Automated control of cyclist training by cardiovascular response

Automated control of cyclist training by cardiovascular response


V.G. Sverkachev, professor, Dr.Hab.
Maikop state technological university, Maikop
N.Yu. Khazhiliev, Ph.D.
Kabardino-Balkarian state university, Nalchik

 Key words: loading, heart rate, automated control system, feedback, training device.

Introduction. Computerized training devices and systems are the best in facilitating adaptation and effectivization of training process, since their use makes muscular work conditions closer to the optimum correlation of external loading and athlete's body capabilities [1– 3]. Here the systems with negative feedback are the most effective.

The purpose of the study was to define the impact of the automated control system on cardiovascular response and elaborate practical guidelines for cycling training.

Materials and methods. We developed, designed and approved in practice a computer controlled exercise bike (CCEB), representing an electronic indoor cycling training system, enabling on-line negative feedback load control by set heart rate (HR).

The system (Fig. 1) includes: frame 1 for fixing the bicycle 2, made of fork tips of the fore wheel 3 and fixed bearing unit 4 of the rear wheel 5. The rear wheel is frictionally connected to the roller 6, placed on an axle 7, set on the frame. The axle 7 has a fan propeller 8 (Fig. 2) on one side of the roller 6 and step loading from another side of the roller 6. It is created using the permanent magnet 9 (Fig. 3), pulled stepwise to the copper disc 10 spinning with the wheel. There is an indicator 11 of bicycle’s simulated movement, which output signal is connected with the rotation of the stipulated roller (Fig. 4).

Fig. 1. General view of CCEB

Fig. 2. The view of the control system from the side of the fan propeller

Fig. 3. The view of the control system from the side of the copper disc

Fig. 4. Rear view of the control system

The dynamic loading results from the interaction of eddy currents, induced in the rotating copper disc by the control winding 12. It is wound on the leg 13, covering a part of the surface of the indicated disc and is connected via the first amplifier 14 and the first digital-analog converter (DAC) 15 to the system unit 16 PC with a display 17 and keyboard 18. The field winding of electric motor 19 is connected to the system unit 16 via the second amplifier 20 and the second DAC 21.

The HR sensor 23, which sounding rod, fixed on a cyclist during training, and the noted sensor 11 of bicycle’s simulated movement are attached to the system unit via the first 24 and second 25 ADC respectively. The axle of electric motor is mechanically (here – frictionally) connected to the rear wheel of the bicycle. All the units and indicators, that need power supply to operate, are powered up 27.

Before starting a cyclist’s training HR limits [lower Р, upper Р] are set on the PC using the keyboard. It is selected individually during the preliminary executive checkup of all athletes and shows the optimal work zone for their heart. There is also an opportunity of setting the standard training mode.

An athlete sits on a bicycle and an HR sensor is fixed on him. The sensor signal is connected to the system unit via the first ADC. The indicator of bicycle’s simulated movement is attached to the system unit via the second ADC. Hence, the characteristics shown on the display screen are: current value of HR, distance travelled, underway time and imaginary route and cyclist’s location on it in every instant of time.

The load on treadles changes depending on the current value of athlete’s HR related to the set limits. When HR exceeds the lower limits of the set passage the control program steps up the voltage applied via the first DAC and the amplifier to the control winding, increasing the loading to the moment when athlete’s HR reaches the set passage. In case of extremely high HR, the indicated program, on the contrary, hyperbolically steps down the voltage till the HR of the one who trains reaches the set zone.

Trainer can set any HR in the automated control system, and if necessary – different and on various route sections. The time of work on the CCEB is set individually. The athlete gets all necessary information, processed on the PC display. All data are saved in the database for statistical processing and further analysis. Provided that an adequate database is created within a long period of time and the specialized software is connected, recommendations on correction of the training process can be given to an ACS trainer (athlete).

Hereafter, the control process can be improved by using other athlete’s physiological characteristics (respiratory rate, arterial pressure, MOC, body temperature etc.) and biomechanical characteristics of performed exercises. The opportunities of the automated control system can be extended by involving the last software developments.

This system contributes to expanding body capabilities and making athletes’ training more efficient thanks to continuous monitoring of their body response when doing an exercise and modulating automatic loading control in compliance with changing indices of the registered characteristics. Such an approach excludes the possibility of overtraining and contributes to better adaptation.

The ability of registration and on-line correction of biomechanical motor patterns in the course training by body response to loading is a primary condition of optimization of the training process control and improvement of athlete’s skills along with protection of his health.

Results and discussion. In our explanatory researches we fixed the dynamics of oxygen saturation by means of the transmission pulse oximetry in differently-skilled cyclists at continuous external loading control by HR (when using CCEB) and under standard conditions. The oxyhemograms, adduced on Fig. 5–7, characterize the main dynamics of oxygen saturation in differently-skilled cyclists. Table 1 contains the values of the registered indicator.

