitored clinical data may vary due to performance variations of technological resources inside a deployed telemedicine system. This paper discusses models to compute quality of clinical data affected by quality of service provided by technological resources along the data processing and delivery chain between the point of monitoring and point of decision. We discuss prospective effects of quality of clinical data degradation on outpatient treatment with medical practitioners, and implement these effects in the clinical decision-making process during design time. Consequently, the designed telemedicine system is technological context and quality-aware and preserves patient's safety and treatment efficacy.
{"title":"Quality of data computational models and telemedicine treatment effects","authors":"N. Larburu, R. Bults, I. Widya, H. Hermens","doi":"10.1109/HealthCom.2014.7001870","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001870","url":null,"abstract":"Clinical decision-support functions of telemedicine systems use patient's monitored clinical data to support treatment of outpatients. However, the quality of monitored clinical data may vary due to performance variations of technological resources inside a deployed telemedicine system. This paper discusses models to compute quality of clinical data affected by quality of service provided by technological resources along the data processing and delivery chain between the point of monitoring and point of decision. We discuss prospective effects of quality of clinical data degradation on outpatient treatment with medical practitioners, and implement these effects in the clinical decision-making process during design time. Consequently, the designed telemedicine system is technological context and quality-aware and preserves patient's safety and treatment efficacy.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116663637","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001876
Yuuki Nishiyama, T. Okoshi, Takuro Yonezawa, J. Nakazawa, K. Takashio, H. Tokuda
Recent technological trends on mobile/wearable devices and sensors have been enabling increasing number of people to collect and store their “life-logs” easily in their daily lives. Beyond exercise behavior change of individual user, our research focus is on the behavior change of teams, based on life-logging technologies and information sharing. In this paper, we propose and evaluate six different types of information sharing model among team members for their exercise promotion, leveraging concepts of “competition” and “collaboration”. According to our experimental mobile web application for exercise promotion and extensive user study among 64 total users for three weeks, the model with “external competition” technique resulted the most effective performance for competitive teams such as sport teams.
{"title":"Towards health exercise behavior change for teams using life-logging","authors":"Yuuki Nishiyama, T. Okoshi, Takuro Yonezawa, J. Nakazawa, K. Takashio, H. Tokuda","doi":"10.1109/HealthCom.2014.7001876","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001876","url":null,"abstract":"Recent technological trends on mobile/wearable devices and sensors have been enabling increasing number of people to collect and store their “life-logs” easily in their daily lives. Beyond exercise behavior change of individual user, our research focus is on the behavior change of teams, based on life-logging technologies and information sharing. In this paper, we propose and evaluate six different types of information sharing model among team members for their exercise promotion, leveraging concepts of “competition” and “collaboration”. According to our experimental mobile web application for exercise promotion and extensive user study among 64 total users for three weeks, the model with “external competition” technique resulted the most effective performance for competitive teams such as sport teams.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114262947","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 : 2014-10-01DOI: 10.1109/HEALTHCOM.2014.7001815
Nuno Pombo, N. Garcia, Virginie Felizardo, K. Bousson
The main challenge of big data processing includes the extraction of relevant information, from a high dimensionality of a wide variety of medical data by enabling analysis, discovery and interpretation. These data are a useful tool for helping to understand disease and to formulate predictive models in different areas and support different tasks, such as triage, evaluation of treatment, and monitoring. In this paper, a case study based on a predictive model using the radial basis function neural network (RBFNN) combined with a filtering technique aiming the estimation of electrocardiogram (ECG) waveform is presented. The proposed method revealed it suitability to support health care professionals on clinical decisions and practices.
