Wiktoria Wojnicz - Publications - Bridge of Knowledge

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dr hab. inż. Wiktoria Wojnicz

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Year 2022
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Year 2024
  • Enhancing rheological muscle models with stochastic processes
    Publication

    - Acta of Bioengineering and Biomechanics - Year 2024

    Purpose: Biological musculoskeletal systems operate under variable conditions. Muscle stiffness, activation signals, and loads change during each movement. The presence of noise and different harmonic components in force production significantly influences the behaviour of the muscular system. Therefore, it is essential to consider these factors in numerical simulations. Methods: This study aims to develop a rheological mathematical...

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  • Timed rolling and rising tests in Duchenne muscular dystrophy ambulant boys: a feasibility study
    Publication
    • A. Sobierajska-Rek
    • J. Jabłońska-Brudło
    • A. Dąbrowska
    • W. Wojnicz
    • J. Meyer-Szary
    • J. Wierzba

    - MINERVA PEDIATRICA - Year 2024

    BACKGROUND: Functional activities are extensively used in motor assessments of patients with Duchenne muscular dystrophy. The role of timed items has been reported as an early prognostic factor for disease progression. However, there are two functional activities that are not widely assessed in clinical practice among Duchenne muscular dystrophy patients: rolling and bed rising. This study aimed to investigate whether the 360-degree...

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  • Towards hand grip force assessment by using EMG estimators
    Publication
    • R. Barański
    • W. Wojnicz
    • B. Zagrodny
    • M. Ludwicki
    • A. Sobierajska-Rek

    - MEASUREMENT - Year 2024

    The purpose of this study was to propose a method to assess individual regression (calibration) curves to establish a relationship between an isometric grip force and surface electromyography (EMG) estimator. In this study 18 healthy volunteers (12 male (23.0 ± 2.0 years) and 6 female (23.2 ± 0.7 years)) had been examined. Ten EMG estimators (mean absolute value, root mean square, entropy, energy, turns per second, mean of zero...

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  • Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis

    We proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...

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