Abstract: This invention relates to a weighbridge (10) having a deck (20) and a bridging portion (50). The deck has first (22) and second ends (24) the bridging portion (50) has a first end (50a) attached to an end (22) of the deck (20) and a free end at second end (50b). The bridging portion (50) is configured to provide a bridge between the end (22) of the deck (22) and a static substrate, in use.

Abstract: A neuromodulation targeting system includes a GUI that facilitates selection of one or more neuromodulation target regions. The GUI provides an interactive display representing anatomy of a patient with user-selectable portions corresponding to a plurality of predefined anatomical regions associated with distinct localized clinical effects of neuromodulation. The system further includes a targeting selector engine that is responsive to user selection of a first portion of the interactive display by configuring delivery of neuromodulation therapy to a first target region to produce a first localized clinical effect in the patient at a location corresponding to the first portion of the display, upon administration of the neuromodulation therapy to the patient.

Abstract: Systems and techniques are disclosed to adapt neurostimulation programming in closed-loop adjustment of an implantable neurostimulation device, based on evaluation and weighting of patient data that excludes or reduces effects of interfering events. In an example, adapting a neurostimulation programming model includes: obtaining patient data observed during a prior time period; identifying events experienced by the patient during the prior time period (e.g., confounding events, intervention events) that cause variance in measurements of patient data; determining weighted data by weighting patient data observed during the one or more events, as the weighting of the patient data reduces effects of the patient data during the one or more events on a modification of the programming model; and modifying (e.g., re-training, reinforcing, or adapting) the programming model based on the weighted data.

Abstract: Various embodiments of the present subject matter use health-related information to improve the monitoring and treatment provided to remotely managed patient populations by generating patient states to simplify the triaging of patient conditions. In an example, the system can receive from a user via a user interface, criteria related to one or more goals to accomplish while receiving therapy to treat a condition. The system can translate, by at least one hardware processor, the criteria related to the one or more goals to a state-based classification defining a plurality of patient states defined by a plurality of parameters and receive a first set of parameter values. The system can further identify a first patient state from among the plurality of patient states using the first set of parameter values and generate an output including the first patient state.

Abstract: Various embodiments of the present subject matter use health-related information to improve the monitoring and treatment provided to remotely managed patient populations by generating patient states to simplify the triaging of patient conditions. In an example, the system can monitor and analyze data, and can include identifying a first patient state from among a plurality of patient states, the plurality of patient states being defined by a state-based goal classification; identifying a second patient state from the plurality of patient states; capturing a change in patient state; and providing a monitoring platform to monitor the change in the patient state. In further examples, adaptive measures can be implemented to account for missing or withheld patient-related data used to generate patient states.

Abstract: Methods and systems for modulating the neuroimmune response while monitoring biomarkers that may directly or indirectly correlate with neuroimmune function. A neuromodulation therapy may be delivered, and a biomarker level determined. Some biomarker levels are determined from bodily fluid collected from the patient, and are compared to a predetermined threshold level. A therapeutic stimulation is delivered to a patient using one or more electrode leads, and/or optical fibers.

Abstract: Systems and methods for generating and implementing customized recommendations as part of closed-loop neurostimulation programming and device configuration approaches are disclosed. In an example, a system is configured to: identify, with a recommendation model (e.g., a closed-loop programming algorithm), a programming setting for use in a neurostimulation device that controls neurostimulation treatment of a patient; communicate, to a patient device (e.g., a patient smartphone), a command to present a recommendation to use the programming setting; and communicate, to the patient device, data values associated with the programming setting, to reconfigure the neurostimulation device according to the programming setting. In various examples, a medical user interface enables a medical user (e.g., clinician) to customize the recommendation, and a patient user interface enables a patient to view and use the recommendation.

