The electroencephalogram (EEG) signal plays a key role in the diagnosis of epilepsy. Substantial data is generated by the EEG recordings of ambulatory recording systems, and detection of epileptic activity requires a ...The electroencephalogram (EEG) signal plays a key role in the diagnosis of epilepsy. Substantial data is generated by the EEG recordings of ambulatory recording systems, and detection of epileptic activity requires a time-consuming analysis of the complete length of the EEG time series data by a neurology expert. A variety of automatic epilepsy detection systems have been developed during the last ten years. In this paper, we investigate the potential of a recently-proposed statistical measure parameter regarded as Sample Entropy (SampEn), as a method of feature extraction to the task of classifying three different kinds of EEG signals (normal, interictal and ictal) and detecting epileptic seizures. It is known that the value of the SampEn falls suddenly during an epileptic seizure and this fact is utilized in the proposed diagnosis system. Two different kinds of classification models, back-propagation neural network (BPNN) and the recently-developed extreme learning machine (ELM) are tested in this study. Results show that the proposed automatic epilepsy detection system which uses sample entropy (SampEn) as the only input feature, together with extreme learning machine (ELM) classification model, not only achieves high classification accuracy (95.67%) but also very fast speed.展开更多
Artificial intelligence(AI)has been developing rapidly in recent years in terms of software algorithms,hardware implementation,and applications in a vast number of areas.In this review,we summarize the latest developm...Artificial intelligence(AI)has been developing rapidly in recent years in terms of software algorithms,hardware implementation,and applications in a vast number of areas.In this review,we summarize the latest developments of applications of AI in biomedicine,including disease diagnostics,living assistance,biomedical information processing,and biomedical research.The aim of this review is to keep track of new scientific accomplishments,to understand the availability of technologies,to appreciate the tremendous potential of AI in biomedicine,and to provide researchers in related fields with inspiration.It can be asserted that,just like AI itself,the application of AI in biomedicine is still in its early stage.New progress and breakthroughs will continue to push the frontier and widen the scope of AI application,and fast developments are envisioned in the near future.Two case studies are provided to illustrate the prediction of epileptic seizure occurrences and the filling of a dysfunctional urinary bladder.展开更多
目的：探究颞叶难治性癫痫患者致痫灶脑组织中高迁移率族蛋白 B1（HMGB1）及Toll样受体蛋白（TLR4）的表达及意义。方法：选取2011年1月1日至2012年1月1日于郑州大学第五附属医院行“致痫灶切除术”的颞叶难治性癫痫患者85例为实验组，...目的：探究颞叶难治性癫痫患者致痫灶脑组织中高迁移率族蛋白 B1（HMGB1）及Toll样受体蛋白（TLR4）的表达及意义。方法：选取2011年1月1日至2012年1月1日于郑州大学第五附属医院行“致痫灶切除术”的颞叶难治性癫痫患者85例为实验组，术中留取致痫灶脑组织标本；选取同期于该院神经外科行“颅内减压术”的患者20例为对照组，术中留取正常脑组织标本。利用免疫组织化学法检测实验组患者致痫灶脑组织及对照组正常脑组织中HMGB1及其受体TLR4的表达，统计分析患者癫痫发作与致痫灶组织中HMGB1及TLR4表达的关系。结果：实验组患者致痫灶脑组织中HMGB1（χ2＝74．375， P ＝0．000）、TLR4（χ2＝57．495， P ＝0．000）阳性表达率均明显高于正常脑组织；实验组患者致痫灶脑组织中 HMGB1、TLR4表达水平与患者癫痫病程（χ2＝25．798， P ＝0．000）、（χ2＝10．548， P ＝0．001），术前癫痫平均发作时间（χ2＝8．403， P ＝0．004）、（χ2＝10．564， P ＝0．001），术前癫痫发作频率（χ2＝4．912， P ＝0．027）、（χ2＝5．567， P ＝0．018）密切相关。结论：HMGB1-TLR4轴可能成为难治性癫痫发病机制、诊疗研究的新方向。展开更多
Background: The association between prenatal exposure to antiseizure medications (ASM) and autism spectrum disorder has been documented. This study sought to examine and synthesize evidence from studies that have eval...Background: The association between prenatal exposure to antiseizure medications (ASM) and autism spectrum disorder has been documented. This study sought to examine and synthesize evidence from studies that have evaluated these associations, with particular focus on the trimester of pregnancy and dosage of exposure. Methodology: PubMed, Embase, and PsycINFO databases were searched following strict inclusion/exclusion criteria. 10 studies were recruited involving children born to mothers with epilepsy who took ASM during pregnancy as cases, and those with epilepsy who did not take any ASM in pregnancy. Results: The relative risk of developing ASD among children exposed to valproic acid (RR, 3.90 [95% CI: 2.36 - 6.44], p < 0.006), was twice higher than that of carbamazepine (RR, 1.65 [95% CI: 0.62 - 4.37], p < 0.0001), or lamotrigine (RR, 1.60 [95% CI: 0.77 - 3.32], p = 0.006). The trimester of exposure and dosage of ASM administered were not significant. Conclusion: In summary, prenatal exposure to ASM increased the risk of developing ASD in children. The relative risk was twice as high in those exposed to valproic acid compared to those exposed to carbamazepine or lamotrigine. Trimester of pregnancy and dosage of ASM used by the mothers were not significant.展开更多
