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https://www.readbyqxmd.com/read/28335555/activity-recognition-and-semantic-description-for-indoor-mobile-localization
#1
Sheng Guo, Hanjiang Xiong, Xianwei Zheng, Yan Zhou
As a result of the rapid development of smartphone-based indoor localization technology, location-based services in indoor spaces have become a topic of interest. However, to date, the rich data resulting from indoor localization and navigation applications have not been fully exploited, which is significant for trajectory correction and advanced indoor map information extraction. In this paper, an integrated location acquisition method utilizing activity recognition and semantic information extraction is proposed for indoor mobile localization...
March 21, 2017: Sensors
https://www.readbyqxmd.com/read/28320669/regularized-speaker-adaptation-of-kl-hmm-for-dysarthric-speech-recognition
#2
Myungjong Kim, Younggwan Kim, Joohong Yoo, Jun Wang, Hoirin Kim
This paper addresses the problem of recognizing the speech uttered by patients with dysarthria, which is a motor speech disorder impeding the physical production of speech. Patients with dysarthria have articulatory limitation, and therefore, they often have trouble in pronouncing certain sounds, resulting in undesirable phonetic variation. Modern automatic speech recognition systems designed for regular speakers are ineffective for dysarthric sufferers due to the phonetic variation. To capture the phonetic variation, Kullback-Leibler divergence based hidden Markov model (KL-HMM) is adopted, where the emission probability of state is parametrized by a categorical distribution using phoneme posterior probabilities obtained from a deep neural network-based acoustic model...
March 13, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28320309/correlated-duplications-and-losses-in-the-evolution-of-palmitoylation-writer-and-eraser-families
#3
Stijn Wittouck, Vera van Noort
BACKGROUND: Protein post-translational modifications (PTMs) change protein properties. Each PTM type is associated with domain families that apply the modification (writers), remove the modification (erasers) and bind to the modified sites (readers) together called toolkit domains. The evolutionary origin and diversification remains largely understudied, except for tyrosine phosphorylation. Protein palmitoylation entails the addition of a palmitoyl fatty acid to a cysteine residue. This PTM functions as a membrane anchor and is involved in a range of cellular processes...
March 20, 2017: BMC Evolutionary Biology
https://www.readbyqxmd.com/read/28289426/transcriptome-wide-identification-classification-and-characterization-of-ap2-erf-family-genes-in-the-desert-moss-syntrichia-caninervis
#4
Xiaoshuang Li, Daoyuan Zhang, Bei Gao, Yuqing Liang, Honglan Yang, Yucheng Wang, Andrew J Wood
APETALA2/Ethylene Responsive Factor (AP2/ERF) is a large family of plant transcription factors which play important roles in the control of plant metabolism and development as well as responses to various biotic and abiotic stresses. The desert moss Syntrichia caninervis, due to its robust and comprehensive stress tolerance, is a promising organism for the identification of stress-related genes. Using S. caninervis transcriptome data, 80 AP2/ERF unigenes were identified by HMM modeling and BLASTP searching...
2017: Frontiers in Plant Science
https://www.readbyqxmd.com/read/28287133/activated-full-length-myosin-x-moves-processively-on-filopodia-with-large-steps-toward-diverse-two-dimensional-directions
#5
Osamu Sato, Hyun Suk Jung, Satoshi Komatsu, Yoshikazu Tsukasaki, Tomonobu M Watanabe, Kazuaki Homma, Mitsuo Ikebe
Myosin-X, (Myo 10), is an unconventional myosin that transports the specific cargos to filopodial tips, and is associated with the mechanism underlying filopodia formation and extension. To clarify the innate motor characteristic, we studied the single molecule movement of a full-length myosin-X construct with leucine zipper at the C-terminal end of the tail (M10(Full)LZ) and the tail-truncated myosin-X without artificial dimerization motif (BAP-M10(1-979)HMM). M10(Full)LZ localizes at the tip of filopodia like myosin-X full-length (M10(Full))...