Abstract: A system (e.g., computing system) for analyzing user interaction associated with a neurostimulation treatment may include functionality to: receive user interaction data associated with a patient undergoing the neurostimulation treatment, with the user interaction data indicating attributes of one or more user interactions in a software platform (e.g., patient computing device) that collects user feedback relating to the neurostimulation treatment; identify attributes of the user interactions from the user interaction data; generate a task to collect additional user input relating to the neurostimulation treatment, with the task being customized to the patient based on the attributes of the user interactions; and control an interaction workflow to perform the task in the software platform.

Abstract: A system to analyze patient location activity in connection with a neurostimulation treatment may: receive tagged location data associated with a patient undergoing the neurostimulation treatment, including tagged location data provided from a patient computing device that indicates a visit of the patient to one or more locations; identify a location type of the locations, using the tagged location data; determine characteristics of the visit at the location type, using the tagged location data; and control a workflow related to the neurostimulation treatment, based on the characteristics of the visit of the patient at the location type. In further examples, such workflows may include a patient interaction workflow, a caregiver workflow, or a clinician workflow, to generate tasks or provide informational alerts based on the patient location activity. Further examples are provided for closed-loop programming of a neurostimulation device based on the patient location activity.

Abstract: A system to analyze data for neurostimulation programming may include capabilities to collect and analyze relevant input data (training data) for training a neurostimulation programming model. In an example, the system may: determine usage of a particular neurostimulation treatment, for a neurostimulation treatment that is associated with a set of parameters used by a neurostimulation device to deliver neurostimulation to a patient; evaluate patient feedback data (e.g., obtained from the patient) associated with the usage of the neurostimulation treatment; calculate, based on the patient feedback data, an amount of training data required to perform training operations on a programming selection model, with such training data being provided at least in part from the patient feedback data and optionally device data.

Abstract: Systems, devices, and methods for providing customizable interactive healthcare services in relation to neuromodulation treatment are disclosed. A digital health system includes a memory device that stores a database of device operation and treatment (DOT) information of neuromodulation device. The DOT information includes information releasable to a patient and device programming capability authorized to the patient, and can be categorized according to a plurality of pre-determined treatment phases and/or according to a plurality of pre-determined patient skill or engagement levels with the neuromodulation device. A processor determines a treatment phase and a skill or engagement level using patient state information, queries the database to determine personalized DOT information corresponding to the treatment phase and the patient skill or engagement level, and provides the personalized DOT information to the patient.

Abstract: Systems and methods are provided for controlling a netting by an Unmanned Aerial Vehicle (UAV). A mesh netting includes a plurality of nettings arranged as interspersed layers in a mesh form. Each of the plurality of nettings has fire-resistant property. Further, a battery powered UAV is present at an aerial location. The mesh netting is coupled to the UAV such that the UAV maintains the mesh netting afloat and adjusts at a position such that a particular source of flying embers is covered with the mesh netting. Also, a lifting kite coupled to the UAV at one end and attached to the mesh netting at another end is provided. The lifting kite carries and holds the mesh netting aloft when the UAV brings the lifting kite at an aloft position such that a particular source is covered with the mesh netting.

Abstract: Systems, devices, and methods for providing customizable interactive healthcare services in relation to neuromodulation treatment are disclosed. A digital health system includes a memory device that stores a database of device operation and treatment (DOT) information of neuromodulation device. The DOT information includes information releasable to a patient and device programming capability authorized to the patient, and can be categorized according to a plurality of pre-determined treatment phases and/or according to a plurality of pre-determined patient skill or engagement levels with the neuromodulation device. A processor determines a treatment phase and a skill or engagement level using patient state information, queries the database to determine personalized DOT information corresponding to the treatment phase and the patient skill or engagement level, and provides the personalized DOT information to the patient.

Abstract: An example of a system for modulating neuroinflammation at a tissue site in a patient includes a neuromodulation output circuit, a memory, and a control circuit. The neuromodulation output circuit may be configured to deliver the neuromodulation. The memory may be configured to store a neuromodulation parameter set selected to modulate neural activity at the tissue site and a sensed biomarker parameter. The biomarker parameter may include a measure of a biomarker or a measure of a derivative of the biomarker. The biomarker may be indicative of the neuroinflammation at the tissue site. The control circuit may be configured to control the delivery of the neuromodulation using the neuromodulation parameter set and adjust one or more parameters of the neuromodulation parameter set using the biomarker parameter.

