Abstract: A system for controlling a therapeutic device and/or environmental parameters can include one or more body worn sensor devices that detect and report one or more physical, physiological, or biological parameters of a person in an environment. The sensor devices can communicate sensor data indicative of the one or more physical, physiological, or biological parameters of a person to an external hub that processes the data and communicates with the therapeutic device to provide a therapy (e.g., neuromodulation, neurostimulation, or drug delivery) as a function of the sensor data. In some embodiments, the therapeutic device can be implanted in the person. In some embodiments, the therapeutic device can be in contact with the skin of the person. The sensor devices can also communicate to the hub that communicates with one or more devices to change the environment as a function of the sensor data.

Abstract: Methods and apparatus for providing personalized biofeedback therapy to a user experiencing a panic attack are described. The method comprises receiving an indication that the user is experiencing a panic attack, receiving, from a recommendation system, a recommended biofeedback therapy for the user, providing the recommended biofeedback therapy to the user during the panic attack, and transmitting to the recommendation system, information related to the panic attack after the panic attack has subsided, wherein the information related to the panic attack is used to provide an updated recommended biofeedback therapy for the user.

Abstract: A system and method for sensing sleep abnormality in a user is disclosed. The system can include an accelerometer sensor in contact with the skin of the user to measure the deflection of the body during respiration and generate a respiration waveform. A controller receives the respiration waveform from the accelerometer sensor to determine a sleep abnormality measurement as a function of the respiration waveform.

Abstract: A method for calculating the location of the center-of-rotation of a joint with an attached member. The method employs an inertial measurement unit (IMU) having an angular rate gyro and an accelerometer and coupling the inertial measurement unit to the member for detection of movement of the member. The inertial measurement unit outputs data representative of angular velocity and acceleration of the member mounted IMU in response to movement of the joint. The method further comprising analyzing the angular rate and acceleration data to determine the center-of-rotation of the joint.

Abstract: A system for controlling a therapeutic device and/or environmental parameters can include one or more body worn sensor devices that detect and report one or more physical, physiological, or biological parameters of a person in an environment. The sensor devices can communicate sensor data indicative of the one or more physical, physiological, or biological parameters of a person to an external hub that processes the data and communicates with the therapeutic device to provide a therapy (e.g., neuromodulation, neurostimulation, or drug delivery) as a function of the sensor data. In some embodiments, the therapeutic device can be implanted in the person. In some embodiments, the therapeutic device can be in contact with the skin of the person. The sensor devices can also communicate to the hub that communicates with one or more devices to change the environment as a function of the sensor data.

Abstract: A system for development of an algorithm for analysis of sensor data includes one or more wearable sensor devices, a smart device, and a cloud computing platform. The sensors in the wearable sensor device produce sensor data (e.g., physiological data) from a user that can be processed by a software algorithm in the wearable sensor device or by a connected smart device (e.g., a smartphone) via cloud computing, producing an algorithm output. The raw sensor data along with other information, such as the algorithm output and sensor data features can be sent to the cloud computing platform for storage and to enable developers to access the data in order to modify the software algorithms. The wearable sensor device can be configured to send more or less data to the cloud computing platform according to the performance of the software algorithm.

Abstract: A method for calculating the location of the center-of-rotation of a joint with an attached member. The method employs an inertial measurement unit (IMU) having an angular rate gyro and an accelerometer and coupling the inertial measurement unit to the member for detection of movement of the member. The inertial measurement unit outputs data representative of angular velocity and acceleration of the member mounted IMU in response to movement of the joint. The method further comprising analyzing the angular rate and acceleration data to determine the center-of-rotation of the joint.

Abstract: A measurement system having a miniature, wireless inertial measurement unit (IMU) disposed within or on a moving object, such as a ball or other member, to calculate the kinematics of the moving object.

Abstract: Systems and methods are presented that detect and classify mass-like regions exhibiting spiculated and/or dense characteristics with high sensitivity and at acceptable false positive rates. One or more suspicious masses are identified in medical imagery of the breast. In certain embodiments, a quantitative measure of spiculation and quantitative measure of density are computed for each suspicious mass located. At least one classification scheme, developed using true and false positives with similar quantitative measures, is then selected for each suspicious mass according to both quantitative measures. In certain other embodiments, a measure of breast location is computed for each suspicious mass. In one embodiment, the location determines whether a suspicious mass appears inside or outside of the parenchyma region of the breast.

