SIMPLIFIED 3-D MODEL FOR THE CALCULATION OF BODY SEGMENT KINEMATIC ASYMMETRIES IN CYCLING
AbstractINTRODUCTION The analysis of lower limb kinematics in cycling has generally been confined in the sagittal plane by using data obtained with a 2-D analysis Furthermore, when asymmetries were evaluated this was done by detecting data from one leg at time and subsequently comparing the scores obtained from the two sides in different trials. The present work provides a three-dimensional model for the calculation of body segment kinematics, by measuring the 3-D coordinates of a reduced number of external markers. METHODS Subjects of this study were 8 professional road cyclists, (age 25.1 ± 40 yr., body mass: 68.6 ± 6.4 kg), usually covering more than 25.000 km/year The subjects used their own bicycle mounted on rollers fitted with an air-operated variable-load device. Data were recorded at three levels of external load (Iow, medium and high) The ELITE system motion analyzer was used with 4 TV cameras paired on the two sides of the cyclist. Sampling frequency was 100 Hz Size of the passive retroreflective markers was 10 mm in diameter. The 3-D body coordinates (iliac crest, great trochanter, femoral condile, malleolus, fifth metatarsal head) and some anthropometric measures of the subject were the input of a mathematical model designed to describe the spatial kinematics of seven rigid segments belonging to the lower limbs (feet, shanks, thighs and pelvis). RESULTS Tables 1 and 2 show the mean and the standard deviation of some of the variables used for the analysis They have been computed by grouping right and left patterns of the whole group As it can be seen, when the load changes there is an evident trend of some variables. For example, the range of motion decreases at the hip joint, when the load Increases, conversely it increases at the knee and at the ankle joint. The individual examination revealed as the majority of athletes were characterized by significant left-right differences in the selected lower leg angles and in some linear kinematic parameters. These asymmetries appear to be subject, joint and pedalling modality dependent. CONCLUSION The method presented here seems to be an useful tool to assess and to evaluate biomechanical data during cycling. The proposed kinematic model gives indeed a good representation of the cyclist during his action. In particular the possibility to collect simultaneously data from both sides of the body appears to be very informative about asymmetries characterizing cyclists.
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