ABSTRACT
AIM: Muscular strength of the leg extensor muscles in children can be affected by several factors such as age, sexual maturation, body mass and training status of the subjects. The purpose of the study was to examine maximal isometric strength characteristics of young male basketball players taking into consideration the combined effects of chronological age and sexual maturation. METHODS: One hundred and twenty male basketball players, aged from 12 to 17 years divided into 6 equivalent age subgroups performed maximum bilateral isometric leg press efforts. The parameters analysed were the maximal voluntary isometric force (MVC), relative strength (MVC/body mass and MVC/fat free mass), starting strength (F50: force exerted during the first 50 ms of the contraction) and speed strength index (the ratio of maximal force to time to attain maximal force). RESULTS: The results indicated that in almost all absolute force parameters, the 12-and 13-year olds demonstrated significantly (p<0.05) lower values compared with the 15(-1)6-and 17-years old groups. Age differences were also significant (p<0.05) when the effects of sexual maturation were taken into consideration in the statistical analysis but they were reduced when strength was adjusted for body mass. Finally, no significant differences for strength per unit of fat free mass were found (p>0.05). CONCLUSIONS: Maximum absolute strength of basketball players is significantly increased from 12 to 17 years and as sexual maturation stage increases. It also appears that body mass and fat free mass should be taken into consideration when examining age effects on strength in basketball players.
Subject(s)
Basketball/physiology , Isometric Contraction/physiology , Leg/physiology , Muscle, Skeletal/physiology , Physical Exertion/physiology , Adolescent , Age Factors , Biomechanical Phenomena , Child , Exercise Test , Humans , Male , Weight Lifting/physiologyABSTRACT
OBJECTIVES: This paper focusses on the person identification problem based on features extracted from the ElectroEncephaloGram (EEG). A bilinear rather than a purely linear model is fitted on the EEG signal, prompted by the existence of non-linear components in the EEG signal--a conjecture already investigated in previous research works. The novelty of the present work lies in the comparison between the linear and the bilinear results, obtained from real field EEG data, aiming towards identification of healthy subjects rather than classification of pathological cases for diagnosis. METHODS: The EEG signal of a, in principle, healthy individual is processed via (non)linear (AR, bilinear) methods and classified by an artificial neural network classifier. RESULTS: Experiments performed on real field data show that utilization of the bilinear model parameters as features improves correct classification scores at the cost of increased complexity and computations. Results are seen to be statistically significant at the 99.5% level of significance, via the chi 2 test for contingency. CONCLUSIONS: The results obtained in the present study further corroborate existing research, which shows evidence that the EEG carries individual-specific information, and that it can be successfully exploited for purposes of person identification and authentication.
Subject(s)
Electroencephalography , Pattern Recognition, Automated , Records , Signal Processing, Computer-Assisted , Humans , Neural Networks, ComputerABSTRACT
Person identification based on spectral information extracted from the EEG is addressed in this work a problem that has not yet been seen in a signal processing framework. Spectral features are extracted non-parametrically from real EEG data recorded from healthy individuals. Neural network classification is applied on these features using a Learning Vector Quantizer in an attempt to experimentally investigate the connection between a person's EEG and genetically specific information. The proposed method, compared with previously proposed methods, has yielded encouraging correct classification scores in the range of 80% to 100% (case-dependent). These results are in agreement with previous research showing evidence that the EEG carries genetic information.
Subject(s)
Anthropology, Physical/methods , Electroencephalography/methods , Neural Networks, Computer , Patient Identification Systems/methods , Signal Processing, Computer-Assisted , Adult , Alpha Rhythm , Beta Rhythm , False Negative Reactions , False Positive Reactions , Female , Fourier Analysis , Humans , Male , Medical Informatics Applications , Medical Informatics Computing , Middle Aged , Pedigree , Sensitivity and Specificity , Theta RhythmABSTRACT
User participation in HIS development is considered essential for achieving systems implementation success. Realizing a participative HIS development, where users are full members of the development team, requires not only choosing an appropriate methodology but also organizing the participation process in a way that is tailored to the particular situation in order to achieve the desired results. A general approach to this problem is presented in this paper. An application of the approach to the particular context of a Greek hospital is described.
