New Linguistic Description Approach for Time Series and its Application to Bed Restlessness Monitoring for Eldercare.

Time series analysis has been an active area of research for years, with important applications in forecasting or discovery of hidden information such as patterns or anomalies in observed data. In recent years, the use of time series analysis techniques for the generation of descriptions and summaries in natural language of any variable, such as temperature, heart rate or CO2 emission has received increasing attention. Natural language has been recognized as more effective than traditional graphical representations of numerical data in many cases, in particular in situations where a large amount of data needs to be inspected or when the user lacks the necessary background and skills to interpret it. In this work, we describe a novel mechanism to generate linguistic descriptions of time series using natural language and fuzzy logic techniques. The proposed method generates quality summaries capturing the time series features that are relevant for a user in a particular application, and can be easily customized for different domains. This approach has been successfully applied to the generation of linguistic descriptions of bed restlessness data from residents at TigerPlace (Columbia, Missouri), which is used as a case study to illustrate the modeling process and show the quality of the descriptions obtained.

Genome-wide linkage analyses identify Hfhl1 and Hfhl3 with frequency-specific effects on the hearing spectrum of NIH Swiss mice.

BACKGROUND: The mammalian cochlea receives and analyzes sound at specific places along the cochlea coil, commonly referred to as the tonotopic map. Although much is known about the cell-level molecular defects responsible for severe hearing loss, the genetics responsible for less severe and frequency-specific hearing loss remains unclear. We recently identified quantitative trait loci (QTLs) Hfhl1 and Hfhl2 that affect high-frequency hearing loss in NIH Swiss mice. Here we used 2f1-f2 distortion product otoacoustic emissions (DPOAE) measurements to refine the hearing loss phenotype. We crossed the high frequency hearing loss (HFHL) line of NIH Swiss mice to three different inbred strains and performed linkage analysis on the DPOAE data obtained from the second-generation populations. RESULTS: We identified a QTL of moderate effect on chromosome 7 that affected 2f1-f2 emissions intensities (Hfhl1), confirming the results of our previous study that used auditory brainstem response (ABR) thresholds to identify QTLs affecting HFHL. We also identified a novel significant QTL on chromosome 9 (Hfhl3) with moderate effects on 2f1-f2 emissions intensities. By partitioning the DPOAE data into frequency subsets, we determined that Hfhl1 and Hfhl3 affect hearing primarily at frequencies above 24 kHz and 35 kHz, respectively. Furthermore, we uncovered additional QTLs with small effects on isolated portions of the DPOAE spectrum. CONCLUSIONS: This study identifies QTLs with effects that are isolated to limited portions of the frequency map. Our results support the hypothesis that frequency-specific hearing loss results from variation in gene activity along the cochlear partition and suggest a strategy for creating a map of cochlear genes that influence differences in hearing sensitivity and/or vulnerability in restricted portions of the cochlea.

Corrections to "Cardiovascular Function and Ballistocardiogram: A Relationship Interpreted via Mathematical Modeling" [Oct 19 2906-2917].

Presents a missing funding acknowledgment for Dr. Mihail Popescu in the above named paper.

Automated geospatial conflation of vector road maps to high resolution imagery.

As the availability of various geospatial data increases, there is an urgent need to integrate multiple datasets to improve spatial analysis. However, since these datasets often originate from different sources and vary in spatial accuracy, they often do not match well to each other. In addition, the spatial discrepancy is often nonsystematic such that a simple global transformation will not solve the problem. Manual correction is labor-intensive and time-consuming and often not practical. In this paper, we present an innovative solution for a vector-to-imagery conflation problem by integrating several vector-based and image-based algorithms. We only extract the different types of road intersections and terminations from imagery based on spatial contextual measures. We eliminate the process of line segment detection which is often troublesome. The vector road intersections are matched to these detected points by a relaxation labeling algorithm. The matched point pairs are then used as control points to perform a piecewise rubber-sheeting transformation. With the end points of each road segment in correct positions, a modified snake algorithm maneuvers intermediate vector road vertices toward a candidate road image. Finally a refinement algorithm moves the points to center each road and obtain better cartographic quality. To test the efficacy of the automated conflation algorithm, we used U.S. Census Bureau's TIGER vector road data and U.S. Department of Agriculture's 1-m multi-spectral near infrared aerial photography in our study. Experiments were conducted over a variety of rural, suburban, and urban environments. The results demonstrated excellent performance. The average correctness measure increased from 20.6% to 95.5% and the average root-mean-square error decreased from 51.2 to 3.4 m.