Fig. 5. The graph of variance of oxygen saturation in elite athletes when using CCEB and at standard trainings

Fig. 6. The graph of variance of oxygen saturation among advanced athletes when using CCEB and at standard trainings


Fig. 7. The graph of variance of oxygen saturation among intermediate athletes when using CCEB and at standard trainings

As shown on the graphs, the fluctuation in blood oxygen tension is significantly lower in the athletes involved in CCEB training, rather than the ones engaged in standard training. The average blood oxygen level (Table 1) is higher among the ones who apply our training system. One is to mark the specifics of changes of the blood oxygen level, observed when performing work with differently-skilled athletes under the examined conditions. Hence, animal and vegetative systems are greatly correlated in conditions of CCEB: the state stabilizes within a shorter period of time, resulting in the increase of athletes’ muscular capabilities (Fig. 8). The changes in the oxygen saturation are accompanied by the rise of the working capacity and decrease of the time for recovery.

Fig. 8. HR curve for elite athletes at CCEB and standard trainings

Table 1. The variation of oxygen saturation among differently-skilled cyclists under different training conditions, ±δ

Skill level

Training conditions


Statistical significance when р<0,05




93,4 ±1,12

95,5 ±1,13


91,0 ±1,84

92,8 ±1,25


86,4 ±2,46

93,2 ±2,14


The given CCEB application methodology is most useful for beginners, for it provides for maintaining a steady blood oxygen level, while stress reaction of the body is rather high and deleterious effects are almost lacking.

The resistance level, being controlled using the HR control program, affected the characteristics of biomechanical motor patterns, which we compared to the characteristics of the exercise performed under standard training conditions, i.e. on a Cateye CS–1000 cyclosimulator without automatic control (many cyclists use this or similar training devices in the course of trainings). The figures below show the graphs of variance of characteristics of different biomechanical patterns of motions performed by differently-skilled athletes (mean sample values are adduced).

As seen from Fig. 8, that shows the HR dynamics specific for elite cyclists when doing tasks under different conditions, the level of the examined indicator rises rather quickly up to 160 bpm both at standard and CCEB training conditions. In case of further performance of the exercise the HR level remains the same till the end of training with the use of our system and is constantly growing under standard conditions and ultimately reaches 180 bpm.

The speed of movement subjected on Fig. 9 when doing an exercise using CCEB is significantly higher compared to standard training conditions and it changes smoothly.

Fig. 9. Speed curve for elite athletes at CCEB and standard trainings

Advanced athletes differ even more in their HR dynamics (Fig. 10) between standard training conditions and when using CCEB. HR at standard training is significantly higher and is constantly going up, while when using our training system it remains on the optimum level.

Fig. 10. HR curve for advanced athletes under different training conditions

The dynamics of the speed of movement (Fig. 11) at the CCEB training is smoother and remains practically at the same level till the end of performance of an exercise, while at standard training the changes are spasmodic: high values when starting an exercise and decrease by the end.


Fig. 11. Speed curve for advanced athletes at different training conditions

The graph of variance of HR among intermediate athletes (Fig. 12) shows similar changes of the examined characteristics, as athletes of higher ranks, proving the efficiency of using CCEB that can maintain the HR level within the optimal limits.

Fig. 12. HR curve for intermediate athletes at CCEB and standard trainings

As shown at Fig. 13, in the CCEB training conditions intermediate athletes are capable of doing a motor task at much higher speed, and the occurring changes are less divergent than when doing exercises under standard training conditions.

Fig. 13. Speed curve for intermediate athletes under different training conditions

Table 2 contains the mean values of the characteristics of the examined biomechanical motor patterns, we have obtained in the experiment.

Table 2. Changes of biomechanical motor patterns among differently-skilled cyclists under different training conditions, ±δ

Skill level

Standard training

CCEB training

Statistical significance when р<0,05


V, km/h

L, km


V, km/h

L, km






































As proved by the results of the study, the CCEB ACS manages its mission efficiently and athlete’s HR is within the set passage (151 – 161 bpm or 152 – 162 bpm in our specific cases). And if due to some reasons HR is beyond the limits of the passage (which the control program seeks to prevent) the ACS normalizes the values.

The efficiency of our training method for road cyclists was estimated by comparing the time for recovery after an exercise and a distance travelled registered at the first and the last sessions when doing the test “30 min bike trainer riding”.

The comparative analysis of the results of the test made at the end of the educational experiment is presented in Table 3. As seen from the Table, both of the groups show the reliable improvement of the results in the registered motor patterns.

Table 3. The results of the basic educational experiment, ±δ

Registered characteristics

Before the experiment

After the experiment

Statistical significance when P<0,05















t recovery, s

124,12± 1,13




L, km





Conclusions. Proceeding from the results of the studies of the dynamics of the physiological data of athletes training under standard conditions and using the computer controlled exercise bike, the latter promotes faster and less damaging adaptation to physical loading than under standard conditions. The HR dynamics, registered in the experiments, testifies to better adaptation of athlete’s cardiovascular system to loading at the computer controlled exercise bike training and its variative changes promote maintaining of the given heart work index in the optimum passage. The athletes who train using the computer controlled exercise bike adapted faster and performed bigger load, which indicates to development of the adaptive syndrome among them.



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  2.  Ippolitov, Y.A. Optimization of conditions of performance of sports exercises / Y.A. Ippolitov, V.S. Cheburaev // Teoriya i praktika fizicheskoy kultury. – 1994. – № 1/2. – P. 44–46. (In Russian)
  3. Shirkovets, E.A. The supervisory control system and corrective actions in training in cyclic sports: abstract of doctoral thesis (Hab.) /E.A. Shirkovets. – Moscow, 1995. (In Russian)

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