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--- visual3d:tutorials:emg:automatic_emg_events [2024/07/12 14:08] – created sgranger
+++ visual3d:tutorials:emg:automatic_emg_events [2024/10/09 14:42] (current) – Fixed external links. wikisysop
@@ Line 1: / Line 1: @@
-====== Automatic_EMG_Events ======
+====== Automatic EMG Events ======
 \\
@@ Line 22: / Line 22: @@
 ==== Preparing for the Tutorial ====
-**Tutorial data download**: Files used in this tutorial can be found here: [[[https://www.has-motion.com/download/examples/EMG_Tutorial.zip|EMG Tutorial]]]
+**Tutorial data download**: Files used in this tutorial can be found here: [[https://www.has-motion.com/download/examples/EMG_Tutorial.zip|EMG Tutorial]]
 The following pipeline has been provided as a **meta_function**, and you may copy and paste it into your **Visual3D x64 > Plugins > Meta-Commands** folder. For more information on Meta-Commands and how they work, follow see [[Visual3D:Documentation:Pipeline:Meta_Commands:Meta_Commands_Overview|here]].
-**Meta-Commands download**: Meta-Command file found here: [[[https://www.has-motion.com/download/examples/EMG/Automatic_EMG_Events.v3m|Automatic_EMG_Events]]]
+**Meta-Commands download**: Meta-Command file found here: [[https://www.has-motion.com/download/examples/EMG/Automatic_EMG_Events.v3m|Automatic_EMG_Events]]
 ==== Loading Data and Calling the Meta-Function ====
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 ==== Detecting Low Activity Signal Regions ====
-{{ENVELOPE.png}}
+{{:ENVELOPE.png}}
 This section will essentially perform on/off detection of the **ENVELOPE** signal with an arbitrary baseline that we define with a user-given parameter.
@@ Line 440: / Line 440: @@
 </code>
-{{TKEO_NEW.png}}
+{{:TKEO_NEW.png}}
-{{ZOOMED.png}}
+{{:ZOOMED.png}}
 We can now take a look at our onset and offset detection.
@@ Line 454: / Line 454: @@
 We can see from these figures that there are a lot of **ON** and **OFF** detections for the **TKEO** signal. This is due to a lot of fluctuation and noise in the signal, and the threshold is passed through many times where there is large muscle activity.
-If you find the automatic detection is identify data fluctuation that is too low in amplitude for your liking, we can adjust the **ThresholdPercent** parameter to change this. For example, this meta-command was re-run on this data using **ThresholdPercent = 0.6**, and the following results were found. We can see that only muscle activity of high magnitude were noted as **ON/OFF** events. {{THRESH60.png}}
+If you find the automatic detection is identify data fluctuation that is too low in amplitude for your liking, we can adjust the **ThresholdPercent** parameter to change this. For example, this meta-command was re-run on this data using **ThresholdPercent = 0.6**, and the following results were found. We can see that only muscle activity of high magnitude were noted as **ON/OFF** events. {{:THRESH60.png}}
 ==== References ====
@@ Line 462: / Line 462: @@
 . [[https://ieeexplore.ieee.org/abstract/document/7096455|José A. Biurrun Manresa, Carsten D. Mørch, and Ole K. Andersen, Teager-Kaiser Energy Operator Improves the Detection and Quantification of Nociceptive Withdrawal Reflexes From Surface Electromyography, IEEE]]
-. [Solnik S, DeVita P, Rider P, Long B, and Hortobágyi T (2008) Teager–Kaiser Operator improves the accuracy of EMG onset detection independent of signal-to-noise ratio, Acta Bioeng Biomech. 2008 ; 10(2): 65–68]
+. Solnik S, DeVita P, Rider P, Long B, and Hortobágyi T (2008) Teager–Kaiser Operator improves the accuracy of EMG onset detection independent of signal-to-noise ratio, Acta Bioeng Biomech. 2008 ; 10(2): 65–68