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23. Standard deviation of the lateral position of the center of pressure versus speed. The standard deviation of the lateral position of the center of pressure decreases significantly with increasing speed (F = 25.294, p < 0.001). Although it may appear that cyclists exhibit less variation in the center of pressure position than non-cyclists, there was not a significant difference between the two groups (F = 3.695, p = 0.059). 

23. Standard deviation of the lateral position of the center of pressure versus speed. The standard deviation of the lateral position of the center of pressure decreases significantly with increasing speed (F = 25.294, p < 0.001). Although it may appear that cyclists exhibit less variation in the center of pressure position than non-cyclists, there was not a significant difference between the two groups (F = 3.695, p = 0.059). 

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While humans have been riding bicycles for nearly 200 years, the dynamics of how exactly they achieve this are not well understood. The overall goals of this dissertation were to identify the major control strategies that humans use to balance and steer bicycles, as well as to identify performance metrics that reliably distinguish rider skill level...

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... This is particularly true in the case of two-wheeled vehicles. Therefore, the performance quality of two-wheeled vehicles cannot be determined from only looking at its open-loop dynamics [48]. A common hypothesis in the literature, not proven yet, relates handling quality and self-stability in the straight running [49]. ...
... However, as mentioned before, although the modelling of vehicle-rider control is a popular topic with a variety of research directions, building a model for the behaviour of the rider is still a challenging task [9,32]. Given the lack of knowledge regarding the human rider characteristics, this topic is yet in its infancy, as well as the type of control they use and the skills that distinguish their ability levels [48]. ...
... The peak value of the cross-correlation between roll rate and steering rate was squared to yield a R 2 , being a measure of the similarity between the two signals. The same way of calculating the cross-correlation between bicycle roll rate and steer rate was also used in a previous study on cyclists' performance (Cain, 2013). This measure was calculated only for Task 1 since it was the only task in which the participants rode the bicycles at constant speed across the whole exercise. ...
... It is interesting that older riders exhibited higher R 2 values and shorter time delays between roll rate and steering rate compared to middle-aged riders during low-speed cycling (Task 1). Similar results were found by Cain (2013) when comparing experienced and inexperienced cyclists. Specifically, in one of his experiments, Cain (2013) found that the R 2 s between bicycle roll rate and steer rate were lower for cyclists than for non-cyclists. ...
... Similar results were found by Cain (2013) when comparing experienced and inexperienced cyclists. Specifically, in one of his experiments, Cain (2013) found that the R 2 s between bicycle roll rate and steer rate were lower for cyclists than for non-cyclists. As mentioned previously, riders stabilize a bicycle by means of two main control inputs: steering and upper-body lean (Kooijman & Schwab, 2013). ...
... Since the elderly are prone to severe injuries, bicycle stability is currently a popular research topic (Schwab and Meijaard, 2013). Three balance strategies have been proposed in former studies: steering as the primary balance strategy and trunkand lateral knee movement as secondary balance strategies (Moore et al., 2011;Cain, 2013). Since steering is the primary balance strategy, the stiffness of the arms plays an important role in active stability during cycling. ...
... Both young -and old adult subjects show an increase in positive steering power and a decrease in negative steering power (see Fig. 9). Cain (2013) showed that average positive steering power is a good measure of steering effort and that increased cycling speed reduces the steering effort required for stabilization. Since the positive steering power increases during perturbed cycling, it causes the cyclist to increase their steering effort. ...
Article
Bicycling is a popular and convenient means of transportation amongst the elderly in the Netherlands. However, the uptake of the electric bicycle resulted in an increase of single-sided bicycle accidents amongst the elderly (Veiligheid, 2010). Since elderly are prone to severe injuries, bicycle stability is currently a popular research topic. Three main balance strategies have been proposed in former studies: steering as the primary balance strategy and trunk −and lateral knee movement as secondary balance strategies (Moore et al., 2011; Cain, 2013). Since steering is the primary strategy for bicycle stability, the stiffness of the arms plays an important role in active stability during cycling. It has been shown that the arm stiffness of a passive rider is an important factor on the stability of a bicycle (Doria and Tognazzo, 2014). In the study presented here, the co-contraction index (CCI) of the upper limb for young and old adult cyclist is studied. Data is collected during experiments based on the setup described in (Kiewiet et al., 2014), wherein contact forces, muscle activities and motions of the rider and bicycle are measured for 15 young adult (mean ± sd: 25.3 ± 2.8 yrs) and 15 old adult (mean ± sd: 58.1 ± 2.1 yrs) subjects during unperturbed and perturbed cycling. The arm stiffness is defined as a co-contraction ratio between muscle activity of the m. Biceps Brachii and m. Triceps Lateralis. Results suggest that older adult cyclists use more co-contraction of their arm muscles during cycling, compared to young cyclists. The inter-subject variability of the found CCI was higher for the old adult subject group, compared to the young group. The results support the initial hypothesis that the increase in co-contraction of the upper limb for older cyclists is higher during perturbed cycling compared to unperturbed cycling than for younger cyclists. The findings might give direction towards solutions for increasing the safety and stability for elderly cyclists.
