A sample code of data augmentation methods for wearable sensor data (time-series data)
Repository for bachelor thesis on Automatic Multi-Modal Detection of Autonomic Arousals in Sleep. The thesis itself and all related data is confidential and thus not publicly available, but access to the thesis can be granted by sending a request to hello@nicklashansen.com.
Detection of Obstructive Sleep Apnea using Heart Rate Variability in ECG Signals using the Time Domain and Frequency Domain methods and Classification is done using SVM(Support Vector Machines) and K-Means Clustering.
sleep apnea, time window, artificial neural network, time series, MLP
Obstructive Sleep Apnea, OSA, CNN, ECG signal, LeNet5
Automatic sleep stage classification using features extracted from ECG data from the polysomnographic ISRUC-SLEEP Dataset
SleepEEGNet: Automated Sleep Stage Scoring with Sequence to Sequence Deep Learning Approach
尝试多种不同的深度神经网络结构(如LSTM,RESNET,DFCNN等)对单通道EEG进行自动化睡眠阶段分期.我们相信这些代码同时可以用于其他生理信号(如ECG,EMG等)的分类.希望这将有助于您的研究.
Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
Project for identify human sleep stage using the combination of ELM and PSO compared to the combination of SVM and PSO
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network