Abstract: Systems, methods, and computer program products identify arrhythmias experienced by a patient. A system includes an external wearable heart monitoring device for continuous and long-term monitoring of a patient that includes electrocardiogram (ECG) electrodes and circuitry to sense surface ECG activity and provide ECG channel(s) producing ECG signal(s), a non-transitory computer-readable medium including an arrhythmia classifier including neural network(s), and processor(s). The neural network(s) are trained based on a historical collection of ECG signal portions with annotation data including at least one annotation for each ECG signal portion and based on weight data including a weight for each annotation based on the annotator thereof. The processor(s) receive the ECG signal(s), monitor the ECG signal(s) to detect at least one arrhythmia event based on the arrhythmia classifier, and transmit at least one communication based on the arrhythmia event(s) to a remote computer system.

Abstract: An ECG processing system for identifying noisy ECG data segments is provided. The ECG processing system includes a network interface and a processor. The network interface is configured to receive a first collection of ECG data segments from wearable medical devices associated with a plurality of patients, each wearable medical device of the wearable medical devices being configured to be continuously worn by a patient for an extended period of time. The processor is configured to produce a second collection of ECG data segments from the first collection of ECG data segments that excludes noisy ECG data segments.

Abstract: Data samples derived from raw physiological data captured by sensors of a wearable medical device monitoring a patient's heart, such as a first ECG channel data sample, a second ECG channel data sample, and/or a cardio-vibrational data sample, are applied to a multi-tier machine learning engine to determine a cardiac condition measure traditionally calculated based upon information typically derived in a laboratory or clinical setting. A first tier of the multi-tier machine learning engine may analyze the physiological data sample(s) using first machine learning classifier(s) to obtain a first result. The first result may then be applied to second machine learning classifier(s) of a second tier of the machine learning engine, along with physiological metrics and/or patient clinical information, to determine the cardiac condition measure.

Abstract: A wearable medical device is provided. The device includes electrodes to receive electrical signals from a patient, monitor for a cardiac arrhythmia, and provide a therapeutic shock to the patient in response to detecting the arrhythmia. The device includes a user interface to receive patient input indicating initiation or termination of a high-noise activity. The device can include accelerometers to generate motion signals. The device includes a processor to monitor for initiation or termination of the high-noise activity based on a noise level in the electrical signals, the motion signals, and the patient input. The processor can cause, in response to the initiation of the high-noise activity, an arrhythmia detection process to execute in an activity-induced noise (AIN) robust mode, and cause, in response to the termination of the high-noise activity, the arrhythmia detection process to execute in an AIN sensitive mode.

Abstract: An ECG processing system for identifying noisy ECG data segments is provided. The ECG processing system includes a network interface and a processor. The network interface is configured to receive a first collection of ECG data segments from wearable medical devices associated with a plurality of patients, each wearable medical device of the wearable medical devices being configured to be continuously worn by a patient for an extended period of time. The processor is configured to produce a second collection of ECG data segments from the first collection of ECG data segments that excludes noisy ECG data segments.

Abstract: An ECG processing system for identifying noisy ECG data segments is provided. The ECG processing system includes a network interface and a processor. The network interface is configured to receive a first collection of ECG data segments from wearable medical devices associated with a plurality of patients, each wearable medical device of the wearable medical devices being configured to be continuously worn by a patient for an extended period of time. The processor is configured to produce a second collection of ECG data segments from the first collection of ECG data segments that excludes noisy ECG data segments.

Abstract: A system for providing electrocardiogram (ECG) information to a healthcare provider (HCP) is provided. The system includes a network interface configured to receive drug prescription information from a computing device associated with the HCP and ECG data from a medical device associated with a patient. The system also includes a memory configured to store the drug prescription information and the ECG data. The system can further a processor configured to select a period of time over which to review the received drug prescription information and the received ECG data, retrieve the received ECG data for the selected period of time, derive one or more ECG metrics including at least one heart rate parameter, and generate a graphical representation indicating a trend in the one or more ECG metrics and a relationship between the one or more ECG metrics and the drug prescription information.

Abstract: An ECG processing system for identifying noisy ECG data segments is provided. The ECG processing system includes a network interface and a processor. The network interface is configured to receive a first collection of ECG data segments from wearable medical devices associated with a plurality of patients, each wearable medical device of the wearable medical devices being configured to be continuously worn by a patient for an extended period of time. The processor is configured to produce a second collection of ECG data segments from the first collection of ECG data segments that excludes noisy ECG data segments.

