The University of Tennessee Research Foundation

Other

US Government As Represented by the Secretary of the Army

Navigated Technologies, LLC

John Douglas Birdwell

Tse-Wei Wang

Dale V Stansberry

David J Icove

Roger Horn

Puneet Yadav

Mark S Rader

Jared B Pendleton

Ranajit Chakraborty

John R Flaherty

Ning Xue

Karl Arthur Sillay

Xue Ning

Mark Edward Dean

Catherine Dorothy Schuman

Mark Hebron Myers

Carl G Sapp

Margaret Grace Drouhard

Kenneth H Gilbert

Dale V Stransberry

One embodiment of an exemplary ambulatory seizure monitoring method calculates a phase lock value synchrony level of a neurological signal of an individual; detects an onset of a seizure event for the individual by comparing the phase lock value synchrony level with a patient threshold for the individual; and transmits a notification to a remote communication device indicating the onset of the seizure event for the individual.

Ambulatory seizure monitoring system and method

A method and apparatus for constructing one of a neuroscience-inspired artificial neural network and a neural network array comprises one of a neuroscience-inspired dynamic architecture, a dynamic artificial neural network array and a neural network array of electrodes associated with neural tissue such as a brain, the method and apparatus having a special purpose display processor. The special purpose display processor outputs a display over a period of selected reference time units to demonstrate a neural pathway from, for example, one or a plurality of input neurons through intermediate destination neurons to an output neuron in three-dimensional space. The displayed neural network may comprise neurons and synapses in different colors and may be utilized, for example, to show the behavior of a neural network for classifying hand-written digits between values of 0 and 9 or recognizing vertical/horizontal lines in a grid image of lines.

Method and apparatus for constructing a neuroscience-inspired artificial neural network with visualization of neural pathways

A suite of components comprising an objective measurement medical data collection device and a cohort database may standardize, simplify, and objectify clinical outcomes tracking, culminating in population health measurements within the restorative neurosciences such as Parkinson disease individuals diagnosed with a disease. A data collection device may comprise one or more of a gyroscope, an accelerometer, a locator, a camera and a magnetometer for collecting, for example, data related to tremors experienced by the individuals diagnosed with disease and receive instruction data responsive to evaluation of the collected data in relation to the cohort database. A related method collects objective measurements during phases of treatment such as preoperative symptomatology, probabilistic atlas linked targeting for neuromodulation, accountancy for gravitational effects of brain shift during surgery, measurements of movement and quality of life during supervised treatment and ongoing community and self-directed treatment and provides feedback to implants, intelligent devices and users thereof.

Patient permission-based mobile health-linked information collection and exchange systems and methods

The present invention provides a method of predicting whether an unknown biological specimen originates from a member of a particular family. The method compares DNA profiles from at least one unknown biological specimen to DNA profiles of more than one family member, which significantly increases the methods' predictive ability. In particular, the invention describes a method of comparing test DNA profiles from unknown biological specimens to a family pedigree comprising target DNA profiles obtained from biological specimens of family members. In one embodiment, a modified Elston Stewart algorithm is used to determine a probability that a genetic relationship exists between at least one unknown biological specimen and the family pedigree.

Methods of associating an unknown biological specimen with a family

Three methods of predicting whether an unknown biological specimen of a missing person originates from a member of a particular family comprise an initial automated decision support (ADS) algorithm for determining a list of relatives of the missing person for DNA typing and which typing technologies of available technologies to use for a listed relative. The ADS algorithm may be implemented on computer apparatus including a processor and an associated memory. The ADS method comprises determining a set of relatives of available family member relatives for DNA typing via a processor from a stored list of family member relatives according to one of a rule base, a table of hierarchically stored relatives developed based on discriminatory power or by calculating the discriminatory power for available family relatives to type. The ADS method may further comprise comparing at least one set of DNA typing data for the unknown biological specimen to DNA typing data from biological specimens from the determined set of relatives; calculating by the processor a likelihood function that the person is related to the family; and outputting a decision whether or not the person is related to the family.

Automated decision support for associating an unknown biological specimen with a family

Analysis of DNA is critical to many applications including identifying perpetrators of crimes based on genetic evidence left at crime scenes. An initial step to analyzing DNA data is detection, identification, and quantization of allele peaks in the DNA data. The invention provides a method and apparatus for accurately and expeditiously performing this initial step by sequentially checking unfitted peaks against various models including a default model, a hybrid peak model, a dual fit model and, in special situations, a narrow fit function and a saturated fit function.