Abstract: This document discusses systems, devices, and methods for monitoring and managing patients with chronic pain. A patient monitoring system comprises a sensor circuit to sense a physiological or functional signal indicative of or correlated to patient mobility, an electrostimulator to generate and deliver neuromodulation therapy to the patient, and a controller circuit to generate a mobility metric using the sensed physiological or functional signal. The mobility metric represents respective times spent in different activity intensity levels associated with one or more types of activities during a specific time period. The controller circuit can trend the mobility metric over time and determine a progress toward a personalized mobility goal of the patient, and control the electrostimulator to initiate or adjust the neuromodulation therapy in accordance with the trended mobility metric or the determined progress toward the mobility goal.

Abstract: An example of a system may include electrodes on at least one lead configured to be operationally positioned for use in modulating a volume of neural tissue, where the neural tissue has an activation function. The system may further include a neural modulation generator configured to deliver energy using at least some electrodes to generate a modulation field within the volume of neural tissue. The neural modulation generator may be configured to use a programmed modulation parameter set to generate the modulation field. The programmed modulation parameter set having values selected to control energy delivery using the at least some electrodes to achieve an objective function specific to the activation function of the volume of neural tissue to promote uniformity of a response to the modulation field in the volume of neural tissue along a span of the at least one lead.

Abstract: Systems and techniques are disclosed to process freeform data relating to neurostimulation treatment of a human patient, to determine relevant attributes and information regarding a state of the patient. In an example, a system to process freeform data implements electronic operations to: obtain freeform input that indicates characteristics of a neurostimulation treatment of a human patient; validate the freeform input; identify attributes associated with a state of the human patient, based on words from the validated freeform input; associate the attributes with the validated freeform input; and store data for the validated freeform input and the associated attributes. Specific operations for validating may include excluding or replacing words, and specific operations for identifying attributes may be based on natural language processing. Such processing of the freeform data may be used to identify results of neurostimulation programs, and effect improvements to neurostimulation programming or usage.

Abstract: A neuromodulation customization system includes a field definition user interface, a neuromodulation signaling engine, and a supervisor engine. The field definition user interface is to facilitate entry of a customized electrotherapy field definition, with the field definition user interface including a set of input controls for defining field shape, field intensity, and field steering parameters of the customized electrotherapy field. The neuromodulation signaling engine is to produce commands for neuromodulation output circuitry to control generation of a customized electrotherapy field via a set of electrodes based on the customized electrotherapy field definition. The supervisor engine is to assess compliance of the customized electrotherapy field to be generated with applicable predefined criteria, and to modify generation of the customized electrotherapy field in response to an assessed non-compliance with the criteria.

Abstract: A system may include at least one data collection platform and an event detector configured to detect an event. The at least one data collection platform may be configured for use to collect healthcare-related data at a defined data resolution for transfer to a data receiving system that may include one or more processors, at least one data input for receiving healthcare-related data, and memory for storing instructions for implementation by the one or more processors to collect healthcare-related data via the at least one data input. The at least one data collection platform may be configured to change the data resolution for collecting healthcare-related data in response to the detected event.

Abstract: A method of stimulating nerve tissue, a tissue stimulation system, and an external control device are provided. The method, system, and control device causes an electrical stimulus to be applied to at least one electrode adjacent the nerve tissue of a patient. The applied electrical stimulus comprises a plurality of pulses defined by a pulse width value and an amplitude value. The pulse amplitude value is increased (e.g., manually), and the pulse width value is automatically decreased in response to increasing the pulse amplitude value in a manner that increases the intensity of the applied electrical stimulus. Alternatively, the pulse width value may be decreased (e.g., manually), and the pulse amplitude value automatically increased in response to decreasing the pulse width value in a manner that increases the intensity of the applied electrical stimulus.