... Several authors showed that steering is the primary control input for balancing (Kooijman, Schwab, & Moore, 2009;Moore, Kooijman, Schwab, & Hubbard, 2011;Weir, 1972). However, Cain (2013) found, that upper-body lean control is the dominant control strategy for balance performance for cycling on rollers. In line with this insight, upper-body lean torque was successfully implemented in several cyclist control models (Nagai, 1983;Sharp, 2001). ...
... It is assumed that the characteristics of the instrumented bicycle used in the present study are similar to those used by Schwab et al. Based on the facts that additional control actions are more important at low speeds (Cain, 2013;Kooijman et al., 2009) and that older adults have an increased delay of automatic balance-correcting muscular responses (Allum, Carpenter, Honegger, Adkin, & Bloem, 2002), the hypothesis in the present study is that older cyclists will more readily revert to recruiting additional balance strategies than young cyclists. ...
... The steering power (P s ) is a measure that represents the amount of effort a cyclist uses to perform steering actions (Cain, 2013). The steering power is defined as the steering torque multiplied by the steering angular velocity. ...
Article
This study concentrates on the cycling strategies of older cyclists (54–62 year olds) in comparison to young cyclists (20–30 year olds). While cycling in a safe laboratory set-up, controlled lateral perturbations are applied to the rear of the bicycle. Three possible strategies to keep balance are analysed for a young and older aged group: steering, lateral trunk movement and outward knee movement. Older subjects appear to rely more on knee movement as a control mechanism than young subjects. Furthermore, the frequency domain analysis revealed that the older adults need more effort to counteract high frequency perturbations. Increased inter-individual variation for the older adults subject group suggests that this group can be seen as a transition group in terms of physical fitness. This explains their increased risk in single-sided bicycle accidents (i.e. accidents involving the cyclist only). Therefore, older cyclists could benefit from improving the stability of cycling at lower speeds.
... It has been suggested that motor control changes when a cyclist progresses from less to more skilled (Cain, 2013). Wierda and Brookhuis (1991) showed higher standard deviation of the steering angle for younger cyclists compared to older ones. ...
... This suggests that more skilled riders steer in the direction of the roll whereas less skilled riders perform additional steering motions that are unrelated to the roll of the bicycle. Cain (2013) also examined the main differences in rider control of experienced versus inexperienced riders and concluded that experienced cyclists exhibit a higher correlation between the lateral position of the centre of pressure and the centre of mass compared to inexperienced cyclists. Experienced cyclists also employ more body lean control (independently from the roll of the bicycle), less steer control, and use less control effort than inexperienced riders. ...
Article
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Research on how human balance and control bicycles are inconclusive, largely due to the small number of participants in the previous studies. Therefore, the aim of this study was to test the hypotheses that 1) cycling lateral deviation amplitude will reliably show differences between more and less experienced cyclists and 2) more experienced will exhibit slower and smaller steering motions compared to the less experienced cyclists. Twenty-eight experienced and inexperienced cyclists rode a bicycle in a straight line. Lateral deviation, steering and roll were measured. Intersession reliability of the deviation was high with Cronbach's alpha values higher than 0.75. The amplitude, variability and rate of steering and roll parameters showed statistically significant differences between the groups. The test used in this study is sensitive to detect differences between more and less experienced cyclists and can be used for further research that aims to test the effect of a specific intervention addressing rider control. We also showed that steering and roll angle, which were described before as two of the main motor control actions in bicycle control, differ in the variability, amplitude and rate between more and less experienced cyclists. The results of the present study have practical implications for improving bicycle rider control and increasing the safety of cyclists.
Article
We present stability and control analysis of a rider-bicycle system under human steering and body movements. The dynamic model of rider-bicycle interactions is first constructed to integrate the rider's body movement with the moving bicycle platform. We then present human balance control strategies based on human riding experiments. The closed-loop system stability is analyzed and discussed. Quantitative influences of the bicycle physical parameters, the human control gains, and the time delays are also analyzed and discussed. Extensive experiments are conducted to validate the human control models and demonstrate human balance performance using the bikebot, an instrumented bicycle platform. The presented modeling and analysis results can be potentially used for further development of bicycle-assisted rehabilitation for postural balance patients.
Article
Understanding how human balance and control bicycles is helpful for not only designing bicycle-based rehabilitation devices but also studying physical human-machine interactions. We present stability analysis of a rider-bicycle system under the rider's steering and upper-body movement balancing controls. The dynamic model of rider-bicycle system is first constructed to integrate the rider's upper-body movement with the moving platform. We then present a human balance control strategy based on the human riding experiments. The closed-loop system stability is analyzed and discussed. Quantitative influences of the bicycle physical parameters, human control gains and human control time delays are also demonstrated and discussed.