Statistical Analysis of Gait Maturation in Children Using Nonparametric Probability Density Function Modeling

Analysis of gait dynamics in children may help understand the development of neuromuscular control and maturation of locomotor function. This paper applied the nonparametric Parzen-window estimation method to establish the probability density function (PDF) models for the stride interval time series of 50 children (25 boys and 25 girls). Four statistical parameters, in terms of averaged stride interval (ASI), variation of stride interval (VSI), PDF skewness (SK), and PDF kurtosis (KU), were computed with the Parzen-window PDFs to study the maturation of stride interval in children. By analyzing the results of the children in three age groups (aged 3–5 years, 6–8 years, and 10–14 years), we summarize the key findings of the present study as follows. (1) The gait cycle duration, in terms of ASI, increases until 14 years of age. On the other hand, the gait variability, in terms of VSI, decreases rapidly until 8 years of age, and then continues to decrease at a slower rate. (2) The SK values of both the histograms and Parzen-window PDFs for all of the three age groups are positive, which indicates an imbalance in the stride interval distribution within an age group. However, such an imbalance would be meliorated when the children grow up. (3) The KU values of both the histograms and Parzen-window PDFs decrease with the body growth in children, which suggests that the musculoskeletal growth enables the children to modulate a gait cadence with ease. (4) The SK and KU results also demonstrate the superiority of the Parzen-window PDF estimation method to the Gaussian distribution modeling, for the study of gait maturation in children.This work was supported by the Fundamental Research Funds for the Central Universities of China (grant no. 2010121061), the Natural Science Foundation of Fujian (grant no. 2011J01371), and the National Natural Science Foundation of China (grant no. 81101115). N. Xiang was supported by Xiamen University Undergraduate Innovation Training Project (grant no. XDDC201210384072). Z. T. Zhong was supported by the Fundamental Research Funds for the Central Universities (grant no. CXB2011023). J. He was supported by the Xiamen University undergraduate student innovative experiment project (grant no. XDDC2011007). The authors acknowledge Hausdorff et al. for providing the data of gait experiments with public access via PhysioNet

19th Annual Symposium of the School of Science, Engineering and Health

We in the School of Science, Engineering and Health welcome you to this 19th Annual Symposium, and we are pleased to invite you to join us physically on campus in the Frey, Kline, and Jordan buildings or to join sessions virtually. Each year our students, faculty and staff present the fruits of their basic and applied research in science and health fields. The outcomes of scientific research expand intellectual understanding and have tremendous impact on quality of life, environmental health, and human flourishing. We warmly welcome you as guests for the day. Angela Hare Dean School of Science, Engineering and Health, Messiah Universit

Treatment with FRAX486 rescues neurobehavioral and metabolic alterations in a female mouse model of CDKL5 deficiency disorder

Introduction: CDKL5 deficiency disorder (CDD) is a rare neurodevelopmental condition, primarily affecting girls for which no cure currently exists. Neuronal morphogenesis and plasticity impairments as well as metabolic dysfunctions occur in CDD patients. The present study explored the potential therapeutic value for CDD of FRAX486, a brain-penetrant molecule that was reported to selectively inhibit group I p21-activated kinases (PAKs), serine/threonine kinases critically involved in the regulation of neuronal morphology and glucose homeostasis.Methods: The effects of treatment with FRAX486 on CDD-related alterations were assessed in vitro (100 nM for 48h) on primary hippocampal cultures from Cdkl5-knockout male mice (Cdkl5-KO) and in vivo (20 mg/Kg, s.c. for 5 days) on Cdkl5-KO heterozygous females (Cdkl5-Het).Results: The in vitro treatment with FRAX486 completely rescued the abnormal neuronal maturation and the number of PSD95-positive puncta in Cdkl5-KO mouse neurons. In vivo, FRAX486 normalized the general health status, the hyperactive profile and the fear learning defects of fully symptomatic Cdkl5-Het mice. Systemically, FRAX486 treatment normalized the levels of reactive oxidizing species in the whole blood and the fasting-induced hypoglycemia displayed by CdklS-Het mice. In the hippocampus of Cdkl5-Het mice, treatment with FRAX486 rescued spine maturation and PSD95 expression and restored the abnormal PAKs phosphorylation at sites which are critical for their activation (P-PAK-Ser144/141/139) or for the control cytoskeleton remodeling (P-PAK1-Thr212).Conclusions: Present results provide evidence that PAKs may represent innovative therapeutic targets for CDD

Advances in Neural Signal Processing

Neural signal processing is a specialized area of signal processing aimed at extracting information or decoding intent from neural signals recorded from the central or peripheral nervous system. This has significant applications in the areas of neuroscience and neural engineering. These applications are famously known in the area of brain–machine interfaces. This book presents recent advances in this flourishing field of neural signal processing with demonstrative applications

Advances in Neural Signal Processing

Neural signal processing is a specialized area of signal processing aimed at extracting information or decoding intent from neural signals recorded from the central or peripheral nervous system. This has significant applications in the areas of neuroscience and neural engineering. These applications are famously known in the area of brain–machine interfaces. This book presents recent advances in this flourishing field of neural signal processing with demonstrative applications

Advances in Neural Signal Processing

Neural signal processing is a specialized area of signal processing aimed at extracting information or decoding intent from neural signals recorded from the central or peripheral nervous system. This has significant applications in the areas of neuroscience and neural engineering. These applications are famously known in the area of brain–machine interfaces. This book presents recent advances in this flourishing field of neural signal processing with demonstrative applications