Abstract: A monster detection assembly includes a detection unit that may be coupled to a support surface, such as a wall or a ceiling in a child's bedroom. The detection unit selectively emits light outwardly therefrom to simulate a detection sequence for monsters and other fictional characters in the child's bedroom. A remote unit is provided and the remote unit is manipulated by a child when the child is in bed. The remote unit is in wireless communication with the detection unit. The detection unit generates the detection sequence when the remote unit is manipulated. Additionally, the remote unit selectively emits audible sounds when the detection unit generates the detection sequence. In this way the remote unit confirms to the child that no monsters were detected thereby soothing the child.

Abstract: A method and system for setting image analysis parameters to control image analysis operations. The method and system include collecting set of digital training images including a set of states for the set of digital training images. An objective function is defined to determine a relative quality of plural different parameter sets used for digital image analysis. Values for the plural different parameter sets that maximize (or minimize) the objective function are determined. The method and system increases a usability of high content screening technologies by reducing a required level of expertise required to configure digital image processing.

Abstract: A method and system for setting image analysis parameters to control image analysis operations. The method and system include collecting set of digital training images including a set of states for the set of digital training images. An objective function is defined to determine a relative quality of plural different parameter sets used for digital image analysis. Values for the plural different parameter sets that maximize (or minimize) the objective function are determined. The method and system increases a usability of high content screening technologies by reducing a required level of expertise required to configure digital image processing.

Abstract: A method and system for setting image analysis parameters to control image analysis operations. The method and system include collecting set of digital training images including a set of states for the set of digital training images. An objective function is defined to determine a relative quality of plural different parameter sets used for digital image analysis. Values for the plural different parameter sets that maximize (or minimize) the objective function are determined. The method and system increases a usability of high content screening technologies by reducing a required level of expertise required to configure digital image processing.

Abstract: A method and system for setting image analysis parameters to control image analysis operations. The method and system include collecting set of digital training images including a set of states for the set of digital training images. An objective function is defined to determine a relative quality of plural different parameter sets used for digital image analysis. Values for the plural different parameter sets that maximize (or minimize) the objective function are determined. The method and system increases a usability of high content screening technologies by reducing a required level of expertise required to configure digital image processing.

Abstract: A method and system for setting image analysis parameters to control image analysis operations. The method and system include collecting set of digital training images including a set of states for the set of digital training images. An objective function is defined to determine a relative quality of plural different parameter sets used for digital image analysis. Values for the plural different parameter sets that maximize (or minimize) the objective function are determined. The method and system increases a usability of high content screening technologies by reducing a required level of expertise required to configure digital image processing.

Abstract: A method and system for setting image analysis parameters to control image analysis operations. The method and system include collecting set of digital training images including a set of states for the set of digital training images. An objective function is defined to determine a relative quality of plural different parameter sets used for digital image analysis. Values for the plural different parameter sets that maximize (or minimize) the objective function are determined. The method and system increases a usability of high content screening technologies by reducing a required level of expertise required to configure digital image processing.

Abstract: The invention provides a method for a method for determining a best initial focal position estimate for a current sample location on a substrate comprising multiple sample locations, comprising determining the best initial focal position estimate by using a result from one or more techniques selected from the group consisting of linear regression analysis of focal positions determined for at least two other sample locations on the substrate and quadratic regression analysis of focal positions determined for at least three other sample locations on the substrate.

Abstract: The invention provides a method for a method for determining a best initial focal position estimate for a current sample location on a substrate comprising multiple sample locations, comprising determining the best initial focal position estimate by using a result from one or more techniques selected from the group consisting of linear regression analysis of focal positions determined for at least two other sample locations on the substrate and quadratic regression analysis of focal positions determined for at least three other sample locations on the substrate.

Abstract: The invention is comprised of a method and apparatus for inspecting substrates and hat sink hat assemblies to determine whether the chips on the substrate and pistons on the heatsink hat assembly are matched. The inspection is carried out by separately illuminating both the substrate and the heatsink hat assembly in such a way that a bilevel image of each assembly is created. Each assembly has an associated image-acquisition device, such as a television or video camera which captures the bilevel image. These images are then converted to an array of image points. The points of the image of the substrate assembly are compared with a preset pattern to determine whether a chip is missing. A similar comparison is done with the points of the image of the heatsink hat assembly to determine whether any piston is missing. A deviation from the expected pattern will be communicated to an operator who will take corrective action.