Oct 22, 2022 · The current work focuses on designing end-to-end deep learning personalized models for pain intensity estimation and pain level classification ...

We investigated a personalized Bidirectional Long short-term memory Recurrent Neural Networks (BiLSTM RNN), and an ensemble of BiLSTM RNN and Extreme Gradient ...

We decomposed EDA signals into tonic and phasic components and augmented them to original signals. The BiLSTM-XGB model outperformed the BiLSTM classification ...

Explored an ensemble of Bidirectional LSTM RNN and Extreme Gradient Boosting (XGB) to build a multiclass pain classification model.

Transformer Encoder with Multiscale Deep Learning for Pain Classification Using Physiological Signals · Personalized Deep Bi-LSTM RNN Based Model for Pain ...

Personalized Deep Bi-LSTM RNN Based Model for Pain Intensity Classification Using EDA Signal. Sensors 2022, 22, 8087. https://doi.org/10.3390/s22218087. AMA ...

It is demonstrated that it is possible to estimate pain intensity of a patient using a computationally inexpensive machine learning model with 3 statistical ...

Recent studies have focused on deep-learning methods due to their success in classifying pain using EDA, such as 1D convolutional neural networks [CNNs] [13], a ...

... LSTM Gradient Boosting pain intensity classification using EDA signal among ... Deep BiLSTM RNN based model for Pain Intensity Classification using ...

Aug 1, 2024 · Researchers report that EDA is one of the most valuable signals for automated and objective pain assessment [1, 11, 33, 38–43]. Several ...