Abstract: Triggering information that defines conditions for presenting a virtual clinical exam may be downloaded to a user device. A server computer may receive sensor data and use the sensor data to evaluate the conditions. When certain conditions are fulfilled, the server computer provides the conditions to the user device for use by the user device in triggering presentation of the virtual clinical exam at the user device.

Abstract: Triggering information that defines conditions for presenting a virtual clinical exam may be downloaded to a user device. The user device may collect sensor data and use the sensor data to evaluate the conditions. When certain conditions are fulfilled, the user device may present the virtual clinical exam at the user device.

Abstract: A user device may machine segment sensor measurements by determining a context window. The context window may include a beginning and an end. The context window may be used to define the time period in which measurements of the sensor measurements are to be segmented.

Abstract: A user device may automatically identify activities that correspond to virtual motor exam tasks and clinical tasks and auto annotate sensor data based on previous annotations and machine-learning models trained using the same. The annotations may describe context, performance, subjective, and objective information related to the performance of the activity for tracking disease or treatment progression.

Abstract: Triggering information that defines conditions for presenting a virtual clinical exam may be downloaded to a user device. The user device may collect sensor data and use the sensor data to evaluate the conditions. When certain conditions are fulfilled, the user device may present the virtual clinical exam at the user device.

Abstract: An approach is provided for automated analysis and classification of quality characteristics associated with captured imagery that may be used in an application such as a map application. The approach includes determining digital data associated with a region of interest in an image. The approach also comprises processing and/or facilitating a processing of the digital data to determine one or more quality attributes associated with the region of interest. The approach further comprises causing, at least in part, a comparison of the one or more quality attributes to one or more criteria. The approach also comprises causing, at least in part, a generation of one or more classifications for the image based, at least in part, on the comparison.

Abstract: An approach is provided for automated classification of an image based on the fogging attributes associated with the image. The approach involves processing and/or facilitating a processing of image data associated with at least one image to cause, at least in part, an extraction of one or more fogging attributes from the image data. The approach also involves causing, at least in part, a mapping of the one or more fogging attributes to one or more features of at least one classifier, wherein the at least one classifier is trained based, at least in part, on a co-registration of the one or more features to one or more records of previously made image judgements. The approach further involves causing, at least in part, a classification of the at least one image as either in a fogging-afflicted state or a non-fogging-afflicted state based, at least in part, on the at least one classifier.

Abstract: An approach is provided for automated classification of an image based on the fogging attributes associated with the image. The approach involves processing and/or facilitating a processing of image data associated with at least one image to cause, at least in part, an extraction of one or more fogging attributes from the image data. The approach also involves causing, at least in part, a mapping of the one or more fogging attributes to one or more features of at least one classifier, wherein the at least one classifier is trained based, at least in part, on a co-registration of the one or more features to one or more records of previously made image judgements. The approach further involves causing, at least in part, a classification of the at least one image as either in a fogging-afflicted state or a non-fogging-afflicted state based, at least in part, on the at least one classifier.

Abstract: An approach is provided for automated analysis and classification of quality characteristics associated with captured imagery that may be used in an application such as a map application. The approach includes determining digital data associated with a region of interest in an image. The approach also comprises processing and/or facilitating a processing of the digital data to determine one or more quality attributes associated with the region of interest. The approach further comprises causing, at least in part, a comparison of the one or more quality attributes to one or more criteria. The approach also comprises causing, at least in part, a generation of one or more classifications for the image based, at least in part, on the comparison.

Abstract: Techniques for enhancing an individual's knowledge of civics topics in an interactive manner are described herein. In particular implementations, a user may interact with a computing device, such as a smart phone, tablet computer, or laptop computer, to take a test related to civics topics and to view information about others that have taken the test. For example, a user may view an average test score of others of a particular geographical region or group, a test score of an elected representative, a test score of a friend, and so on.

Abstract: A waste removal vehicle including a loader, an elevator having a chain-driven conveyor mounted on the loader, and a pair of moveable wing arms including a flexible lower portion for engaging the surface of the location floor and forwardly mounted rollers for engaging the curb of an alley or aisle that are positioned on either side of the elevator for directing animal excrement and associated waste from a concentrated feeding location, such as a barn or stable. One end of the elevator is positioned in front of the loader to float on rollers above the floor and accept waste materials, while the opposing end communicates with the upper portion of a tank mounted on the rear of the loader. As the vehicle is driven along, the wing arms collect and direct waste to the elevator, which transports the waste to a holding tank on the back of the vehicle.