Cardiovascular Function and Ballistocardiogram: A Relationship Interpreted via Mathematical Modeling.

OBJECTIVE: To develop quantitative methods for the clinical interpretation of the ballistocardiogram (BCG). METHODS: A closed-loop mathematical model of the cardiovascular system is proposed to theoretically simulate the mechanisms generating the BCG signal, which is then compared with the signal acquired via accelerometry on a suspended bed. RESULTS: Simulated arterial pressure waveforms and ventricular functions are in good qualitative and quantitative agreement with those reported in the clinical literature. Simulated BCG signals exhibit the typical I, J, K, L, M, and N peaks and show good qualitative and quantitative agreement with experimental measurements. Simulated BCG signals associated with reduced contractility and increased stiffness of the left ventricle exhibit different changes that are characteristic of the specific pathological condition. CONCLUSION: The proposed closed-loop model captures the predominant features of BCG signals and can predict pathological changes on the basis of fundamental mechanisms in cardiovascular physiology. SIGNIFICANCE: This paper provides a quantitative framework for the clinical interpretation of BCG signals and the optimization of BCG sensing devices. The present paper considers an average human body and can potentially be extended to include variability among individuals.

Genetic differences in sensitivity to alterations of mandible structure caused by the teratogen 2,3,7,8-tetrachlorodibenzo-p-dioxin.

The contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is an environmental pollutant and teratogen that has been shown to alter craniofacial development. Differences in sensitivity to TCDD are attributed primarily to differences in alleles at the Ahr locus coding for the aryl-hydrocarbon receptor (AHR) that binds TCDD and mediates its effects by altering gene expression. The authors used geometric morphometric methods to evaluate differences in the effects of small in utero exposures of TCDD on adult mandible size and shape in five different inbred mouse strains with the same Ahr alleles. Because of the known effects of this toxicant on bone and craniofacial structures, the authors hypothesized that TCDD would decrease mandible size and alter mandible shape, but that the effects of TCDD exposure would differ among the inbred strains. The authors found that TCDD did alter mandible size and shape, but these effects were limited to specific strains and also differed between the sexes. The relative sensitivity to TCDD's effects on mandibles did not correspond with the previously reported sensitivity to TCDD's effects on molars. The authors hypothesize that beyond Ahr-related effects, variation in response to TCDD reflects differences in the genetic architecture controlling the trait being evaluated, thus explaining the species, strain, and trait specificity of TCDD.

Effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin on molar development among non-resistant inbred strains of mice: a geometric morphometric analysis.

Prenatal development is highly sensitive to the effects of environmental contaminants. 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is an environmental toxicant that at very low levels causes teratogenic effects such as irregular tooth development. Variations in susceptibility to TCDD's effects have been attributed primarily to differences at the Ahr locus. There is some evidence, however, that genes at other loci may be involved in mediating TCDD's effects on various endpoints. Our hypothesis therefore was that the effect of TCDD on molar development would differ even among inbred mouse strains possessing similar Ahr alleles. To test this, geometric morphometric techniques were used to evaluate the effects of several different levels of TCDD on molar size, shape and asymmetry in the offspring of dosed females from five different inbred strains of mice bearing TCDD-sensitive Ahr alleles. The results indicated that a maternal dose of 1 microg TCDD/kg body weight on gestation day 13 altered the shape (but not the size or asymmetry) of the first two molars in mice from the C3H/HeJ and CBA/J strains of mice, but not in mice from the other strains. The C3H/HeJ and CBA/J strains appeared to be the most sensitive to the disruption of molar development via TCDD and the C57BL/6J strain appeared to be the least sensitive.

Sleep Posture Classification Using Bed Sensor Data and Neural Networks.