March 13, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28272531/non-invasive-prenatal-diagnosis-of-beta-thalassemia-by-semiconductor-sequencing-a-feasibility-study-in-the-sardinian-population
#6
Luisella Saba, Maddalena Masala, Valentina Capponi, Giuseppe Marceddu, Matteo Massidda, Maria Cristina Rosatelli
β-Thalassemia is the most common autosomal recessive single-gene disorder in Sardinia, where approximately 10.3% of the population is a carrier. Prenatal diagnosis is carried out at 12 weeks of gestation via villocentesis and is commonly aimed at ascertaining the presence or absence of the HBB variant c.118C>T, which is the most common in Sardinia. In this study, we describe for the first time the application of semiconductor sequencing to the non-invasive prenatal diagnosis of β-thalassemia in 37 couples at risk for this variant...
March 8, 2017: European Journal of Human Genetics: EJHG
https://www.readbyqxmd.com/read/28269527/predicting-short-term-icu-outcomes-using-a-sequential-contrast-motif-based-classification-framework
#7
Shameek Ghosh, Hung Nguyen, Jinyan Li
Critical ICU events like acute hypotension and septic shock are dangerous complications, leading to multiple organ failures and eventual death. Previously, pattern mining algorithms have been employed for extracting interesting rules in various clinical domains. However, the extracted rules are directly investigated by clinicians for diagnosing a disease. Towards this purpose, there is a need to develop advanced prediction models which integrate dynamic patterns to learn a patient's physiological condition...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269158/detecting-cell-division-of-pseudomonas-aeruginosa-bacteria-from-bright-field-microscopy-images-with-hidden-conditional-random-fields
#8
Lee-Ling S Ong, Xinghua Zhang, Binu Kundukad, Justin Dauwels, Patrick Doyle, H Harry Asada
An approach to automatically detect bacteria division with temporal models is presented. To understand how bacteria migrate and proliferate to form complex multicellular behaviours such as biofilms, it is desirable to track individual bacteria and detect cell division events. Unlike eukaryotic cells, prokaryotic cells such as bacteria lack distinctive features, causing bacteria division difficult to detect in a single image frame. Furthermore, bacteria may detach, migrate close to other bacteria and may orientate themselves at an angle to the horizontal plane...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268626/multistep-model-for-predicting-upper-limb-3d-isometric-force-application-from-pre-movement-electrocorticographic-features
#9
Jing Wu, Benjamin R Shuman, Bingni W Brunton, Katherine M Steele, Jared D Olson, Rajesh P N Rao, Jeffrey G Ojemann
Neural correlates of movement planning onset and direction may be present in human electrocorticography in the signal dynamics of both motor and non-motor cortical regions. We use a three-stage model of jPCA reduced-rank hidden Markov model (jPCA-RR-HMM), regularized shrunken-centroid discriminant analysis (RDA), and LASSO regression to extract direction-sensitive planning information and movement onset in an upper-limb 3D isometric force task in a human subject. This mode achieves a relatively high true positive force-onset prediction rate of 60% within 250ms, and an above-chance 36% accuracy (17% chance) in predicting one of six planned 3D directions of isometric force using pre-movement signals...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268460/autonomous-vision-guided-approach-for-the-analysis-and-grading-of-vertical-suspension-tests-during-hammersmith-infant-neurological-examination-hine
#10
Prasenjit Dey, Debi Prosad Dogra, Partha Pratim Roy, Harish Bhaskar
Computer vision assisted diagnostic systems are gaining popularity in different healthcare applications. This paper presents a video analysis and pattern recognition framework for the automatic grading of vertical suspension tests on infants during the Hammersmith Infant Neurological Examination (HINE). The proposed vision-guided pipeline applies a color-based skin region segmentation procedure followed by the localization of body parts before feature extraction and classification. After constrained localization of lower body parts, a stick-diagram representation is used for extracting novel features that correspond to the motion dynamic characteristics of the infant's leg movements during HINE...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268332/towards-an-unsupervised-device-for-the-diagnosis-of-childhood-pneumonia-in-low-resource-settings-automatic-segmentation-of-respiratory-sounds
#11
J Sola, F Braun, E Muntane, C Verjus, M Bertschi, F Hugon, S Manzano, M Benissa, A Gervaix
Pneumonia remains the worldwide leading cause of children mortality under the age of five, with every year 1.4 million deaths. Unfortunately, in low resource settings, very limited diagnostic support aids are provided to point-of-care practitioners. Current UNICEF/WHO case management algorithm relies on the use of a chronometer to manually count breath rates on pediatric patients: there is thus a major need for more sophisticated tools to diagnose pneumonia that increase sensitivity and specificity of breath-rate-based algorithms...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28267626/bayesian-switching-factor-analysis-for-estimating-time-varying-functional-connectivity-in-fmri
#12
Jalil Taghia, Srikanth Ryali, Tianwen Chen, Kaustubh Supekar, Weidong Cai, Vinod Menon
There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000)...
