標(biāo)題: Titlebook: Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders; M. Murugappan,Yuvaraj Rajamanickam Book 2022 The Editor(s) ( [打印本頁] 作者: Coronary-Artery 時(shí)間: 2025-3-21 19:41
書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders影響因子(影響力)
書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders影響因子(影響力)學(xué)科排名
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書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders被引頻次
書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders被引頻次學(xué)科排名
書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders年度引用
書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders年度引用學(xué)科排名
書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders讀者反饋
書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders讀者反饋學(xué)科排名
作者: Arthropathy 時(shí)間: 2025-3-21 21:41
Book 2022a key role in detecting neurological abnormalities and improving diagnosis and treatment consistency in medicine. This book covers different aspects of biomedical signals-based systems used in the automatic detection/identification of neurological disorders. Several biomedical signals are introduced作者: 改良 時(shí)間: 2025-3-22 02:13
Book 2022t explains the role of the CAD system in processing biomedical signals and the application to neurological disorder diagnosis. The book provides the basics of biomedical signal processing, optimization methods, and machine learning/deep learning techniques used in designing CAD systems for neurological disorders..作者: 手術(shù)刀 時(shí)間: 2025-3-22 06:07
M. Murugappan,Yuvaraj RajamanickamPresents the concepts of CAD for various neurological disorders;.Covers biomedical signal processing and machine learning/deep learning techniques;.Includes case studies, real-time examples, and resea作者: 鍍金 時(shí)間: 2025-3-22 11:55
http://image.papertrans.cn/b/image/188096.jpg作者: 你正派 時(shí)間: 2025-3-22 13:38 作者: erythema 時(shí)間: 2025-3-22 18:05
978-3-030-97847-1The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: MAOIS 時(shí)間: 2025-3-23 00:22
https://doi.org/10.1007/978-81-322-1976-7phalogram (EEG). Identifying an abnormal EEG serves as a preliminary indicator before specialized testing to determine the neurological disorder. Traditional identification methods involve manual perusal of the EEG signals. This method is relatively slow and tedious, requires trained neurologists, a作者: Modicum 時(shí)間: 2025-3-23 03:58 作者: 灌輸 時(shí)間: 2025-3-23 07:56 作者: Somber 時(shí)間: 2025-3-23 12:59
Ahmad Martadha Mohamed,Zahrul Akmal DaminSD prior to their onset. As a result, developing an alarm system assists caregivers, doctors and therapists in preventing such aggressive behaviours before they occur. Only a few studies have studied the physiological markers in ASD children and adults. The Pan-Tompkins equation was used to determin作者: Pillory 時(shí)間: 2025-3-23 15:28
Ahmad Martadha Mohamed,Zahrul Akmal Damins of motor, sensory, or psychic dysfunction. Tonic-clonic seizure (TCSZ), a type of electroclinical seizure, has a high risk of injury due to the convulsions. Video EEG is an essential tool, employed in the hospitals for the identification of those seizures. This is not practical outside the clinica作者: jumble 時(shí)間: 2025-3-23 20:25 作者: 拉開這車床 時(shí)間: 2025-3-24 00:45 作者: 爭(zhēng)論 時(shí)間: 2025-3-24 05:38
https://doi.org/10.1007/978-981-15-5266-3ous entropy measures have been developed from both theoretical and experimental perspectives. Approximate entropy and Shannon entropy are basic entropy measures that have been successfully applied to various biomedical data. However, these measures have some drawbacks, such as sensitivity to data le作者: vocation 時(shí)間: 2025-3-24 08:00
Land and Housing Controversies in Hong Kongbe made more efficient by using deep learning which can automatically extract effective features. In this work, a 2D convolutional neural network-gated recurrent unit (CNN-GRU) hybrid model is proposed to perform binary, ternary, and quinary classification on the University of Bonn epilepsy database作者: 一瞥 時(shí)間: 2025-3-24 12:07
