Pub Date : 2016-10-01DOI: 10.1109/HLDVT.2016.7748261
D. Venuto, V. Annese, G. Mezzina, M. Ruta, E. Sciascio
This paper proposes a novel mobile healthcare system for remotely monitoring neuro-cognitive functions of impaired subjects and proposing possible treatments. Currently, only hospital centers perform similar analyses through fixed and wired electroencephalography (EEG) inspection. The solution proposed here works wirelessly and improves its accuracy learning by performances of the subject playing a game/test. The system is based on spatio-temporal detection and characterization of a specific brain potential named P300. It includes: i) a wearable wireless EEG device; ii) a gateway (tablet or smartphone) processing gathered data, also providing the test/game to the user. Given the above hardware settings, a new algorithm, named tuned-Residue Iteration Decomposition (t-RIDE), provides spatiotemporal features of P300s and a semantic-based reasoner allows taking into account factors which could modify the test if performed in non-standard conditions. The system has been adopted with 12 subjects involved in three different cognitive tasks with increasing difficulty. Fast diagnosis of cognitive deficits is reached, including mild and heavy impairments cases: t-RIDE processing is performed in 1.95s (after 79 iterations for convergence) whereas semantic matchmaking routine requires 2.5ms in the worst case. A case study for an Alzheimer injured patient is reported to corroborate and clarify the proposed approach.
{"title":"Brain-computer interface using P300: a gaming approach for neurocognitive impairment diagnosis","authors":"D. Venuto, V. Annese, G. Mezzina, M. Ruta, E. Sciascio","doi":"10.1109/HLDVT.2016.7748261","DOIUrl":"https://doi.org/10.1109/HLDVT.2016.7748261","url":null,"abstract":"This paper proposes a novel mobile healthcare system for remotely monitoring neuro-cognitive functions of impaired subjects and proposing possible treatments. Currently, only hospital centers perform similar analyses through fixed and wired electroencephalography (EEG) inspection. The solution proposed here works wirelessly and improves its accuracy learning by performances of the subject playing a game/test. The system is based on spatio-temporal detection and characterization of a specific brain potential named P300. It includes: i) a wearable wireless EEG device; ii) a gateway (tablet or smartphone) processing gathered data, also providing the test/game to the user. Given the above hardware settings, a new algorithm, named tuned-Residue Iteration Decomposition (t-RIDE), provides spatiotemporal features of P300s and a semantic-based reasoner allows taking into account factors which could modify the test if performed in non-standard conditions. The system has been adopted with 12 subjects involved in three different cognitive tasks with increasing difficulty. Fast diagnosis of cognitive deficits is reached, including mild and heavy impairments cases: t-RIDE processing is performed in 1.95s (after 79 iterations for convergence) whereas semantic matchmaking routine requires 2.5ms in the worst case. A case study for an Alzheimer injured patient is reported to corroborate and clarify the proposed approach.","PeriodicalId":166427,"journal":{"name":"2016 IEEE International High Level Design Validation and Test Workshop (HLDVT)","volume":"30 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117048910","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 : 2016-10-01DOI: 10.1109/HLDVT.2016.7748272
Md. Ariful Islam, Qinsi Wang, Ramin M. Hasani, Ondrej Balun, E. Clarke, R. Grosu, S. Smolka
We present a probabilistic reachability analysis of a (nonlinear ODE) model of a neural circuit in Caeorhabditis elegans (C. elegans), the common roundworm. In particular, we consider Tap Withdrawal (TW), a reflexive behavior exhibited by a C. elegans worm in response to vibrating the surface on which it is moving. The neural circuit underlying this response is the subject of this investigation. Specially, we perform bounded-time reachability analysis on the TW circuit model of Wicks et al. (1996) to estimate the probability of various TW responses. The Wicks et al. model has a number of parameters, and we demonstrate that the various TW responses and their probability of occurrence in a population of worms can be viewed as a problem of parameter uncertainty. Our approach to this problem rests on encoding each TW response as a hybrid automaton with parametric uncertainty. We then perform probabilistic reachability analysis on these automata using a technique that combines a δ-decision procedure with statistical tests. The results we obtain are a significant extension of those of Wicks et al. (1996), who equip their model with fixed parameter values that reproduce a single TW response. In contrast, our technique allow us to more thoroughly explore the models parameter space using statistical sampling theory, identifying in the process the distribution of TW responses. Wicks et al. conducted a number of ablation experiments on a population of worms in which one or more of the neurons in the TW circuit are surgically ablated (removed). We show that our technique can be used to correctly estimate TW response-probabilities for four of these ablation groups. We also use our technique to predict TW response behavior for two ablation groups not previously considered by Wicks et al.
