2020
DOI: 10.3390/ijerph17082846
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Do Surface Slope and Posture Influence Lower Extremity Joint Kinetics during Cycling?

Abstract: The purpose of this study was to investigate the effects of surface slope and body posture (i.e., seated and standing) on lower extremity joint kinetics during cycling. Fourteen participants cycled at 250 watts power in three cycling conditions: level seated, uphill seated and uphill standing at a 14% slope. A motion analysis system and custom instrumented pedal were used to collect the data of fifteen consecutive cycles of kinematics and pedal reaction force. One crank cycle was equally divided into four phas… Show more

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Cited by 5 publications
(6 citation statements)
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“…When switching from seated to standing cycling, joint angles drastically change, inducing changes in lower limb joint moments and powers (Caldwell et al 1998 , 1999 ; Tang et al 2020 ; Wilkinson et al 2020 ) and a slower preferred cadence (Harnish et al 2007 ). During seated cycling, a part of the cyclist’s body weight is passively supported by the saddle, whereas during standing, the body weight has to be actively supported by muscles but can also provide positive power during downstroke (Stone and Hull 1995 ), resulting in higher maximal power outputs reached during standing compared to sitting (Millet et al 2002 ; Reiser et al 2002 ).…”
Section: Optimal Slopementioning
confidence: 99%
“…When switching from seated to standing cycling, joint angles drastically change, inducing changes in lower limb joint moments and powers (Caldwell et al 1998 , 1999 ; Tang et al 2020 ; Wilkinson et al 2020 ) and a slower preferred cadence (Harnish et al 2007 ). During seated cycling, a part of the cyclist’s body weight is passively supported by the saddle, whereas during standing, the body weight has to be actively supported by muscles but can also provide positive power during downstroke (Stone and Hull 1995 ), resulting in higher maximal power outputs reached during standing compared to sitting (Millet et al 2002 ; Reiser et al 2002 ).…”
Section: Optimal Slopementioning
confidence: 99%
“…Further, the 95 % LoA between flat and uphill cycling derived power output at CP of + 7.7 to −10.1 % ( + 26 to −32 W) may be too large to consider both conditions as equivalent. Road gradient partially affects biomechanical (e. g. joint moments) [15][16][17][18][19] and physiological (e. g. EMG activity) [15,[20][21][22][23] parameters during cycling exercise, indicating an effect of gradient on muscle recruitment patterns. Recent studies investigated the influence of changes in muscle activity, muscle contraction and/or muscle fibre type recruitment patterns on critical speed or CP estimates and their associated metabolic rate [24,25].…”
Section: Power-duration Relationshipmentioning
confidence: 99%
“…It has been shown that field derived CP estimates may be considered as valid and reliable compared with laboratory esti-mates, whereas the reliability (and hence validity) of field derived W´ estimates is still debated [13,14]. However, previous research has shown that road gradient may partially affect biomechanical and physiological parameters like crank kinetics (e. g. crank inertial load, crank torque profile) [15][16][17], lower limb joint kinetics (e. g. joint moments, joint mechanical work) [18,19], lower limb neuromuscular activation (e. g. intensity and timing of EMG activity) [20][21][22] and gross efficiency [15,23] during cycling in a seated position. Furthermore, it has been shown that a certain metabolic rate (e. g. V ̇O2 and/or blood[lactate] at critical speed or CP) may be achieved by different interplays of muscle activity, muscle contraction and/ or muscle fibre type recruitment patterns, and external workrates [24,25].…”
Section: Introductionmentioning
confidence: 99%
“…The pedaling torque might not fully contribute to the E-bike's wheel torque. As reported in [8][9][10][11][12][13][14], an effective pedaling torque can be different depending on different crank positions.…”
Section: Introductionmentioning
confidence: 99%
“…The sources in [ 1 , 2 , 24 , 38 , 39 ] aim to design suitable torque controllers for assisted E-bikes; however, no further analysis of the influence of the cyclist’s pedaling torque was addressed. By contrast, [ 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 ] investigate the cyclist’s pedaling dynamic with no motor-assisted torque assumed. Moreover, [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ] focus on E-bike cycling performance with respect to human behaviors, including heartbeat, gender, and weight.…”
Section: Introductionmentioning
confidence: 99%