General Electric Company

Yang Zhao

Huan Tan

Mauricio Castillo-Effen

Ghulam Ali Baloch

Douglas Roy Forman

Jeffrey Michael Ashe

Shiraj Sen

Yakov Polishchuk

Steven Robert Gray

Charles Burton Theurer

Christopher Donald Johnson

Christopher Michael Puleo

Andrew Day

Brandon Stephen Good

Yi Xu

Arpit Jain

Ting Yu

Lynn Ann DeRose

David Toledano

David Andrew Shoudy

Steven William Wik

Judith Ann Guzzo

John Brandon Laflen

S M Shajedul Hasan

Ying Fan

Viktor Holovashchenko

Kirk Dennis Wallace

Sm Shajedul Hasan

Jeffrey Richardson Terry

Ching-Ling Huang

Roberto Silveira Silva Filho

Raju Venkataramana

Alex Tepper

Patrick Jay Biel

Lynn Ann Derose

Embodiments of the present disclosure relate to techniques for facilitating personalized neuromodulation treatment protocols. In one embodiment, a predetermined treatment position of an energy application device is used to guide future treatments for the patient. In one embodiment, a position of the energy application device relative to the predetermined treatment position is determined. In one embodiment, a total dose of ultrasound energy applied to the region of interest is determined.

Neuromodulation energy application techniques

Certain examples provide systems and methods to monitor and control hospital operational systems based on occupancy data and medical orders. An example healthcare workflow management and reasoning system includes a workflow engine including a first particularly programmed processor to monitor one or more medical orders from one or more hospital information systems to identify a condition indicating that a first patient in a first room is ready for a clinical activity such as discharge. The example healthcare workflow management and reasoning system includes a sensing component including a second processor to gather occupancy data regarding the first patient in the first room and transmit the occupancy data to the workflow engine. The example workflow engine controls one or more hospital operational systems to trigger cleaning of the first room, lighting settings for the first room, and transportation of a second patient to the first room based on occupancy data from the sensing component.

Methods and systems to sense situational awareness with a dual doppler and control for optimized operations

The example embodiments are directed to a system and method for controlling and commanding an unmanned robot using natural interfaces. In one example, the method includes receiving a plurality of sensory inputs from a user via one or more natural interfaces, wherein each sensory input is associated with an intention of the user for an unmanned robot to perform a task, processing each of the plurality of sensory inputs using a plurality of channels of processing to produce a first recognition result and a second recognition result, combining the first recognition result and the second recognition result to determine a recognized command, and generating a task plan assignable to the unmanned robot based on the recognized command and predefined control primitives.

Controlling and commanding an unmanned robot using natural interfaces

System and methods may evaluate and/or improve target aiming accuracy for a sensor of an Unmanned Aerial Vehicle ('UAV'). According to some embodiments, a position and orientation measuring unit may measure a position and orientation associated with the sensor. A pose estimation platform may execute a first order calculation using the measured position and orientation as the actual position and orientation to create a first order model. A geometry evaluation platform may receive planned sensor position and orientation from a targeting goal data store and calculate a standard deviation for a target aiming error utilizing: (i) location and geometry information associated with the industrial asset, (ii) a known relationship between the sensor and a center-of-gravity of the UAV, (iii) the first order model as a transfer function, and (iv) an assumption that the position and orientation of the sensor have Gaussian-distributed noises with zero mean and a pre-determined standard deviation.

Systems and methods associated with unmanned aerial vehicle targeting accuracy

Provided are systems and methods for monitoring an asset via an autonomous model-driven inspection. In an example, the method may include storing an inspection plan including a virtually created three-dimensional (3D) model of a travel path with respect to a virtual asset that is created in virtual space, converting the virtually created 3D model of the travel path about the virtual asset into a physical travel path about a physical asset corresponding to the virtual asset, autonomously controlling vertical and lateral movement of the unmanned robot in three dimensions with respect to the physical asset based on the physical travel path and capturing data at one or more regions of interest, and capturing data at one or more regions of interest, and storing information concerning the captured data about the asset.

Three-dimensional robotic inspection system

The present approach relates to navigation (e.g., route planning and movement) of robots in an indoor environment shared with humans. The present approach includes detecting human activity over time, including but not limited to human motion; modeling human activities using the historical human activity, and using the modeled human activity to plan robotic motion or movement.

System and methods for robotic autonomous motion planning and navigation

Provided are systems and methods for autonomous robotic localization. In one example, the method includes receiving ranging measurements from a plurality of fixed anchor nodes that each have a fixed position and height with respect to the asset, receiving another ranging measurement from an aerial anchor node attached to an unmanned robot having a dynamically adjustable position and height different than the fixed position and height of each of the plurality of anchor nodes, and determining a location of the autonomous robot with respect to the asset based on the ranging measurements received from the fixed anchor nodes and the aerial anchor node, and autonomously moving the autonomous robot about the asset based on the determined location.

Self-localized mobile sensor network for autonomous robotic inspection

A metrological interface device includes a printed circuit board ('PCB') including at least one metrological sensor communication interface and at least one first wireless communication interface. The metrological interface device is in communication with a metrological sensing device via the metrological sensor communication interface. Each metrological sensing device is coupled to a physical asset. Each metrological interface device is configured to receive the metrological data from the metrological sensing device. The metrological interface device is configured to receive metrological data from the metrological sensing device via the metrological sensor communication interface. Metrological data represents physical measurement data associated with the physical asset. Each metrological interface device is configured to advertise connection availability to a plurality of mobile computing devices, and also configured to receive a connection request from a connecting mobile computing device, and is additionally configured to create an active connection with the connecting mobile computing device.

Methods and systems for a universal wireless platform for asset monitoring

A system and method include a plurality of sensors proximate a subject, wherein each sensor includes a plurality of antennas, and wherein each sensor operates on a plurality of frequency channels. The method includes receiving, at a respiration module, a signal associated with each antenna for each of the plurality of frequency channels; and calculating a respiration rate of the subject based on the received signal associated with each antenna for each of the plurality of frequency channels. Numerous other aspects are provided.

Method and system for wireless respiration rate monitoring using space and frequency diversities

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Niskayuna, NY, United States of America

Yang Zhao