{"title":"Probabilistic reachability analysis of the tap withdrawal circuit in caenorhabditis elegans","authors":"Md. Ariful Islam, Qinsi Wang, Ramin M. Hasani, Ondrej Balun, E. Clarke, R. Grosu, S. Smolka","doi":"10.1109/HLDVT.2016.7748272","DOIUrl":"https://doi.org/10.1109/HLDVT.2016.7748272","url":null,"abstract":"We present a probabilistic reachability analysis of a (nonlinear ODE) model of a neural circuit in Caeorhabditis elegans (C. elegans), the common roundworm. In particular, we consider Tap Withdrawal (TW), a reflexive behavior exhibited by a C. elegans worm in response to vibrating the surface on which it is moving. The neural circuit underlying this response is the subject of this investigation. Specially, we perform bounded-time reachability analysis on the TW circuit model of Wicks et al. (1996) to estimate the probability of various TW responses. The Wicks et al. model has a number of parameters, and we demonstrate that the various TW responses and their probability of occurrence in a population of worms can be viewed as a problem of parameter uncertainty. Our approach to this problem rests on encoding each TW response as a hybrid automaton with parametric uncertainty. We then perform probabilistic reachability analysis on these automata using a technique that combines a δ-decision procedure with statistical tests. The results we obtain are a significant extension of those of Wicks et al. (1996), who equip their model with fixed parameter values that reproduce a single TW response. In contrast, our technique allow us to more thoroughly explore the models parameter space using statistical sampling theory, identifying in the process the distribution of TW responses. Wicks et al. conducted a number of ablation experiments on a population of worms in which one or more of the neurons in the TW circuit are surgically ablated (removed). We show that our technique can be used to correctly estimate TW response-probabilities for four of these ablation groups. We also use our technique to predict TW response behavior for two ablation groups not previously considered by Wicks et al.","PeriodicalId":166427,"journal":{"name":"2016 IEEE International High Level Design Validation and Test Workshop (HLDVT)","volume":"13 22","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113979948","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 : 2016-10-01DOI: 10.1109/HLDVT.2016.7748260
Houssam Abbas, Zhihao Jiang, Kuk Jin Jang, M. Beccani, J. Liang, R. Mangharam
Medical devices like the Implantable Cardioverter Defibrillator (ICD) are life-critical systems. Malfunctions of the device can cause serious injury or death of the patient. In addition to rigorous testing and verification during the development process, new medical devices often go through clinical trials to evaluate their safety and performance on sample populations. Clinical trials are costly and prone to failure if not planned and executed properly. Evaluating devices on computer models of the relevant physiological systems can provide helpful insights into the safety and efficacy of the device, thus helping to plan and execute a clinical trial. In this paper, we demonstrate how to develop high-level physiological models of cardiac electrophysiology and how to apply them to the Rhythm ID Head to Head Trial (RIGHT), a 5-year long clinical trial for comparing two ICDs. We refer to this as a Computer-Aided Clinical Trial (CACT). We explored two modeling options, a white-box model capturing the mechanisms of the physiological behaviors, and a blackbox model which uses machine learning methods to synthesize physiological input signals. Both models were able to generate physiological inputs to the ICDs and we discuss the challenges and appropriateness of the two modeling options.
{"title":"High-level modeling for computer-aided clinical trials of medical devices","authors":"Houssam Abbas, Zhihao Jiang, Kuk Jin Jang, M. Beccani, J. Liang, R. Mangharam","doi":"10.1109/HLDVT.2016.7748260","DOIUrl":"https://doi.org/10.1109/HLDVT.2016.7748260","url":null,"abstract":"Medical devices like the Implantable Cardioverter Defibrillator (ICD) are life-critical systems. Malfunctions of the device can cause serious injury or death of the patient. In addition to rigorous testing and verification during the development process, new medical devices often go through clinical trials to evaluate their safety and performance on sample populations. Clinical trials are costly and prone to failure if not planned and executed properly. Evaluating devices on computer models of the relevant physiological systems can provide helpful insights into the safety and efficacy of the device, thus helping to plan and execute a clinical trial. In this paper, we demonstrate how to develop high-level physiological models of cardiac electrophysiology and how to apply them to the Rhythm ID Head to Head Trial (RIGHT), a 5-year long clinical trial for comparing two ICDs. We refer to this as a Computer-Aided Clinical Trial (CACT). We explored two modeling options, a white-box model capturing the mechanisms of the physiological behaviors, and a blackbox model which uses machine learning methods to synthesize physiological input signals. Both models were able to generate physiological inputs to the ICDs and we discuss the challenges and appropriateness of the two modeling options.","PeriodicalId":166427,"journal":{"name":"2016 IEEE International High Level Design Validation and Test Workshop (HLDVT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134147859","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 : 2016-10-01DOI: 10.1109/HLDVT.2016.7748267
M. Kebaili, Jean-Christophe Brignone, K. Morin-Allory
In the context of industrial designs, circuits are based on many IPs defined on their own clock domain. It leads to globally asynchronous locally synchronous designs. The transmission of data between clock domains must be carefully verified to avoid metastability, inconsistency and data loss. EDA tools propose a strategy based on a minimal detection of a synchronizer structure. Conversely, in this paper we propose a meta-model of synchronizer that speeds up the proof and ensures its better automation.