{"title":"Big data reduction using RBFNN: A predictive model for ECG waveform for eHealth platform integration","authors":"Nuno Pombo, N. Garcia, Virginie Felizardo, K. Bousson","doi":"10.1109/HEALTHCOM.2014.7001815","DOIUrl":"https://doi.org/10.1109/HEALTHCOM.2014.7001815","url":null,"abstract":"The main challenge of big data processing includes the extraction of relevant information, from a high dimensionality of a wide variety of medical data by enabling analysis, discovery and interpretation. These data are a useful tool for helping to understand disease and to formulate predictive models in different areas and support different tasks, such as triage, evaluation of treatment, and monitoring. In this paper, a case study based on a predictive model using the radial basis function neural network (RBFNN) combined with a filtering technique aiming the estimation of electrocardiogram (ECG) waveform is presented. The proposed method revealed it suitability to support health care professionals on clinical decisions and practices.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130357527","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001837
F. Zakaria, C. Toulouse, M. Mohamed el Badaoui, C. Servière, M. Khalil
There have been numerous studies involving research and development, for detecting falls exhibited by the elderly. Considering that the prevention of a falling elderly is much more complex to address and estimate, very little research has been done. In fact research is often strictly limited resourceful medical organizations that have specialized clinical tools. Human locomotion, particularly “Walking” is defined by sequences of cyclic and repeated gestures. The variability of such sequences can reveal information about drive failure and motor / motor-neuron disorders. Studying and exploiting the Cyclostationary (CS) properties of such sequences, offers a complementary way to quantify human locomotion and its changes with progressing aging and the development of diseases. This quantization may provide an insight into the neural function and the neural control of walking which would be altered by changes associated with aging and the presence of certain diseases. As part of the collaboration between LASPI and CHU Saint Etienne, we decided to focus on certain advanced signal processing theory and methods, to study very complex phenomena of human walking, which is often subject to numerous motor and / or motor-neurons malfunctions, such as in the case of the falling elderly population, that often has serious and severe consequences. Furthermore, this paper also examined the effects on walking in elderly subjects in three task conditions: (a) single task (MS) and (b) dual task: walking by performing a fluency task(MF) and (c) walking while backward counting (MD). Results show that the conditions of walking impacted the Cyclostationarity and its known indicator: the cyclic autocorrelation function. Such indicator also evolved between fallers and non-fallers and between the fallers who have history of falls and those who haven't.
已经有大量的研究和开发，用于检测老年人所表现出的跌倒。考虑到老年人摔倒的预防要复杂得多，难以处理和估计，因此做的研究很少。事实上，研究往往受到严格限制，资源丰富的医疗机构有专门的临床工具。人类的运动，特别是“行走”是由一系列循环和重复的手势来定义的。这些序列的可变性可以揭示驱动故障和运动/运动神经元疾病的信息。研究和利用这些序列的循环静止(CS)特性，为量化人类运动及其随年龄增长和疾病发展的变化提供了一种补充方法。这种量化可以为神经功能和行走的神经控制提供一种见解，这些神经功能和神经控制将被与衰老和某些疾病相关的变化所改变。作为LASPI和CHU Saint Etienne之间合作的一部分，我们决定将重点放在某些先进的信号处理理论和方法上，以研究人类行走的非常复杂的现象，这些现象通常受到许多运动和/或运动神经元故障的影响，例如在老年人跌倒的情况下，这通常会产生严重和严重的后果。此外，本文还研究了三种任务条件对老年人行走的影响:(a)单任务(MS)和(b)双任务:通过执行流畅性任务(MF)和(c)边走边倒数(MD)。结果表明，步行条件对循环平稳性及其已知指标循环自相关函数有影响。这一指标在跌倒者和非跌倒者之间以及有跌倒史和没有跌倒史的人之间也会发生变化。
{"title":"Contribution of the cyclic correlation in gait analysis: Variation between fallers and non-fallers","authors":"F. Zakaria, C. Toulouse, M. Mohamed el Badaoui, C. Servière, M. Khalil","doi":"10.1109/HealthCom.2014.7001837","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001837","url":null,"abstract":"There have been numerous studies involving research and development, for detecting falls exhibited by the elderly. Considering that the prevention of a falling elderly is much more complex to address and estimate, very little research has been done. In fact research is often strictly limited resourceful medical organizations that have specialized clinical tools. Human locomotion, particularly “Walking” is defined by sequences of cyclic and repeated gestures. The variability of such sequences can reveal information about drive failure and motor / motor-neuron disorders. Studying and exploiting the Cyclostationary (CS) properties of such sequences, offers a complementary way to quantify human locomotion and its changes with