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  • Uporaba klasifikatorja MiniRocket v klasifikaciji starosti oseb na podlagi frekvenc proženja motoričnih enot med plantarno fleksijo [Elektronski vir]
    Kavran, Domen ...
    This paper presents and evaluates a method for age classification based on the motor unit discharge rates using the MiniRocket classifier. The proposed method was tested on a dataset of older and ... younger subjects that included EMG signals from gastrocnemius medialis, gastrocnemius lateralis, soleus, and tibialis anterior muscles during plantar flexion. The average F1-score for all muscles was 0,562 ± 0,259 at 30% maximum voluntary contraction and 0,525 ± 0,277 at 60% maximum voluntary contraction. Classification proved most successful when exclusively utilizing motor units of the gastrocnemius lateralis muscle. This led to the highest F1-score of 0,770 ± 0,204 at 30% maximum voluntary contraction. In the current form, the MiniRocket classifier proves to be less capable of capturing the different behaviors of motor units between young and old persons. Our results suggests that inclusion of other muscle features, such as exerted muscle force, is likely required to reach the classification rates of classifiers that are based on motor unit features carefully selected by human operators.
    Source: Zbornik dvaintridesete mednarodne Elektrotehniške in računalniške konference ERK 2023 [Elektronski vir] = Proceedings of the 32nd International Electrotechnical and Computer Science Conference ERK 2023 : Portorož, Slovenija, 28. - 29. september 2023 (Str. 423-426)
    Type of material - conference contribution ; adult, serious
    Publish date - 2023
    Language - slovenian
    COBISS.SI-ID - 167916803

    Link(s):

    https://erk.fe.uni-lj.si/2023/papers/kavran(uporaba_klasifikatorja).pdf

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