Related Experiment Video

Updated: May 25, 2026

Simultaneous Photothrombosis and Fiber Photometry to Induce and Monitor Ischemic Stroke in Behaving Mice
07:49

Simultaneous Photothrombosis and Fiber Photometry to Induce and Monitor Ischemic Stroke in Behaving Mice

Published on: November 14, 2025

A multidimensional signal processing approach for classification of microwave measurements with application to stroke

Hamed Yousefi Mesri1, Masoud Khazaeli Najafabadi, Tomas McKelvey

  • 1Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden. mesri@student.chalmers.se

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|January 19, 2012
PubMed

More Related Videos

STFEEG-Tool: A Spatial-Temporal-Frequency EEG Analysis Tool for Motor Imagery Brain-Computer Interfaces05:36

STFEEG-Tool: A Spatial-Temporal-Frequency EEG Analysis Tool for Motor Imagery Brain-Computer Interfaces

Published on: March 10, 2026

A Bedside, Single Burr Hole Approach to Multimodality Monitoring in Severe Brain Injury06:18

A Bedside, Single Burr Hole Approach to Multimodality Monitoring in Severe Brain Injury

Published on: March 26, 2019

Related Concept Videos

Classification of Signals01:30

Classification of Signals

In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...