March 3, 2017: NeuroImage
https://www.readbyqxmd.com/read/28253858/a-hybrid-method-for-the-imputation-of-genomic-data-in-livestock-populations
#13
Roberto Antolín, Carl Nettelblad, Gregor Gorjanc, Daniel Money, John M Hickey
BACKGROUND: This paper describes a combined heuristic and hidden Markov model (HMM) method to accurately impute missing genotypes in livestock datasets. Genomic selection in breeding programs requires high-density genotyping of many individuals, making algorithms that economically generate this information crucial. There are two common classes of imputation methods, heuristic methods and probabilistic methods, the latter being largely based on hidden Markov models. Heuristic methods are robust, but fail to impute markers in regions where the thresholds of heuristic rules are not met, or the pedigree is inconsistent...
March 3, 2017: Genetics, Selection, Evolution: GSE
https://www.readbyqxmd.com/read/28227782/predicting-short-term-icu-outcomes-using-a-sequential-contrast-motif-based-classification-framework
#14
Shameek Ghosh, Hung Nguyen, Jinyan Li, Shameek Ghosh, Hung Nguyen, Jinyan Li, Shameek Ghosh, Hung Nguyen, Jinyan Li
Critical ICU events like acute hypotension and septic shock are dangerous complications, leading to multiple organ failures and eventual death. Previously, pattern mining algorithms have been employed for extracting interesting rules in various clinical domains. However, the extracted rules are directly investigated by clinicians for diagnosing a disease. Towards this purpose, there is a need to develop advanced prediction models which integrate dynamic patterns to learn a patient's physiological condition...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227387/detecting-cell-division-of-pseudomonas-aeruginosa-bacteria-from-bright-field-microscopy-images-with-hidden-conditional-random-fields
#15
Lee-Ling S Ong, Xinghua Zhang, Binu Kundukad, Justin Dauwels, Patrick Doyle, H Harry Asada, Lee-Ling S Ong, Xinghua Zhang, Binu Kundukad, Justin Dauwels, Patrick Doyle, H Harry Asada, Binu Kundukad, Lee-Ling S Ong, Xinghua Zhang, Justin Dauwels, Patrick Doyle, H Harry Asada
An approach to automatically detect bacteria division with temporal models is presented. To understand how bacteria migrate and proliferate to form complex multicellular behaviours such as biofilms, it is desirable to track individual bacteria and detect cell division events. Unlike eukaryotic cells, prokaryotic cells such as bacteria lack distinctive features, causing bacteria division difficult to detect in a single image frame. Furthermore, bacteria may detach, migrate close to other bacteria and may orientate themselves at an angle to the horizontal plane...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226806/multistep-model-for-predicting-upper-limb-3d-isometric-force-application-from-pre-movement-electrocorticographic-features
#16
Jing Wu, Benjamin R Shuman, Bingni W Brunton, Katherine M Steele, Jared D Olson, Rajesh P N Rao, Jeffrey G Ojemann, Jing Wu, Benjamin R Shuman, Bingni W Brunton, Katherine M Steele, Jared D Olson, Rajesh P N Rao, Jeffrey G Ojemann, Rajesh P N Rao, Jared D Olson, Benjamin R Shuman, Katherine M Steele, Jing Wu, Jeffrey G Ojemann, Bingni W Brunton
Neural correlates of movement planning onset and direction may be present in human electrocorticography in the signal dynamics of both motor and non-motor cortical regions. We use a three-stage model of jPCA reduced-rank hidden Markov model (jPCA-RR-HMM), regularized shrunken-centroid discriminant analysis (RDA), and LASSO regression to extract direction-sensitive planning information and movement onset in an upper-limb 3D isometric force task in a human subject. This mode achieves a relatively high true positive force-onset prediction rate of 60% within 250ms, and an above-chance 36% accuracy (17% chance) in predicting one of six planned 3D directions of isometric force using pre-movement signals...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226633/autonomous-vision-guided-approach-for-the-analysis-and-grading-of-vertical-suspension-tests-during-hammersmith-infant-neurological-examination-hine
