823 resultados para walking stick


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STUDY DESIGN. Observational cohort study. OBJECTIVE. To investigate spinal coordination during preferred and fast speed walking in pain-free subjects with and without a history of recurrent low back pain (LBP). SUMMARY OF BACKGROUND DATA. Dynamic motion of the spine during walking is compromised in the presence of back pain (LBP), but its analysis often presents some challenges. The coexistence of significant symptoms may change gait because of pain or adaptation of the musculoskeletal structures or both. A history of LBP without the overlay of a current symptomatic episode allows a better model in which to explore the impact on spinal coordination during walking. METHODS. Spinal and lower limb segmental motions were tracked using electromagnetic sensors. Analyses were conducted to explore the synchrony and spatial coordination of the segments and to compare the control and subjects with LBP. RESULTS. We found no apparent differences between the groups for either overall amplitude of motion or most indicators of coordination in the lumbar region; however, there were significant postural differences in the mid-stance phase and other indicators of less phase locking in controls compared with subjects with LBP. The lower thoracic spinal segment was more affected by the history of back pain than the lumbar segment. CONCLUSION. Although small, there were indicators that alterations in spinal movement and coordination in subjects with recurrent LBP were due to adaptive changes rather than the presence of pain. © 2013, Lippincott Williams & Wilkins.

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Background: Several factors may influence kinetic data measurements, including body conformation and body mass. In addition, gender differences in gait pattern have been observed in healthy humans. Therefore, the aim of this study was to compare the kinetic and temporospatial parameters in clinically healthy male and female cats using a pressure-sensitive walkway. Eighteen crossbreed adult cats were divided into two groups: G1 had ten male cats (nine neutered) aged from 1 to 4 years and body mass 3.1-6.8 kg; G2 had eight spayed female cats, aged from 1 to 6 years and body mass 3.3-4.75 kg. The data from the first five valid trials were collected for each cat. A trial was considered valid if the cat maintained a velocity between 0.54-0.74 m/s and acceleration from -0.20 to 0.20 m/s2. The peak vertical force (PVF), vertical impulse (VI), gait cycle time, stance time, swing time, stride length, and percentage body weight distribution among the four limbs were determined. In addition, the lengths of each forelimb and each hind limb were measured using a tape with the animal standing.Results: No significant differences were observed in each group in either the forelimbs or the hind limbs or between the left and right sides for any of the variables. For both groups, the PVF (%BW), the VI, and the percentage body weight distribution were higher at the forelimbs than the hind limbs. The stride length was larger for males; however, the other kinetic and temporospatial variables did not show any statistically significant differences between the groups. The lengths of the forelimbs and hind limbs were larger in the male cats. There was a significant moderate positive correlation between the stride length and the length of the limbs.Conclusions: In conclusion, the only difference observed between male and female cats was the stride length, and this was due to the greater body size of male cats. This difference did not affect other temporospatial or kinetics variables. © 2013 Verdugo et al.; licensee BioMed Central Ltd.

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Pós-graduação em Ciências da Motricidade - IBRC

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Both Semi-Supervised Leaning and Active Learning are techniques used when unlabeled data is abundant, but the process of labeling them is expensive and/or time consuming. In this paper, those two machine learning techniques are combined into a single nature-inspired method. It features particles walking on a network built from the data set, using a unique random-greedy rule to select neighbors to visit. The particles, which have both competitive and cooperative behavior, are created on the network as the result of label queries. They may be created as the algorithm executes and only nodes affected by the new particles have to be updated. Therefore, it saves execution time compared to traditional active learning frameworks, in which the learning algorithm has to be executed several times. The data items to be queried are select based on information extracted from the nodes and particles temporal dynamics. Two different rules for queries are explored in this paper, one of them is based on querying by uncertainty approaches and the other is based on data and labeled nodes distribution. Each of them may perform better than the other according to some data sets peculiarities. Experimental results on some real-world data sets are provided, and the proposed method outperforms the semi-supervised learning method, from which it is derived, in all of them.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)