OMNI Rate of Perceived Exertion

2021 ◽  
pp. 93-96
2004 ◽  
Vol 18 (4) ◽  
pp. 30-31
Author(s):  
Konrad J. Dias ◽  
Kathleen Amos ◽  
Jennifer Koons ◽  
Patrick Martchink ◽  
Jared Smiddy ◽  
...  

Author(s):  
James R. Mckee ◽  
Bradley A. Wall ◽  
Jeremiah J. Peiffer

Purpose: To examine the influence of temporal location of high-intensity interval training (HIIT) within a cycling session on the time spent ≥90% of maximal oxygen consumption and physiological and perceptual responses. Methods: In a randomized, crossover design, 16 trained cyclists (male, n = 13 and female, n = 3) completed three 90-minute cycling sessions with HIIT placed at the beginning, middle, or end of the session (13, 36, and 69 min, respectively). Intervals consisted of three 3-minute efforts at 90% of the power output associated with maximal oxygen consumption interspersed with 3 minutes of recovery. Oxygen consumption, minute ventilation, respiratory rate, and heart rate were recorded continuously during work intervals. Rate of perceived exertion was recorded at the end of work intervals, and sessional rate of perceived exertion was collected 20 minutes after session completion. Results: No differences were observed for mean oxygen consumption (P = .479) or time spent ≥90% maximal oxygen consumption (P = .753) between condition. The mean rate of perceived exertion of all intervals were greater in the Middle (P < .01, effect size = 0.83) and End (P < .05, effect size = 0.75) compared with Beginning conditions. Mean minute ventilation was greater in the End compared with Beginning condition (P = .015, effect size = 0.63). However, no differences in mean respiratory rate were observed between conditions (P = .297). Conclusions: Temporal location of HIIT has no impact on oxygen consumption or cardiovascular stress within a cycling session. However, HIIT performed later in the session resulted in higher ventilation, which may indicate the need for greater anaerobic contribution to these intervals.


Author(s):  
Nicola Giovanelli ◽  
Lara Mari ◽  
Asia Patini ◽  
Stefano Lazzer

Purpose: To compare energetics and spatiotemporal parameters of steep uphill pole walking on a treadmill and overground. Methods: First, the authors evaluated 6 male trail runners during an incremental graded test on a treadmill. Then, they performed a maximal overground test with poles and an overground test at 80% (OG80) of vertical velocity of maximal overground test with poles on an uphill mountain path (length = 1.3 km, elevation gain = 433 m). Finally, they covered the same elevation gain using poles on a customized treadmill at the average vertical velocity of the OG80. During all the tests, the authors measured oxygen uptake, carbon dioxide production, heart rate, blood lactate concentration, and rate of perceived exertion. Results: Treadmills required lower metabolic power (15.3 [1.9] vs 16.6 [2.0] W/kg, P = .002) and vertical cost of transport (49.6 [2.7] vs 53.7 [2.1] J/kg·m, P < .001) compared with OG80. Also, oxygen uptake was lower on a treadmill (41.7 [5.0] vs 46.2 [5.0] mL/kg·min, P = .001). Conversely, respiratory quotient was higher on TR80 compared with OG80 (0.98 [0.02] vs 0.89 [0.04], P = .032). In addition, rate of perceived exertion was higher on a treadmill and increased with elevation (P < .001). The authors did not detect any differences in other physiological measurements or in spatiotemporal parameters. Conclusions: Researchers, coaches, and athletes should be aware that steep treadmill pole walking requires lower energy consumption but same heart rate and rate of perceived exertion than overground pole walking at the same average intensity.


2019 ◽  
Vol 9 (23) ◽  
pp. 5174
Author(s):  
Alessio Rossi ◽  
Enrico Perri ◽  
Luca Pappalardo ◽  
Paolo Cintia ◽  
F. Iaia

The use of machine learning (ML) in soccer allows for the management of a large amount of data deriving from the monitoring of sessions and matches. Although the rate of perceived exertion (RPE), training load (S-RPE), and global position system (GPS) are standard methodologies used in team sports to assess the internal and external workload; how the external workload affects RPE and S-RPE remains still unclear. This study explores the relationship between both RPE and S-RPE and the training workload through ML. Data were recorded from 22 elite soccer players, in 160 training sessions and 35 matches during the 2015/2016 season, by using GPS tracking technology. A feature selection process was applied to understand which workload features influence RPE and S-RPE the most. Our results show that the training workloads performed in the previous week have a strong effect on perceived exertion and training load. On the other hand, the analysis of our predictions shows higher accuracy for medium RPE and S-RPE values compared with the extremes. These results provide further evidence of the usefulness of ML as a support to athletic trainers and coaches in understanding the relationship between training load and individual-response in team sports.


Author(s):  
Sérgio Matos ◽  
Filipe Manuel Clemente ◽  
Rui Silva ◽  
Joel Pereira ◽  
José María Cancela Carral

Endurance sports like trail running constitute an extensive individual modality causing numerous physiological changes to occur in the athlete. In this sense, an adequate monitoring of training load appears to be essential to improve competition performance. The aim of this study was two-fold: (i) to analyze trail runners’ weekly load variations in the four weeks leading up to a trail running competition, and (ii) to determine the relationship between the runners’ pacing in competitions and their physical fitness and workload parameters. Twenty-five amateur male trail runners (age: 36.23 ± 8.30 years old; minimum International Trail Running Association performance index: 600) were monitored daily for the duration of a season (52 weeks). External load (distance covered, pace) and internal load (rate of perceived exertion) were measured daily. Additionally, weekly workload measures of acute:chronic workload ratio (ACWR), training monotony, and training strain were calculated. The runners were also assessed for maximal aerobic speed (MAS) every four months. No significant differences in workload measures (p > 0.05) were observed in the four weeks leading up to each short trail competition; however, leading up to the long trail, ultra-trail medium, and ultra-trail long/extra-long competitions, the differences in the runners’ workload measures were significant (p < 0.05). In the short trail, pace was found to be moderately correlated with the ACWR of total distance (r = −0.334) and with training monotony of rate of perceived exertion (RPE) (r = −0.303). In the ultra-trail, a large correlation was observed between pace and elevation accumulated (r = 0.677). We concluded that significant workload differences from one week to the next only occurred in preparation for longer-distance competitions, with sudden acute load decreases and very low ACWR values reported mainly in weeks 1 and 2 of the taper. Meaningful relationships were found between performance (pace) and MAS for longer trails and between pace and MAS for ultra-trail competitions.


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