#17
Prasenjit Dey, Debi Prosad Dogra, Partha Pratim Roy, Harish Bhaskar, Prasenjit Dey, Debi Prosad Dogra, Partha Pratim Roy, Harish Bhaskar, Debi Prosad Dogra, Harish Bhaskar, Prasenjit Dey, Partha Pratim Roy
Computer vision assisted diagnostic systems are gaining popularity in different healthcare applications. This paper presents a video analysis and pattern recognition framework for the automatic grading of vertical suspension tests on infants during the Hammersmith Infant Neurological Examination (HINE). The proposed vision-guided pipeline applies a color-based skin region segmentation procedure followed by the localization of body parts before feature extraction and classification. After constrained localization of lower body parts, a stick-diagram representation is used for extracting novel features that correspond to the motion dynamic characteristics of the infant's leg movements during HINE...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226493/towards-an-unsupervised-device-for-the-diagnosis-of-childhood-pneumonia-in-low-resource-settings-automatic-segmentation-of-respiratory-sounds
#18
J Sola, F Braun, E Muntane, C Verjus, M Bertschi, F Hugon, S Manzano, M Benissa, A Gervaix, J Sola, F Braun, E Muntane, C Verjus, M Bertschi, F Hugon, S Manzano, M Benissa, A Gervaix, F Hugon, C Verjus, A Gervaix, S Manzano, M Bertschi, E Muntane, M Benissa, J Sola, F Braun
Pneumonia remains the worldwide leading cause of children mortality under the age of five, with every year 1.4 million deaths. Unfortunately, in low resource settings, very limited diagnostic support aids are provided to point-of-care practitioners. Current UNICEF/WHO case management algorithm relies on the use of a chronometer to manually count breath rates on pediatric patients: there is thus a major need for more sophisticated tools to diagnose pneumonia that increase sensitivity and specificity of breath-rate-based algorithms...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28224501/modeling-movement-primitives-with-hidden-markov-models-for-robotic-and-biomedical-applications
#19
Michelle Karg, Dana Kulić
Movement primitives are elementary motion units and can be combined sequentially or simultaneously to compose more complex movement sequences. A movement primitive timeseries consist of a sequence of motion phases. This progression through a set of motion phases can be modeled by Hidden Markov Models (HMMs). HMMs are stochastic processes that model time series data as the evolution of a hidden state variable through a discrete set of possible values, where each state value is associated with an observation (emission) probability...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28224500/automated-estimation-of-mouse-social-behaviors-based-on-a-hidden-markov-model
#20
Toshiya Arakawa, Akira Tanave, Aki Takahashi, Satoshi Kakihara, Tsuyoshi Koide, Takashi Tsuchiya
Recent innovations in sensing and Information and Communication Technology (ICT) have enabled researchers in animal behavior to collect an enormous amount of data. Consequently, the development of an automated system to substitute for some of the observations and analyses that are performed currently by expert researchers is becoming a crucial issue so that the vast amount of accumulated data can be processed efficiently. For this purpose, we introduce a process for the automated classification of the social interactive status of two mice in a square field on the basis of a Hidden Markov model (HMM)...
2017: Methods in Molecular Biology
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