Sleep posture has been shown to be important in monitoring health conditions such as congestive heart failure (CHF), sleep apnea, pressure ulcers, and even blood pressure abnormalities. In this paper, we investigate the use of four hydraulic bed transducers placed underneath the mattress to classify different sleep postures. For classification, we employed a simple neural network. Different combinations of parameters were studied to determine the best configuration. Data were collected on four major postures from 58 subjects. We report the results of classification for different combinations of these four postures. Both 10-Fold and Leave-One-Subject-Out (LOSO) Cross-validations (CV) were used to evaluate the accuracy of our predictions. Our results show that there are multiple configuration settings that make classification accuracy as high as 100% using k-Fold CV for all postures. Maximum classification accuracy after applying LOSO is 93% for a two-class classification of separating Left vs. Right lateral positions. The second-best classification accuracy with LOSO is 92% for the classification of lateral versus non-lateral.

Shear wave elastography and Afirma™ gene expression classifier in thyroid nodules with indeterminate cytology: a comparison study.

PURPOSE: To compare shear wave elastography (SWE) and Afirma™ gene expression classifier (GEC) for diagnosis of malignancy in thyroid nodules (TNs) with Bethesda Classification (BC) III or IV indeterminate cytology. METHODS: This preliminary single-center prospective study was approved by the Institutional Review Board. We evaluated 151 consented patients with 151 indeterminate TNs (123 BC III, 28 BC IV) on fine-needle aspiration biopsy (FNAB). B-mode ultrasound, vascularity, and SWE were performed prior to FNAB. TN stiffness was measured as shear wave velocity (SWV) in meters per second (m/s). The stiffest area of the TN was selected for SWV measurement. GEC testing was performed with a second FNAB. Surgery was recommended for GEC-suspicious TNs, or GEC-benign TNs with two or more worrisome B-mode US features. RESULTS: Surgical pathology confirmed 31 malignant TNs. Among the GEC-suspicious group, 28 of 59 TNs were malignant. The SWV value of ≥3.59 m/s was the best cut-off for malignancy risk based on the receiver operating curve (ROC). Twenty-six malignant TNs had SWV ≥ 3.59 m/s. The sensitivity and specificity for SWV ≥ 3.59 m/s were 83.9 and 79.2%, respectively. Positive predictive value (PPV) was 51.0% and negative predictive value (NPV) was 95.0%. For the GEC-suspicious group, sensitivity, specificity, PPV, and NPV were 90.3, 74.2, 47.5, and 96.7%, respectively. In multivariate analysis, SWV and GEC-suspicious were significant predictors of malignancy, but B-mode features and vascularity were not. CONCLUSION: This preliminary study indicates that SWE and GEC are independent predictors of malignancy in TNs with BC III or IV.

Relational analysis of CpG islands methylation and gene expression in human lymphomas using possibilistic C-means clustering and modified cluster fuzzy density.

Heterogeneous genetic and epigenetic alterations are commonly found in human non-Hodgkin's lymphomas (NHL). One such epigenetic alteration is aberrant methylation of gene promoter-related CpG islands, where hypermethylation frequently results in transcriptional inactivation of target genes, while a decrease or loss of promoter methylation (hypomethylation) is frequently associated with transcriptional activation. Discovering genes with these relationships in NHL or other types of cancers could lead to a better understanding of the pathobiology of these diseases. The simultaneous analysis of promoter methylation using Differential Methylation Hybridization (DMH) and its associated gene expression using Expressed CpG Island Sequence Tag (ECIST) microarrays generates a large volume of methylation-expression relational data. To analyze this data, we propose a set of algorithms based on fuzzy sets theory, in particular Possibilistic c-Means (PCM) and cluster fuzzy density. For each gene, these algorithms calculate measures of confidence of various methylation-expression relationships in each NHL subclass. Thus, these tools can be used as a means of high volume data exploration to better guide biological confirmation using independent molecular biology methods.

The effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin on molar and mandible traits in congenic mice: a test of the role of the Ahr locus.