Presently,we develop a simplified corticothalamic(SCT)model and propose a single-pulse alternately resetting stimulation(SARS)with sequentially applying anodic(A,“+”)or cathodic(C,“−”)phase pulses to the thalamic ...Presently,we develop a simplified corticothalamic(SCT)model and propose a single-pulse alternately resetting stimulation(SARS)with sequentially applying anodic(A,“+”)or cathodic(C,“−”)phase pulses to the thalamic reticular(RE)nuclei,thalamus-cortex(TC)relay nuclei,and cortical excitatory(EX)neurons,respectively.Abatement effects of ACC-SARS of RE,TC,and EX for the 2 Hz-4 Hz spike and wave discharges(SWD)of absence seizures are then concerned.The m∶n on-off ACC-SARS protocol is shown to effectively reduce the SWD with the least current consumption.In particular,when its frequency is out of the 2 Hz-4 Hz SWD dominant rhythm,the desired seizure abatements can be obtained,which can be further improved by our proposed directional steering(DS)stimulation.The dynamical explanations for the SARS induced seizure abatements are lastly given by calculating the averaged mean firing rate(AMFR)of neurons and triggering averaged mean firing rates(TAMFRs)of 2 Hz-4 Hz SWD.展开更多
文摘The electroencephalogram (EEG) signal plays a key role in the diagnosis of epilepsy. Substantial data is generated by the EEG recordings of ambulatory recording systems, and detection of epileptic activity requires a time-consuming analysis of the complete length of the EEG time series data by a neurology expert. A variety of automatic epilepsy detection systems have been developed during the last ten years. In this paper, we investigate the potential of a recently-proposed statistical measure parameter regarded as Sample Entropy (SampEn), as a method of feature extraction to the task of classifying three different kinds of EEG signals (normal, interictal and ictal) and detecting epileptic seizures. It is known that the value of the SampEn falls suddenly during an epileptic seizure and this fact is utilized in the proposed diagnosis system. Two different kinds of classification models, back-propagation neural network (BPNN) and the recently-developed extreme learning machine (ELM) are tested in this study. Results show that the proposed automatic epilepsy detection system which uses sample entropy (SampEn) as the only input feature, together with extreme learning machine (ELM) classification model, not only achieves high classification accuracy (95.67%) but also very fast speed.
基金the Startup Research Fund of Westlake University(041030080118)the Research Fund of Westlake Universitythe Bright Dream Joint Institute for Intelligent Robotics(10318H991901).
文摘Artificial intelligence(AI)has been developing rapidly in recent years in terms of software algorithms,hardware implementation,and applications in a vast number of areas.In this review,we summarize the latest developments of applications of AI in biomedicine,including disease diagnostics,living assistance,biomedical information processing,and biomedical research.The aim of this review is to keep track of new scientific accomplishments,to understand the availability of technologies,to appreciate the tremendous potential of AI in biomedicine,and to provide researchers in related fields with inspiration.It can be asserted that,just like AI itself,the application of AI in biomedicine is still in its early stage.New progress and breakthroughs will continue to push the frontier and widen the scope of AI application,and fast developments are envisioned in the near future.Two case studies are provided to illustrate the prediction of epileptic seizure occurrences and the filling of a dysfunctional urinary bladder.