Land and Housing Controversies in Hong Konged to automate the final diagnosis step but for the design of sensors, the preprocessing unit, and the processing unit as well. Today, it is an essential requirement that these CAD systems have low latency and low power consumption, which is not possible using a traditional software-based system tha作者: 貪婪的人 時(shí)間: 2025-3-24 17:49
https://doi.org/10.1007/978-981-15-5266-3ent losing the capability of controlling his/her actions. Besides being prone to injuries, losing consciousness, and control of the body, patients have a higher risk of experiencing sudden unexpected death in epilepsy (SUDEP). Therefore, continuous multimodal monitoring using electrodermal activity 作者: 喧鬧 時(shí)間: 2025-3-24 20:56 作者: 災(zāi)禍 時(shí)間: 2025-3-24 23:32 作者: 誘騙 時(shí)間: 2025-3-25 05:03 作者: 事物的方面 時(shí)間: 2025-3-25 08:57 作者: 混雜人 時(shí)間: 2025-3-25 15:03
Hilbert Huang Transform (HHT) Analysis of Heart Rate Variability (HRV) in Recognition of Emotion inSD prior to their onset. As a result, developing an alarm system assists caregivers, doctors and therapists in preventing such aggressive behaviours before they occur. Only a few studies have studied the physiological markers in ASD children and adults. The Pan-Tompkins equation was used to determin作者: congenial 時(shí)間: 2025-3-25 19:35
Detection of Tonic-Clonic Seizures Using Scalp EEG of Spectral Moments,s of motor, sensory, or psychic dysfunction. Tonic-clonic seizure (TCSZ), a type of electroclinical seizure, has a high risk of injury due to the convulsions. Video EEG is an essential tool, employed in the hospitals for the identification of those seizures. This is not practical outside the clinica作者: 必死 時(shí)間: 2025-3-25 22:35 作者: Amplify 時(shí)間: 2025-3-26 00:36
A Novel Parametric Nonstationary Signal Model for EEG Signals and Its Application in Epileptic Seizification. The EEG signals are considered as signatures of neural activities and represent the electrical activity inside the brain. The EEG signals are considered predominantly nonlinear and nonstationary in nature; thus, obtaining meaningful inferences from the EEG signal has been a strenuous task作者: Fibroid 時(shí)間: 2025-3-26 05:32
Biomedical Signal Analysis Using Entropy Measures: A Case Study of Motor Imaginary BCI in End Usersous entropy measures have been developed from both theoretical and experimental perspectives. Approximate entropy and Shannon entropy are basic entropy measures that have been successfully applied to various biomedical data. However, these measures have some drawbacks, such as sensitivity to data le作者: Patrimony 時(shí)間: 2025-3-26 11:53 作者: aspersion 時(shí)間: 2025-3-26 13:28
Catalogic Systematic Literature Review of Hardware-Accelerated Neurodiagnostic Systems,ed to automate the final diagnosis step but for the design of sensors, the preprocessing unit, and the processing unit as well. Today, it is an essential requirement that these CAD systems have low latency and low power consumption, which is not possible using a traditional software-based system tha作者: 未成熟 時(shí)間: 2025-3-26 18:54
Wearable Real-Time Epileptic Seizure Detection and Warning System,ent losing the capability of controlling his/her actions. Besides being prone to injuries, losing consciousness, and control of the body, patients have a higher risk of experiencing sudden unexpected death in epilepsy (SUDEP). Therefore, continuous multimodal monitoring using electrodermal activity 作者: obviate 時(shí)間: 2025-3-26 22:42
Analysis of Intramuscular Coherence of Lower Limb Muscle Activities Using Magnitude Squared Coherenning about the central nervous system’s techniques for controlling motor task execution. The main aim of this study was to compare the intramuscular coherence of lower limb muscles during the various tasks. The study utilized a publicly available full-body mobile brain-body imaging database for the 作者: 執(zhí)拗 時(shí)間: 2025-3-27 03:54
Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders作者: 我正派 時(shí)間: 2025-3-27 08:57 作者: 羅盤 時(shí)間: 2025-3-27 10:28
to neurological disorder diagnosis. The book provides the basics of biomedical signal processing, optimization methods, and machine learning/deep learning techniques used in designing CAD systems for neurological disorders..978-3-030-97847-1978-3-030-97845-7作者: 混雜人 時(shí)間: 2025-3-27 17:28
Abnormal EEG Detection Using Time-Frequency Images and Convolutional Neural Network,figurable CNN structures, namely, DenseNet, SeizureNet, and Inception-ResNet-V2, to extract deep learned features. Finally, an extreme learning machine (ELM)-based classifier detects the input TF images. The proposed STFT-based CNN method is evaluated using the Temple University Hospital (TUH) abnor作者: 序曲 時(shí)間: 2025-3-27 21:28
Physical Action Categorization Pertaining to Certain Neurological Disorders Using Machine Learning- of life for such patients or providing better treatment. The framework makes use of various features from various signal signatures with contribution from time domain, frequency domain, and inter-channel statistics. Next, we conducted a comparative analysis of SVM, 3-NN, and ensemble learning with 作者: Munificent 時(shí)間: 2025-3-27 22:49
A Comparative Study on EEG Features for Neonatal Seizure Detection,as analyzed using XGBoost and support vector machine (SVM) classifier with fourfold cross-validation. We found that entropy plays a significant role in the discrimination of seizure and non-seizure segments. We achieved an average AUC of 0.84 and 0.76 using XGBoost and SVM classifiers, respectively.作者: 令人不快 時(shí)間: 2025-3-28 03:05 作者: Virtues 時(shí)間: 2025-3-28 09:26 作者: NUL 時(shí)間: 2025-3-28 11:05
Investigation of the Brain Activation Pattern of Stroke Patients and Healthy Individuals During Hap Complexity parameters were lower in LBD and RBD in the frontal regions of the alpha band. The significant difference channels between the emotions were analyzed by statistical analysis using ANOVA. Moreover, the features of each subject group were used for emotion classification by the application 作者: 圍裙 時(shí)間: 2025-3-28 18:10
A Novel Parametric Nonstationary Signal Model for EEG Signals and Its Application in Epileptic Seiz extracting the low-frequency average component, while the three-peak cluster in the frequency domain has been used for segmenting the EEG signals in order to capture its instantaneous parameters. The study has been done on the publicly available EEG database of the University of Bonn. Our study sug作者: 新奇 時(shí)間: 2025-3-28 21:25 作者: mutineer 時(shí)間: 2025-3-29 01:30 作者: 在前面 時(shí)間: 2025-3-29 05:45
Catalogic Systematic Literature Review of Hardware-Accelerated Neurodiagnostic Systems,te array (FPGA), allowing rapid testing and deployment of hardware systems. Moreover, the novel neuromorphic platform has the potential to efficiently accelerate neural networks as well, which was not possible with the FPGA..In this chapter, we conduct a systematic review of hardware-accelerated neu作者: exostosis 時(shí)間: 2025-3-29 08:36
Wearable Real-Time Epileptic Seizure Detection and Warning System,body were sent continuously to the detection and warning subsystem, where it was continuously processed and analyzed. The later block can also automatically alert the parent/caregiver of the patient over the cellular network in case of a seizure event. Among the various machine learning algorithms, 作者: macrophage 時(shí)間: 2025-3-29 13:05
Analysis of Intramuscular Coherence of Lower Limb Muscle Activities Using Magnitude Squared Coherent 1000?Hz, and it was recorded from six sites bilaterally: tibialis anterior (TA), medial gastrocnemius (MG), vastus lateralis (VL), rectus femoris (RF), semitendinosus (ST), and biceps femoris longus (BFL). In this study, we have analyzed different lower limb muscle pairs such as TA-MG, TA-VL, and 作者: 清唱?jiǎng)?nbsp; 時(shí)間: 2025-3-29 19:13
