AI Medical Compendium Journal:
IEEE transactions on bio-medical engineering

Showing 51 to 60 of 342 articles

Self-Supervised Learning Improves Accuracy and Data Efficiency for IMU-Based Ground Reaction Force Estimation.

IEEE transactions on bio-medical engineering
OBJECTIVE: Recent deep learning techniques hold promise to enable IMU-driven kinetic assessment; however, they require large extents of ground reaction force (GRF) data to serve as labels for supervised model training. We thus propose using existing ...

The Deep-Match Framework: R-Peak Detection in Ear-ECG.

IEEE transactions on bio-medical engineering
The Ear-ECG provides a continuous Lead I like electrocardiogram (ECG) by measuring the potential difference related to heart activity by electrodes which are embedded within earphones. However, the significant increase in wearability and comfort enab...

Formulation of Common Spatial Patterns for Multi-Task Hyperscanning BCI.

IEEE transactions on bio-medical engineering
This work proposes a new formulation for common spatial patterns (CSP), often used as a powerful feature extraction technique in brain-computer interfacing (BCI) and other neurological studies. In this approach, applied to multiple subjects' data and...

A Spatiotemporal Deep Learning Framework for Scalp EEG-Based Automated Pain Assessment in Children.

IEEE transactions on bio-medical engineering
OBJECTIVE: Common pain assessment approaches such as self-evaluation and observation scales are inappropriate for children as they require patients to have reasonable communication ability. Subjective, inconsistent, and discontinuous pain assessment ...

Brain Deformation Estimation With Transfer Learning for Head Impact Datasets Across Impact Types.

IEEE transactions on bio-medical engineering
OBJECTIVE: The machine-learning head model (MLHM) to accelerate the calculation of brain strain and strain rate, which are the predictors for traumatic brain injury (TBI), but the model accuracy was found to decrease sharply when the training/test da...

Magnetic Resonance Spectroscopy Quantification Aided by Deep Estimations of Imperfection Factors and Macromolecular Signal.

IEEE transactions on bio-medical engineering
OBJECTIVE: Magnetic Resonance Spectroscopy (MRS) is an important technique for biomedical detection. However, it is challenging to accurately quantify metabolites with proton MRS due to serious overlaps of metabolite signals, imperfections because of...

Towards Efficient Neural Decoder for Dexterous Finger Force Predictions.

IEEE transactions on bio-medical engineering
OBJECTIVE: Dexterous control of robot hands requires a robust neural-machine interface capable of accurately decoding multiple finger movements. Existing studies primarily focus on single-finger movement or rely heavily on multi-finger data for decod...

Development of Convolutional Neural Network to Segment Ultrasound Images of Histotripsy Ablation.

IEEE transactions on bio-medical engineering
OBJECTIVE: Histotripsy is a focused ultrasound therapy that ablates tissue via the action of bubble clouds. It is under investigation to treat a number of ailments, including renal tumors. Ultrasound imaging is used to monitor histotripsy, though the...

Emergency Response Person Localization and Vital Sign Estimation Using a Semi-Autonomous Robot Mounted SFCW Radar.

IEEE transactions on bio-medical engineering
The large number and scale of natural and man-made disasters have led to an urgent demand for technologies that enhance the safety and efficiency of search and rescue teams. Semi-autonomous rescue robots are beneficial, especially when searching inac...

Developing RPC-Net: Leveraging High-Density Electromyography and Machine Learning for Improved Hand Position Estimation.

IEEE transactions on bio-medical engineering
OBJECTIVE: The purpose of this study was to develop and evaluate the performance of RPC-Net (Recursive Prosthetic Control Network), a novel method using simple neural network architectures to translate electromyographic activity into hand position wi...