A5014969027- EEG and Brain-Computer Interfaces
- Alzheimer's disease research and treatments
- Bioinformatics and Genomic Networks
- Dementia and Cognitive Impairment Research
- Structural Health Monitoring Techniques
- Muscle activation and electromyography studies
- Concrete Corrosion and Durability
- ECG Monitoring and Analysis
- Neuroscience and Neural Engineering
- Advanced Battery Technologies Research
- Stroke Rehabilitation and Recovery
Amsterdam University Medical Centers
2021-2023
University of Amsterdam
2022-2023
Amsterdam Neuroscience
2023
Evaluate the effect of artifact rejection on performance a Convolutional Neural Network (CNN) based algorithm for classification abnormal and normal electroencephalography (EEG) data. We developed an automated CNN-based clean versus applied this to EEG Additionally, algorithms were with without beforehand. For each algorithm, five CNNs trained using 5-fold cross-validation majority vote these was used test compared bootstrap accuracies number training epochs required between scenario in...
To develop an artificial neural network (ANN) for classification of motor unit action potential (MUAP) duration in real-word, unselected and uncleaned needle electromyography (n-EMG) recordings.
Abstract Background In dementia with Lewy bodies (DLB), Alzheimer co‐pathology is common, and associated an unfavorable prognosis. For targeted treatment development it crucial to understand the biological underpinnings of DLB co‐pathology, how differs from disease (AD). We performed a cerebrospinal fluid (CSF) proteome profiling biologically characterize without AD in vivo . Method Patients Amsterdam Dementia Cohort, Twin60+, UPENN, we selected individuals (n=109), subcategorized them CSF...
Objective: Evaluate the effect of artifact rejection on performance a Convolutional Neural Network (CNN) based algorithm for classification abnormal and normal electroencephalography (EEG) data.Methods: We developed an automated CNN-based clean versus applied this to EEG data. Additionally, algorithms were with without beforehand. For each algorithm, five CNNs trained using 5-fold cross-validation majority vote these was used test compared bootstrap accuracies number training epochs required...
Abstract Background In dementia with Lewy bodies (DLB), amyloid co‐pathology is common and associated an unfavorable prognosis. For targeted treatment development for DLB, we need to establish 1) whether the presence of marks co‐occurring Alzheimer disease (AD), 2) how DLB differs from without amyloid. We employ proteomics in cerebrospinal fluid (CSF), established method assess biological dysregulation vivo , characterization pathology. Method selected individuals ADC UPENN cohorts,...