2,3,7,8-Tetracholorodibenzo-p-dioxin is a highly toxic substance that can cause a variety of adverse effects on organisms. While it has been shown that TCDD acts mainly through the aryl-hydrocarbon receptor (AHR), the mechanism of toxicity is not completely clear. To test the role of the AHR in mediating the effects of TCDD, we exposed two congenic strains of mice differing only at the Ahr locus (Ahr(b)/Ahr(b) and Ahr(d)/Ahr(d)) to TCDD (0, 0.01, 0, or 1 microg/kg body weight) in utero on gestation day 13 and examined the developmental effects on mandible and mandibular tooth row size and shape. Our hypothesis was that TCDD would significantly affect one or more of these endpoints in Ahr(b)/Ahr(b) mice, previously shown to be sensitive to the effects of TCDD, while causing little or no effect in mice carrying the less sensitive Ahr(d) allele. At the doses used in this study, TCDD did not alter the size of mandibles or molars in either Ahr(b)/Ahr(b) or Ahr(d)/Ahr(d) mice. However, we did find that the highest dose of TCDD altered mandible shape, but only in Ahr(b)/Ahr(b) (not Ahr(d)/Ahr(d)) male mice. Similarly, the highest dose of TCDD significantly altered molar shape in Ahr(b)/Ahr(b) but not Ahr(d)/Ahr(d) male mice, although females in both congenic strains were affected. These results suggest that the effects of TCDD on molar and mandible shape are influenced by the Ahr genotype but that males and females differ in sensitivity to both of these effects.

Fuzzy measures on the Gene Ontology for gene product similarity.

One of the most important objects in bioinformatics is a gene product (protein or RNA). For many gene products, functional information is summarized in a set of Gene Ontology (GO) annotations. For these genes, it is reasonable to include similarity measures based on the terms found in the GO or other taxonomy. In this paper, we introduce several novel measures for computing the similarity of two gene products annotated with GO terms. The fuzzy measure similarity (FMS) has the advantage that it takes into consideration the context of both complete sets of annotation terms when computing the similarity between two gene products. When the two gene products are not annotated by common taxonomy terms, we propose a method that avoids a zero similarity result. To account for the variations in the annotation reliability, we propose a similarity measure based on the Choquet integral. These similarity measures provide extra tools for the biologist in search of functional information for gene products. The initial testing on a group of 194 sequences representing three proteins families shows a higher correlation of the FMS and Choquet similarities to the BLAST sequence similarities than the traditional similarity measures such as pairwise average or pairwise maximum.

Sleep stage recognition using respiration signal.

This paper presents a sleep stage recognition system for Awake, rapid eye movement (REM) and non-REM (NREM) sleep detection. Two respiratory variability (RV) features are extracted from oro-nasal airflow signals provided in the sleep-EDF (Expanded) database. A two layer system with threshold comparison classifier is implemented. This system achieved state-of-the-art performance with simple features and classifiers. The average accuracy of 74.00%±5.30% and Cohen's kappa coefficient of 0.49±0.08 were achieved with 21 recordings. In the end, the measure of sleep efficiency was calculated and the average absolute error was 3.61%±3.66%.

Shear Wave Elastography and Cervical Lymph Nodes: Predicting Malignancy.

This prospective study evaluates the accuracy of virtual touch imaging quantification (VTIQ), a non-invasive shear wave elastography method for measuring cervical lymph nodes (LN) stiffness in differentiating benign from malignant LN. The study evaluated 270 LN in 236 patients with both conventional B-mode ultrasound and VTIQ shear wave elastography before fine-needle aspiration biopsy (FNAB). LN stiffness was measured as shear wave velocity (SWV) in m/s. Surgical resection was advised for FNAB results that were not clearly benign. Surgical pathology confirmed 54 malignant LN. The receiver operating curve (ROC) identified a single cut-off value of 2.93 m/s as the maximum SWV for predicting a malignant cervical LN. The sensitivity and specificity were 92.59% and 75.46%, respectively. Positive predictive value (PPV) was 48.54% and negative predictive value (NPV) was 97.60%. LN stiffness measured by VTIQ-generated shear wave elastography is an independent predictor of malignancy.

Shear wave elastography and parathyroid adenoma: A new tool for diagnosing parathyroid adenomas.