Abstract: A container for storing various yard equipment items is provided. The container includes an open volume for receiving a lawn mower, an open rear end for inserting and removing the lawn mower, a pair of sidewalls, an open bottom, and a top wall including several risers and treads. The risers and treads provide the top wall with a stair step configuration. The stair steps enable the housing to match the contours of the yard equipment contained therein, and additionally provide storage space on the top of the housing for storing a plurality of items. The yard equipment can be inserted into and removed from the container without disturbing the items stored on the steps.

Abstract: A measurement system having a miniature, wireless inertial measurement unit (IMU) disposed within or on a moving object, such as a ball or other member, to calculate the kinematics of the moving object.

Abstract: An apparatus for analyzing movement of equipment. The apparatus includes an inertial measurement unit continuously measuring six rigid body degrees of freedom of the equipment and outputting data representative thereof, wherein the inertial measurement unit defines a planar substrate having a single common plane. The inertial measurement unit further includes at least one angular rate gyro and at least one accelerometer sufficient to measure the six rigid body degrees of freedom and each being mounted on the single common plane. The apparatus further includes a processing unit determining the acceleration of the mass center of the equipment, the angular velocity and the angular acceleration of the equipment through a single derivative operation.

Abstract: Systems, computer-readable media, and methods are presented that identify suspicious anomalies in a colon with higher sensitivity and at a lower false positive rate. A plurality of images of an anatomical colon is acquired. Candidate suspicious anomalies are identified in each image. The candidate suspicious anomalies across images are then compared using registration and matching. Features of candidate suspicious anomalies across images may be jointly evaluated to perform classification.

Abstract: Methods are presented that detect and classify mass-like regions exhibiting spiculated and/or dense characteristics with high sensitivity and at acceptable false positive rates. One or more suspicious masses are identified in medical imagery of the breast. In certain embodiments, a quantitative measure of spiculation and quantitative measure of density are computed for each suspicious mass located. At least one classification scheme, developed using true and false positives with similar quantitative measures, is then selected for each suspicious mass according to both quantitative measures. In certain other embodiments, a measure of breast location is computed for each suspicious mass. In one embodiment, the location determines whether a suspicious mass appears inside or outside of the parenchyma region of the breast.

Abstract: This discloses methods and systems for the processing of medical image data of a colon acquired with an imaging device, such as a computerized tomography (“CT”) scanner and more particularly, to methods and systems for the classification of structures or objects in said medical image data. The disclosed methods and systems analyze image data for objects such as rectal tubes or stools, or for clusters of suspicious regions, and may eliminate such objects from further analysis prior to presenting potential polyps to a user.

Abstract: Systems, computer-readable media, methods, and a medical imaging system are presented that compute and output a density estimate of a breast. The density estimate may be computed using information from at least two digital images, wherein each image represents a view of at least a portion of the breast from a different specific angle. The density estimate may be computed using information from at least one digital breast image and at least one digital opposite breast image, wherein the at least one digital breast image represents a view of at least a portion of the breast from a specific angle and wherein the at least one digital opposite breast image represents a view of at least a portion of the opposite breast. The density estimate may be computed using computed parenchyma information, the parenchyma information being computed using texture information and density information derived from at least one digital image of at least a portion of the breast.

Abstract: Systems, computer-readable media, and methods are presented that identify suspicious anomalies in a colon with higher sensitivity and at a lower false positive rate. A plurality of images of an anatomical colon is acquired. Candidate suspicious anomalies are identified in each image. The candidate suspicious anomalies across images are then compared using registration and matching. Features of candidate suspicious anomalies across images may be jointly evaluated to perform classification.

Abstract: The application discloses computer-based apparatus and methods for analysis of images of the colon to assist in the detection of colonic polyps. The apparatus and methods include the detection, classification and display of candidate colonic folds.

Abstract: The application discloses computer-based apparatus and methods for analysis of images of the colon to assist in the detection of colonic polyps. The apparatus and methods include the classification of anomalies which are suspected colonic polyps by morphological types, and the use of information about the morphological type to assist in the determination of whether the anomaly is a polyp.

Abstract: Methods, a system, and a computer readable medium are presented that detect and classify mass-like regions exhibiting spiculated and/or dense characteristics with high sensitivity and at acceptable false positive rates. One or more suspicious masses are identified in medical imagery of the breast. In accordance with certain embodiments, for each suspicious mass located, a quantitative measure of spiculation and quantitative measure of density are computed. At least one classification scheme is then selected for each suspicious mass according to both quantitative measures. Each classification scheme is developed using true positives and false positives with similar quantitative measures. In accordance with certain other embodiments, for each suspicious mass located, a measure of breast location is computed. At least one classification scheme is then selected for each suspicious mass according to the measure of breast location.