{"title":"Clock domain crossing formal verification: a meta-model","authors":"M. Kebaili, Jean-Christophe Brignone, K. Morin-Allory","doi":"10.1109/HLDVT.2016.7748267","DOIUrl":"https://doi.org/10.1109/HLDVT.2016.7748267","url":null,"abstract":"In the context of industrial designs, circuits are based on many IPs defined on their own clock domain. It leads to globally asynchronous locally synchronous designs. The transmission of data between clock domains must be carefully verified to avoid metastability, inconsistency and data loss. EDA tools propose a strategy based on a minimal detection of a synchronizer structure. Conversely, in this paper we propose a meta-model of synchronizer that speeds up the proof and ensures its better automation.","PeriodicalId":166427,"journal":{"name":"2016 IEEE International High Level Design Validation and Test Workshop (HLDVT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133406667","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 : 2016-10-01DOI: 10.1109/HLDVT.2016.7748264
M. Lora, S. Vinco, F. Fummi
This paper proposes a meet-in-the-middle approach for the modeling and simulation of heterogeneous systems. The starting point is a set of heterogeneous models, developed by adopting the designer's favorite design language and formalism. The methodology exploits automatic translation, abstraction and integration flows to generate a single homogeneous system-level description, that allows fast system simulation. The approach is supported by two novel design domain/abstraction level taxonomies, that generalize a state-of the art taxonomy to identify what characteristics would allow efficient system-level simulation, together with the transformations that must be applied to the starting model to achieve them. The advantage of the approach on system design and prototyping is particularly evident on any kind of highly heterogeneous systems, such as smart systems. The overall automatic flow has been implemented and applied to an open-source case study to measure the performance of each identified abstraction level, and the impact of the proposed methodology.
{"title":"A unifying flow to ease smart systems integration","authors":"M. Lora, S. Vinco, F. Fummi","doi":"10.1109/HLDVT.2016.7748264","DOIUrl":"https://doi.org/10.1109/HLDVT.2016.7748264","url":null,"abstract":"This paper proposes a meet-in-the-middle approach for the modeling and simulation of heterogeneous systems. The starting point is a set of heterogeneous models, developed by adopting the designer's favorite design language and formalism. The methodology exploits automatic translation, abstraction and integration flows to generate a single homogeneous system-level description, that allows fast system simulation. The approach is supported by two novel design domain/abstraction level taxonomies, that generalize a state-of the art taxonomy to identify what characteristics would allow efficient system-level simulation, together with the transformations that must be applied to the starting model to achieve them. The advantage of the approach on system design and prototyping is particularly evident on any kind of highly heterogeneous systems, such as smart systems. The overall automatic flow has been implemented and applied to an open-source case study to measure the performance of each identified abstraction level, and the impact of the proposed methodology.","PeriodicalId":166427,"journal":{"name":"2016 IEEE International High Level Design Validation and Test Workshop (HLDVT)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132679247","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 : 2016-10-01DOI: 10.1109/HLDVT.2016.7748271
Nataša Miškov-Živanov, P. Zuliani, Qinsi Wang, E. Clarke, J. Faeder
We use computational modeling and formal analysis techniques to study temporal behavior of a discrete logical model of the naïve T cell differentiation. The model is analyzed formally and automatically by performing temporal logic queries via statistical model checking. While the model can be verified and then further explored using Monte Carlo simulations, model checking allows for much more efficient analysis by testing a large set of system properties, with much smaller runtime than the one required by simulations. The results obtained using model checking provide details about relative timing of events in the system, which would otherwise be very cumbersome and time consuming to obtain through simulations only. We efficiently test a large number of properties, and confirm or reject hypotheses that were drawn from previous analysis of experimental and simulation data.
{"title":"High-level modeling and verification of cellular signaling","authors":"Nataša Miškov-Živanov, P. Zuliani, Qinsi Wang, E. Clarke, J. Faeder","doi":"10.1109/HLDVT.2016.7748271","DOIUrl":"https://doi.org/10.1109/HLDVT.2016.7748271","url":null,"abstract":"We use computational modeling and formal analysis techniques to study temporal behavior of a discrete logical model of the naïve T cell differentiation. The model is analyzed formally and automatically by performing temporal logic queries via statistical model checking. While the model can be verified and then further explored using Monte Carlo simulations, model checking allows for much more efficient analysis by testing a large set of system properties, with much smaller runtime than the one required by simulations. The results obtained using model checking provide details about relative timing of events in the system, which would otherwise be very cumbersome and time consuming to obtain through simulations only. We efficiently test a large number of properties, and confirm or reject hypotheses that were drawn from previous analysis of experimental and simulation data.","PeriodicalId":166427,"journal":{"name":"2016 IEEE International High Level Design Validation and Test Workshop (HLDVT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130623795","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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