S56 Abstracts of the 17th Annual Meeting of ESMAC, Poster Presentations / Gait & Posture 28S (2008) S49–S118 [3] JR. Gage, 2004 The Treatment of Gait Problems in Cerebral Palsy, Mac Keith Press, London, UK. [4] Akalan N.E., 2008. The influence of increased patellar tendon length on knee extension biomechanics during knee extension exercise, ESMAC, Antalya. [5] Abdel-Rahman, E.M., Hefzy, M.S., 1998. Journal of Biomechanics 20, 276-90. 6. Caruntu, D.I. Hefzy M.S., 2004. Journal of Biomechanical Engineering 126 (1), 44-53. P011 Functional degrees of freedom of neck movements: linear models may overestimate variability A. Page 1 , J.A. Galvez 1 , J.M. Baydal-Bertomeu 1 , V. Mata 2 , J.M. Belda-Lois 1 . 1 Instituto de Biomecanica de Valencia, Spain; 2 Departamento de Ingenieria Mecanica y de Materiales, Universidad Politecnica de Valencia, Spain Summary: In this work we analyze the functional degrees of freedom (fDOFs) of three neck movements used in clinical tests: sagittal flexion-extension, lateral flexion and lateral rotation. We also introduce the concept of considering nonlinear models for fDOF analysis and compare the results with those obtained using the linear approach. We found that the analyzed neck motions have only one fDOF, although linear models may detect false fDOFs. Conclusions: The simple neck movements studied in this work can be characterized as having only one fDOF each, since the main joint variable can by itself explain more than 98.7% of the variance in all three types of motion when a nonlinear model is used. The results obtained with principal components analysis (PCA) are similar, but the first factor explains a smaller fraction of the variance in all cases, because PCA cannot detect nonlinear relations. Thus the use of PCA for the fDOF analysis of natural movements may lead to the identification of false fDOFs associated with degrees of freedom (DOFs) whose relation to the other DOFs is extremely nonlinear. Introduction: The concept of fDOF was introduced recently to analyze the control mechanisms of human motions (see [1] and the references cited therein). These studies used linear procedures such as PCA with simple models of the joints involved. However, there are fewer studies about motion coordination of complex joints such as the neck or the lumbar spine. Knowledge about these joints could be valuable to define the number of DOFs that need to be considered in clinical assessment tests. The goals of this work were twofold: first, to analyze the fDOFs of the neck movements most commonly used in clinical tests; second, to study the effect of the linearization implicit in PCA, by comparing the results with those obtained when considering nonlinear relations between DOFs. Patients/Materials and Methods: We analyzed sagittal flexion- extension, lateral flexion and lateral rotation of the neck in a subsample of five healthy subjects taken from a previous study [2]. The six DOFs of the head were defined using the three coordinates of the centroid of the set of markers and the rotation angles with respect to a reference position. These variables were centred and rescaled to make the ranges of variation of angles and displacements comparable. For each movement, we performed a nonlinear fit between the main variable (the angle of sagittal flexion, lateral flexion or lateral rotation) and the other DOFs by means of the procedure described in [3]. We calculated the percentage of the total variance explained by this nonlinear fit and also obtained the corresponding nonlinear correlation coefficient. We subsequently compared the results with those obtained by PCA [1]. Results: The table below shows, for each type of movement, the proportions of variance explained by the first factor obtained from PCA and by the main variable with the nonlinear fit (average for the five subjects). We also included the correlations of the main variable with the z coordinate of the centroid of the set of markers, zG, to illustrate the effect of using a linear model, instead of a nonlinear one, for the identification of fDOFs. Neck movements Flexion-extension Lateral flexion Lateral rotation Linear Nonlinear Linear Nonlinear Linear Nonlinear Explained variance (%) 97.80 99.79 97.81 98.71 98.42 98.93 R of zG with main variable 0.569 0.998 0.294 0.993 0.297 0.910 Discussion: With the nonlinear fit, the variance accounted for by the main variable is very high in all cases, and always higher than the variance explained by the first principal component from the PCA, which includes a linear combination of variables. The correlations between zG and the main variable are systematically underestimated with the linear model, which could identify zG as an independent DOF not coordinated with the main variable. References [1] Li ZM. Functional Degrees of Freedom. Motor Control 2006; 10: 301– 310. [2] Baydal-Bertomeu JM, Serra-A˜ n´ o MP, Garrido-Ja´ en D, et al. Rehabil- itaci´ on 2007; 41: 53-60. [3] Page A, Candelas P, Belmar F. European Journal of Physics 2006; 27: 273–279. P012 Example of exercise caloric pattern in a subject with cardiovascular risk N. Deliu, V. Calota. Occupational Medicine, Institute of Public Health, Bucharest, Romania Summary: Starting from the difficulties encountered in clinical practice, such as lack of precise criteria for design of exercise programs in cardiovascular and metabolic disorders, the authors aimed to study caloric and cardiovascular patterns during walking on a treadmill in a subject with cardiovascular risk versus two normals. Conclusions: During walking at speed faster than usual walking speed (>1.4 m/s), the net metabolic rate of the subject with cardiovascular risk was higher with 25-30% than normals and exercise heart rate was 85-90% from maximal heart rate (anaerobic effort from Fox and Haskell diagram). On the basis of our results, the authors consider that exercise programs in cardiovascular and metabolic disorders should be planned taking account of caloric and cardiovascular pattern of each patient. For our patient we recommend 30 minutes/day, 5 days/week walking with 1.19 m/s, this work load having an aerobic (cardiotraining) effect. Introduction: In recovery programs of muscularticular, metabolic and cardiovascular diseases, exercise and diet play a central role. For designing these programs, the practitioners use medical guidelines (exercise of 150–200 kcal/session, 30 minute/day,