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Surface Electromyography Data Analysis for Evaluation of Physical Exercise Habits between Athletes and Non-Athletes during Indoor Rowing.

Tomasz GrzejszczakAnna RokselaAnna PoświataAnna SiemianowiczAgnieszka KiełbońMichał Mikulski
Published in: Sensors (Basel, Switzerland) (2024)
In this paper, surface electromyography (sEMG) is used to gather the activation neural signal from muscles during an indoor rowing exercise. The exercise was performed by professional athletes and amateur non-athletes. The data acquisition and processing are described to obtain a set of parameters: number of cycles, average cycle time, cycle time standard deviation, fatigue time, muscle activation time, and muscle energy. These parameters are used to draw conclusions on common non-athletes' mistakes during exercise for better training advice and a way of statistically distinguishing an athlete from a non-athlete.
Keyphrases
  • data analysis
  • high intensity
  • physical activity
  • high school
  • air pollution
  • skeletal muscle
  • resistance training
  • particulate matter
  • health risk
  • machine learning
  • sleep quality