Method and apparatus for allele peak fitting and attribute extraction from DNA sample data

Method and apparatus for determining a metric for use in predicting properties of an unknown specimen belonging to a group of reference specimen electrical devices comprises application of a network analyzer for collecting impedance spectra for the reference specimens and determining centroids and thresholds for the group of reference specimens so that an unknown specimen may be confidently classified as a member of the reference group using the metric. If a trait is stored with the reference group of electrical device specimens, then, the trait may be predictably associated with the unknown specimen along with any traits identified with the unknown specimen associated with the reference group.

Method and apparatus for classifying known specimens and media using spectral properties and identifying unknown specimens and media

The present invention provides at least three methods of predicting whether an unknown biological specimen originates from a member of a particular family. These methods compare DNA profiles from unknown biological specimens to DNA profiles of more than one family member, which significantly increases the methods' identification ability. In particular, the invention describes combining at least a ranked first family member list and a ranked second family member list to create a combined ranked list and identifying the unknown biological specimen as one contained among a list of specimens having the highest combined rankings representing the candidates that are most likely related to the family. A second method encompasses comparing test DNA profiles from unknown biological specimens to a family pedigree comprising target DNA profiles obtained from multiple biological specimens of family members. This method also embodies using a modified Elston Stewart algorithm to determine a pedigree likelihood ratio to rank and identify the test profile of the unknown biological specimen most likely to be the missing person sought after by the corresponding family represented by the family pedigree. A third method encompasses construction of a database or directed graph of discovered or known relationships between biological specimens and comparison to a graph representing a family pedigree to identify portions of the database or directed graph that correspond to portions of the family pedigree, in order to rank or identify one or more unknown biological specimens as most likely related to one or more family pedigrees.

Least Square Deconvolution (LSD) uses quantitative allele peak data, for example, allele peak area, allele peak height and optical density, derived/obtained from a sample containing the DNA of more than one contributor to resolve the best-fit genotype profile of each contributor. The resolution is based on finding the least square fit of the mass ratio coefficients at each locus to come closest to the quantitative allele peak data. Consistent top-ranked mass ratio combinations from each locus can be pooled to form at least one composite DNA profile at a subset of the available loci. The top-ranked DNA profiles can be used to check against the profile of a suspect or be used to search for a matching profile in a DNA database.

Least-square deconvolution (LSD): a method to resolve DNA mixtures

A tree-structured index to multidimensional data is created using naturally occurring patterns and clusters within the data which permit efficient search and retrieval strategies in a database of DNA profiles. A search engine utilizes hierarchical decomposition of the database by identifying clusters of similar DNA profiles and maps to parallel computer architecture, allowing scale up past to previously feasible limits. Key benefits of the new method are logarithmic scale up and parallelization. These benefits are achieved by identification and utilization of naturally occurring patterns and clusters within stored data. The patterns and clusters enable the stored data to be partitioned into subsets of roughly equal size. The method can be applied recursively, resulting in a database tree that is balanced, meaning that all paths or branches through the tree have roughly the same length. The method achieves high performance by exploiting the natural structure of the data in a manner that maintains balanced trees. Implementation of the method maps naturally to parallel computer architectures, allowing scale up to very large databases.

Parallel data processing architecture

A tree-structured index to multidimensional data is created using naturally occurring patterns and clusters within the data which permit efficient search and retrieval strategies in a database of DNA profiles. A search engine utilizes hierarchical decomposition of the database by identifying clusters of similar DNA profiles and maps to parallel computer architecture, allowing scale up past previously feasible limits. Key benefits of the new method are logarithmic scale up and parallelization. These benefits are achieved by identification and utilization of naturally occurring patterns and clusters within stored data. The patterns and clusters enable the stored data to be partitioned into subsets of roughly equal size. The method can be applied recursively, resulting in a database tree that is balanced, meaning that all paths or branches through the tree have roughly the same length. The method achieves high performance by exploiting the natural structure of the data in a manner that maintains balanced trees. Implementation of the method maps naturally to parallel computer architectures, allowing scale up to very large databases.

Parallel data processing system

An item is organized and presented by displaying a table, wherein the table displays a plurality of data comprising DNA profile analysis results including an observation characterizing the at least one item, and wherein an analysis result is based on a decision made by an expert system according to a rule base. An observation comprises one of concordance, a locus having a concordance error, an off-ladder peak, a peak height imbalance and a peak falling in an overlap region between loci. The rule base comprises rules related to background noise, spike, broad peak, duplicate allele, bleed-through peak, pull-up peak, stutter peak, &#x2212;A peak and global filter rules.

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Oak Ridge, TN, United States of America

John Douglas Birdwell