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@@ -21,19 +21,19 @@ The dataset consists of 8 EMG signals recorded from the domineering foot of each
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  For this dataset, it is recommended to work with binary classification models, taking the "Transition-to-Fatigue" state as the positive class, as the data in the "Fatigue" class is significantly limited.
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  **FEATURES**
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- Time
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- Right Rectus femoris
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- Left Gluteus maximus
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- Left Gastrocnemius medialis
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- Left Semitendinosus
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- Left Biceps femoris caput longus
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- Right Vastus medialis
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- Right Tibialis anterior
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- Left Gastrocnemius lateralis
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  **TARGETS**
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- 0-No Fatigue
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- 1-Transition To Fatigue
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- 2-Fatigue
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  By: Yomin Jaramillo M
 
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  For this dataset, it is recommended to work with binary classification models, taking the "Transition-to-Fatigue" state as the positive class, as the data in the "Fatigue" class is significantly limited.
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  **FEATURES**
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+ - Time
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+ - Right Rectus femoris
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+ - Left Gluteus maximus
27
+ - Left Gastrocnemius medialis
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+ - Left Semitendinosus
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+ - Left Biceps femoris caput longus
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+ - Right Vastus medialis
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+ - Right Tibialis anterior
32
+ - Left Gastrocnemius lateralis
33
 
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  **TARGETS**
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+ - 0-No Fatigue
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+ - 1-Transition To Fatigue
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+ - 2-Fatigue
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  By: Yomin Jaramillo M