Classification of the mechanomyogram signal using a wavelet packet transform and singular value decomposition

Title on author’s file: Classification of mechanomyogram signal using wavelet packet transform and singular value decomposition for multifunction prosthesis control2008-2009 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Dynamic monitoring of forearm muscles using one-dimensional sonomyography system

2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

A Gaussian Bayesian model to identify spatio-temporal causalities for air pollution based on urban big data

Identifying the causalities for air pollutants and answering questions, such as, where do Beijing's air pollutants come from, are crucial to inform government decision-making. In this paper, we identify the spatio-temporal (ST) causalities among air pollutants at different locations by mining the urban big data. This is challenging for two reasons: 1) since air pollutants can be generated locally or dispersed from the neighborhood, we need to discover the causes in the ST space from many candidate locations with time efficiency; 2) the cause-and-effect relations between air pollutants are further affected by confounding variables like meteorology. To tackle these problems, we propose a coupled Gaussian Bayesian model with two components: 1) a Gaussian Bayesian Network (GBN) to represent the cause-and-effect relations among air pollutants, with an entropy-based algorithm to efficiently locate the causes in the ST space; 2) a coupled model that combines cause-and-effect relations with meteorology to better learn the parameters while eliminating the impact of confounding. The proposed model is verified using air quality and meteorological data from 52 cities over the period Jun 1st 2013 to May 1st 2015. Results show superiority of our model beyond baseline causality learning methods, in both time efficiency and prediction accuracy. © 2016 IEEE.postprintLink_to_subscribed_fulltex

Measurement of depth-dependence and anisotropy of ultrasound speed of bovine articular cartilage in vitro

Author name used in this publication: S. G. PatilAuthor name used in this publication: Y. P. ZhengAuthor name used in this publication: J. Y. WuAuthor name used in this publication: J. Shi2004-2005 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Continuous monitoring of electromyography (EMG), mechanomyography (MMG), sonomyography (SMG) and torque output during ramp and step isometric contractions

2010-2011 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Estimation of wrist angle from sonomyography using support vector machine and artificial neural network models

2008-2009 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

A simple method for estimating the convectiondispersion equation parameters of solute transport in agricultural ecosystem

The convection-dispersion equation (CDE) is the classical approach for modeling solute transport in porous media. So, estimating parameters became a key problem in CDE. For statistical method, some problems such as parameter uniqueness are still unsolved because of more factors. Due to the advantage of clear physical concept and unique parameter values, the simple deterministic method became very useful alternatives. In this paper, a simple method was proposed to estimate both D and R, and the validity was verified by experiment, which can be applied in agriculture and environmental fields for predicting soil quality property.Key words: Convection-dispersion equation (CDE), parameters estimation, agricultural system

Effects of calcium phosphate nanocrystals on osseointegration of titainium implant in irradiated bone

Radiotherapy may compromise the integration of implant and cause implant loss. Implant surface modifications have the possibility of promoting cell attachment, cell growth, and bone formation which ultimately enhance the osseointegration process. The present study aimed to investigate the effects of calcium phosphate nanocrystals on implant osseointegration in irradiated bone. Sixteen rabbits were randomly assigned into control and nano-CaP groups, receiving implants with dual acid-etched surface or dual acid-etched surface discretely deposited of nanoscale calcium-phosphate crystals, respectively. The left leg of all the rabbits received 15 Gy radiation, followed by implants placement one week after. Four animals in each group were sacrificed after 4 and 12 weeks, respectively. Implant stability quotient (ISQ), ratio of bone volume to total volume (BV/TV), bone growth rate, and bone-to-implant contact (BIC) were evaluated. The nano-CaP group showed significantly higher ISQ (week 12, P = 0.031) and bone growth rate (week 6, P = 0.021; week 9, P = 0.001) than that in control group. No significant differences in BV/TV and BIC were found between two groups. Titanium implant surface modified with CaP nanocrystals provides a potential alternative to improve bone healing around implant in irradiated bone.published_or_final_versio