OBJECTIVES: This study prospectively determines the shear wave elastography characteristics of parathyroid adenomas using virtual touch imaging quantification, a non-invasive ultrasound based shear wave elastography method. METHODS: This prospective study examined 57 consecutive patients with biochemically proven primary hyperparathyroidism and solitary parathyroid adenoma identified by ultrasound and confirmed by at least one of the following: surgical resection, positive Technetium-99m Sestamibi Scintigraphy (MIBI) scan, or fine needle aspiration biopsy with positive PTH washout (performed only in MIBI negative patients). Vascularity and shear wave elastography were performed for all patients. Parathyroid adenoma stiffness was measured as shear wave velocity in meters per second. RESULTS: The median (range) pre-surgical value for PTH and calcium were 58pg/mL (19, 427) and 10.8mg/dL (9.5, 12.1), respectively. 37 patients had positive MIBI scan. 20 patients had negative MIBI scan but diagnosis was confirmed with positive PTH washout. 42 patients underwent parathyroidectomy, and an adenoma was confirmed in all. The median (range) shear wave velocity for all parathyroid adenomas enrolled in this study was 2.02m/s (1.53, 2.50). The median (range) shear wave velocity for thyroid tissue was 2.77m/s (1.89, 3.70). The shear wave velocity of the adenomas was independent of adenoma size, serum parathyroid hormone concentration, or plasma parathyroid hormone concentration. CONCLUSIONS: Tissue elasticity of parathyroid adenoma is significantly lower than thyroid tissue. B-mode features and distinct vascularity pattern are helpful tools in diagnosing parathyroid adenoma with ultrasound. Shear wave elastography may provide valuable information in diagnosing parathyroid adenoma.

Textual summarization of events leading to health alerts.

Extracting information from the sensors installed in the homes of elderly pose a unique set of challenges. Add to it the short amount of time the clinicians and nurses have to analyze this data, and the problem becomes more complicated. A system already in place at an "Aging in Place" facility monitors the activities of residents through multiple non-intrusive sensors and sends alerts on detecting an unusual event. We present an approach to generate textual summaries of events leading to the alerts. We analyze our system using four case studies and also list the comments provided by collaborators in healthcare domain. The system was then iterated to take some of those suggestions into account to give a glimpse of what an ideal system should look like.

Thyroid Nodules and Shear Wave Elastography: A New Tool in Thyroid Cancer Detection.

This study determines the performance of virtual touch imaging quantification (VTIQ), a non-invasive shear wave elastography method for measuring thyroid nodule (TN) stiffness, in distinguishing benign from malignant TNs. This prospective study evaluates 707 TNs in 676 patients with fine-needle aspiration biopsy (FNAB). Before FNAB, both conventional B-mode ultrasound and shear wave elastography were performed. Surgical resection was recommended for FNAB results that were not clearly benign. Surgical pathology confirmed 82 malignant TNs. The receiver operating curve identified a single cut-off of 3.54 m/s as the maximum shear wave velocity (SWV) for predicting thyroid cancer (TC). The sensitivity and specificity were 79.27% and 71.52%, respectively. Positive predictive value (PPV) was 26.75% and negative predictive value (NPV) was 96.34%. Compared with B-mode US features for predicting malignancy, SWV ≥3.54 m/s has a higher sensitivity, specificity, PPV and NPV. TN stiffness measured by VTIQ-generated shear wave elastography is an independent predictor of TC.

The use of force histograms for affine-invariant relative position description.

Affine invariant descriptors have been widely used for recognition of objects regardless of their position, size, and orientation in space. Examples of color, texture, and shape descriptors abound in the literature. However, many tasks in computer vision require looking not only at single objects or regions in images but also at their spatial relationships. In an earlier work, we showed that the relative position of two objects can be quantitatively described by a histogram of forces. Here, we study how affine transformations affect this descriptor. The position of an object with respect to another changes when the objects are affine transformed. We analyze the link between 1) the applied affinity, 2) the relative position before transformation (described through a force histogram), and 3) the relative position after transformation. We show that any two of these elements allow the third one to be recovered. Moreover, it is possible to determine whether (or how well) two relative positions are actually related through an affine transformation. If they are not, the affinity that best approximates the unknown transformation can be retrieved, and the quality of the approximation assessed.

Sit-to-stand measurement for in-home monitoring using voxel analysis.

We present algorithms to segment the activities of sitting and standing, and identify the regions of sit-to-stand (STS) transitions in a given image sequence. As a means of fall risk assessment, we propose methods to measure STS time using the 3-D modeling of a human body in voxel space as well as ellipse fitting algorithms and image features to capture orientation of the body. The proposed algorithms were tested on ten older adults with ages ranging from 83 to 97. Two techniques in combination yielded the best results, namely the voxel height in conjunction with the ellipse fit. Accurate STS time was computed on various STSs and verified using a marker-based motion capture system. This application can be used as part of a continuous video monitoring system in the homes of older adults and can provide valuable information to help detect fall risk and enable early interventions.