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Related Concept Videos

Exercise and Muscle Performance01:27

Exercise and Muscle Performance

Exercise induces a range of adaptations in muscle tissue, depending on the type and duration of activity. Such physical training can be broadly categorized into two types: endurance exercises and resistance exercises.
Endurance exercises
Endurance exercises involve running, swimming, or cycling, which require repetitive movements with low force output. When a person engages in endurance exercise, a few noticeable changes occur in their skeletal muscles. For instance, the number of capillaries...

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Time series analysis: evaluating performance trends within resistance exercise sessions.

Loren Zf Chiu1, George J Salem

  • 1Musculoskeletal Biomechanics Research Laboratory, University of Southern California, Los Angeles, California, USA. Loren.Chiu@ualberta.ca

Journal of Strength and Conditioning Research
|December 10, 2009
PubMed
Summary
This summary is machine-generated.

Time series analysis, using a moving average method, helps coaches and scientists interpret performance data by reducing variability. This technique clarifies systematic patterns in high-power resistance exercise, optimizing training stimulus and minimizing fatigue.

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Area of Science:

  • Sports Science
  • Exercise Physiology
  • Biomechanical Analysis

Background:

  • Frequent performance measurements are now possible due to technical advances.
  • Variability in physiological and psychological factors can obscure performance patterns.
  • Interpreting performance data requires methods to reduce variability.

Purpose of the Study:

  • To describe the moving-average method for time series analysis.
  • To reduce variability in performance measurements during high-power resistance exercise.
  • To elucidate systematic patterns in exercise performance.

Main Methods:

  • Ten male power athletes performed three high-power resistance exercise sessions with varying loads and repetitions.
  • Barbell power was measured using three-dimensional motion analysis.
  • A 3-point moving average was applied to the time series data.

Main Results:

  • High-power resistance exercise initially increased performance, followed by a decrease after the midpoint.
  • Deviations in performance responses obscured the underlying systematic pattern.
  • The 3-point moving average effectively reduced variability and revealed the systematic pattern.

Conclusions:

  • Exercise acutely elicits systematic changes in performance.
  • Time series analysis, specifically the moving average technique, can identify these patterns.
  • Optimizing exercise parameters to maximize training stimulus and minimize fatigue is facilitated by understanding these patterns.