文摘目的：探究颞叶难治性癫痫患者致痫灶脑组织中高迁移率族蛋白 B1（HMGB1）及Toll样受体蛋白（TLR4）的表达及意义。方法：选取2011年1月1日至2012年1月1日于郑州大学第五附属医院行“致痫灶切除术”的颞叶难治性癫痫患者85例为实验组，术中留取致痫灶脑组织标本；选取同期于该院神经外科行“颅内减压术”的患者20例为对照组，术中留取正常脑组织标本。利用免疫组织化学法检测实验组患者致痫灶脑组织及对照组正常脑组织中HMGB1及其受体TLR4的表达，统计分析患者癫痫发作与致痫灶组织中HMGB1及TLR4表达的关系。结果：实验组患者致痫灶脑组织中HMGB1（χ2＝74．375， P ＝0．000）、TLR4（χ2＝57．495， P ＝0．000）阳性表达率均明显高于正常脑组织；实验组患者致痫灶脑组织中 HMGB1、TLR4表达水平与患者癫痫病程（χ2＝25．798， P ＝0．000）、（χ2＝10．548， P ＝0．001），术前癫痫平均发作时间（χ2＝8．403， P ＝0．004）、（χ2＝10．564， P ＝0．001），术前癫痫发作频率（χ2＝4．912， P ＝0．027）、（χ2＝5．567， P ＝0．018）密切相关。结论：HMGB1-TLR4轴可能成为难治性癫痫发病机制、诊疗研究的新方向。
文摘Background: The association between prenatal exposure to antiseizure medications (ASM) and autism spectrum disorder has been documented. This study sought to examine and synthesize evidence from studies that have evaluated these associations, with particular focus on the trimester of pregnancy and dosage of exposure. Methodology: PubMed, Embase, and PsycINFO databases were searched following strict inclusion/exclusion criteria. 10 studies were recruited involving children born to mothers with epilepsy who took ASM during pregnancy as cases, and those with epilepsy who did not take any ASM in pregnancy. Results: The relative risk of developing ASD among children exposed to valproic acid (RR, 3.90 [95% CI: 2.36 - 6.44], p < 0.006), was twice higher than that of carbamazepine (RR, 1.65 [95% CI: 0.62 - 4.37], p < 0.0001), or lamotrigine (RR, 1.60 [95% CI: 0.77 - 3.32], p = 0.006). The trimester of exposure and dosage of ASM administered were not significant. Conclusion: In summary, prenatal exposure to ASM increased the risk of developing ASD in children. The relative risk was twice as high in those exposed to valproic acid compared to those exposed to carbamazepine or lamotrigine. Trimester of pregnancy and dosage of ASM used by the mothers were not significant.
基金Project supported by the National Natural Science Foundation of China(Nos.11702018,11932003,and 11672074)。
文摘Presently,we develop a simplified corticothalamic(SCT)model and propose a single-pulse alternately resetting stimulation(SARS)with sequentially applying anodic(A,“+”)or cathodic(C,“−”)phase pulses to the thalamic reticular(RE)nuclei,thalamus-cortex(TC)relay nuclei,and cortical excitatory(EX)neurons,respectively.Abatement effects of ACC-SARS of RE,TC,and EX for the 2 Hz-4 Hz spike and wave discharges(SWD)of absence seizures are then concerned.The m∶n on-off ACC-SARS protocol is shown to effectively reduce the SWD with the least current consumption.In particular,when its frequency is out of the 2 Hz-4 Hz SWD dominant rhythm,the desired seizure abatements can be obtained,which can be further improved by our proposed directional steering(DS)stimulation.The dynamical explanations for the SARS induced seizure abatements are lastly given by calculating the averaged mean firing rate(AMFR)of neurons and triggering averaged mean firing rates(TAMFRs)of 2 Hz-4 Hz SWD.