progressing aging and the development of diseases. This quantization may provide an insight into the neural function and the neural control of walking which would be altered by changes associated with aging and the presence of certain diseases. As part of the collaboration between LASPI and CHU Saint Etienne, we decided to focus on certain advanced signal processing theory and methods, to study very complex phenomena of human walking, which is often subject to numerous motor and / or motor-neurons malfunctions, such as in the case of the falling elderly population, that often has serious and severe consequences. Furthermore, this paper also examined the effects on walking in elderly subjects in three task conditions: (a) single task (MS) and (b) dual task: walking by performing a fluency task(MF) and (c) walking while backward counting (MD). Results show that the conditions of walking impacted the Cyclostationarity and its known indicator: the cyclic autocorrelation function. Such indicator also evolved between fallers and non-fallers and between the fallers who have history of falls and those who haven't.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114714507","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001879
M. Schapranow, K. Klinghammer, Cindy Fähnrich, H. Plattner
Latest medical diagnostics generate increasing amounts of big medical data. Specific software tools optimized for the use by healthcare experts and researchers as well as systematic processes for data processing and analysis in clinical and research environments are still missing. Our work focuses on the integration of high-throughput next-generation sequencing data and its systematic processing and its instantaneous analysis to use them in the course of precision medicine. We share our research results on designing a generic research process for drug response analysis including specific software tools built on top of our distributed in-memory computing platform for processing of big medical data. Furthermore, we present our technical foundations as well as process aspects of integrating and combining heterogeneous data sources, such as genome, patient, and experimental data.
{"title":"In-memory technology enables interactive drug response analysis","authors":"M. Schapranow, K. Klinghammer, Cindy Fähnrich, H. Plattner","doi":"10.1109/HealthCom.2014.7001879","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001879","url":null,"abstract":"Latest medical diagnostics generate increasing amounts of big medical data. Specific software tools optimized for the use by healthcare experts and researchers as well as systematic processes for data processing and analysis in clinical and research environments are still missing. Our work focuses on the integration of high-throughput next-generation sequencing data and its systematic processing and its instantaneous analysis to use them in the course of precision medicine. We share our research results on designing a generic research process for drug response analysis including specific software tools built on top of our distributed in-memory computing platform for processing of big medical data. Furthermore, we present our technical foundations as well as process aspects of integrating and combining heterogeneous data sources, such as genome, patient, and experimental data.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123083102","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001871
L. Lianas, F. Frexia, G. Delussu, Paolo Anedda, G. Zanetti
In this work we describe pyEHR, a new toolkit for building scalable clinical/phenotypic data management systems for biomedical research applications. The toolkit uses openEHR formalisms to guarantee the decoupling of clinical data descriptions from implementation details, and NoSQL technologies, or next-generation SQL ones, to provide scalable storage back-ends.
{"title":"pyEHR: A scalable clinical data management toolkit for biomedical research projects","authors":"L. Lianas, F. Frexia, G. Delussu, Paolo Anedda, G. Zanetti","doi":"10.1109/HealthCom.2014.7001871","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001871","url":null,"abstract":"In this work we describe pyEHR, a new toolkit for building scalable clinical/phenotypic data management systems for biomedical research applications. The toolkit uses openEHR formalisms to guarantee the decoupling of clinical data descriptions from implementation details, and NoSQL technologies, or next-generation SQL ones, to provide scalable storage back-ends.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122183689","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：