A forecasting framework for predicting perceived fatigue: Using time series methods to forecast ratings of perceived exertion with features from wearable sensors

Repetition duration influences ratings of perceived exertion.

This study investigated the effect of different repetition durations on ratings of perceived exertion (RPE) in active muscles (RPE-AM) and the overall body (RPE-O). 19 male volunteers (M age = 25.4 yr., SD = 3.5) performed strength training protocols with multiple sets matched by the number of sets and repetitions, intensity and rest interval but different repetition durations: 4 sec., 6 sec., ...

Use of ratings of perceived exertion in sports.

The rating of perceived exertion (RPE) is a recognized marker of intensity and of homeostatic disturbance during exercise. It is typically monitored during exercise tests to complement other measures of intensity. The purpose of this commentary is to highlight the remarkable value of RPE as a psychophysiological integrator in adults. It can be used in such diverse fashions as to predict exercis...

Reliability of ratings of perceived exertion during progressive treadmill exercise.

OBJECTIVE To assess the test-retest reliability (repeatability) of Borg's 6-20 rating of perceived exertion (RPE) scale using a more appropriate statistical technique than has been employed in previous investigations. The RPE scale is used widely in exercise science and sports medicine to monitor and/or prescribe levels of exercise intensity. The "95% limits of agreement" technique has recently...

A Comparison Between Time Series, Exponential Smoothing, and Neural Network Methods To Forecast GDP of Iran

Using Wavelets and Splines to Forecast Non-Stationary Time Series

 This paper deals with a short term forecasting non-stationary time series using wavelets and splines. Wavelets can decompose the series as the sum of two low and high frequency components. Aminghafari and Poggi (2007) proposed to predict high frequency component by wavelets and extrapolate low frequency component by local polynomial fitting. We propose to forecast non-stationary process u...