Abstract: A system and related method for tracking a moving subject via a ground-based or airborne peripheral device includes plugging an intelligent camera device to the unmanned vehicle, establishing a peripheral link by which the intelligent camera device can assume control of the unmanned vehicle's control systems. Based on analysis of images captured by the intelligent camera device, in addition to position data associated with the unmanned vehicle or with the subject, the intelligent camera device may autonomously maneuver the unmanned vehicle to track or follow the subject while maintaining the moving subject in a consistent framing orientation.

Abstract: The present invention relates to a computerized system for and method of providing precision healthcare services such as consultation, education, assessment, diagnosis, intervention, or treatment at a distance via encrypted real-time image and audio presence where the healthcare professional's assessment, diagnosis, and intervention activities are informed by patient feedback, smart objects, and artificial intelligence and patient outcomes are optimized through recursive system feedback. The present invention is unlimited with regard to the type of patient entity or healthcare professional entity.

Abstract: The invention pertains to the fields of healthcare services and machine learning. More particularly, the invention pertains to a computer-implemented system for and method of gathering patient attitudes, values, opinions, traits, indicators of health, and symptoms of distress via a user interface that includes a moveable element with high granularity that presents a series of dichotomous choices allowing a patient or other person to move the element across the range of available values. The disclosure also describes a method of transforming legacy psychometric items into a form that modifies the kind of data produced through their usage. This continuous, high-granularity, data generated by the patient interaction can be used to generate training and test sets in machine learning and to facilitate the AI-optimized assessment, diagnosis, and treatment of mental and emotional health and distress at a distance.

Abstract: The present disclosure relates to a method for assessing how a particular patient's responses may vary from those that are typically given on an item or instrument that relies on high granularity, dichotomous, responses. This method allows for the quantifiable description of patterns of possible overreporting, underreporting, “yeasaying,” “naysaying,” favoring one half of a representative continuum in a manner unrelated to item content, attempting to portray oneself in an overly favorable light, or attempting to portray oneself in an overly negative light. This method allows for validity checks without recourse to generating additional, specific, validity check items possibly modifying the times required to construct and train various machine learning (ML) systems including artificial neural networks (ANNs).

Abstract: An unmanned aerial vehicle (UAV) may select a subject to track or follow and capture images including the subject. A visual recognition system of the UAV may generate a profile of reference images portraying the subject breaking the reference images down into pixel sets corresponding to the subject and his/her components and distinguishing characteristics (body parts, clothing, facial features, accessories). The visual recognition system may break the incoming stream of incoming images into pixel sets, analyzing the pixel sets to distinguish the subject from his/her surroundings (i.e., in a crowd) and determine movement of the subject and the current orientation of the UAV to the subject. The UAV may then change its heading, velocity, or position based on any difference between the current orientation and the desired or predetermined orientation between the UAV and the subject.

Abstract: An action camera system for an unmanned aerial vehicle (UAV) selects a target based on a reference image captured by an onboard camera. Image processing determines a desired orientation of the target to the UAV, by which the UAV can track the target and provide streaming video images from the desired orientation. Image processing establishes a visual lock on the target and controls the UAV to maintain the desired orientation while capturing streaming images. Additional position data provided by sensors aboard a smartphone carried by the target enhances the tracking ability of the action camera system and enables predictive analysis of the target's future position. The action camera system may additionally provide preselected modes of operation that control UAV movement and image capture depending on the user's desired objectives.

Abstract: The present invention relates to a computerized system for and methods of securely providing precision healthcare services related to the AI-optimized prescribing and monitoring of behavioral health homework at a distance. The system is continually learning in a recursive manner such that the output of one set of patient experiences are added to the AI system to further refine future patient recommendations with regard to prescribed homework assignments. The present invention is unlimited with regard to the type of patient entity or healthcare professional entity.

Abstract: The present invention relates to a computerized system for and method of providing precision healthcare services such as consultation, education, assessment, diagnosis, intervention, or treatment at a distance via encrypted real-time image and audio presence where the healthcare professional's assessment, diagnosis, and intervention activities are informed by patient feedback, smart objects, and artificial intelligence and patient outcomes are optimized through recursive system feedback. The present invention is unlimited with regard to the type of patient entity or healthcare professional entity.

Abstract: A system and method for power management aboard an unmanned aerial vehicle (UAV) configured to follow a subject based on images captured by an onboard camera includes a power monitor that determines if available power from the UAV's onboard batteries has dropped below predetermined thresholds. If a low power level is detected, the power management system may divert power from non-essential systems to the attitude control system to keeping the UAV aloft. If a critical power level is detected, the power management system may shut down other UAV subsystems so that the attitude control system can safely land the UAV. The power management system may send an alert to a smartphone or other device carried by the subject. Position sensors of the subject's device may be used to interpolate the position of the UAV based on the subject's own position for recovery of the UAV.

Abstract: Systems and methods for simultaneously capturing live audio and video feeds and reducing motor/rotor noise associated with the video feed for a multirotor unmanned aerial vehicle (UAV). Noise reduction occurs in real time or near real time as one or more frequencies associated with a motor, rotor, or attitude of the UAV are recognized, subtracted and/or dithered from the audio feed, resulting in one or more correction signals. The one or more correction signals may be dynamically summed in order to generate a corrected audio feed for transmission.

Abstract: An unmanned aerial vehicle (UAV) may select a subject to track or follow and capture images including the subject. A visual recognition system of the UAV may generate a profile of reference images portraying the subject breaking the reference images down into pixel sets corresponding to the subject and his/her components and distinguishing characteristics (body parts, clothing, facial features, accessories). The visual recognition system may break the incoming stream of incoming images into pixel sets, analyzing the pixel sets to distinguish the subject from his/her surroundings (i.e., in a crowd) and determine movement of the subject and the current orientation of the UAV to the subject. The UAV may then change its heading, velocity, or position based on any difference between the current orientation and the desired or predetermined orientation between the UAV and the subject.