International Business Machines Corporation

Boston Scientific Neuromodulation Corporation

University College Dublin

Giovanni Russo

Robert Shorten

Yassine Lassoued

Julien Monteil

Martin Mevissen

Qinghuang Lin

Jeffrey L Rogers

Tigran Tchrakian

Andrea Simonetto

Jonathan P Epperlein

Jakub Marecek

Rodrigo Hernan Ordonez-Hurtado

Claudio Gambella

Wynita M Griggs

Elizabeth Daly

Sergiy Zhuk

Pierpaolo Tommasi

Martin Stephenson

Joao H Bettencourt-Silva

Rudi Verago

Anton Dekusar

Bissan Ghaddar

Julia O'Connell

Eleni Pratsini

Barry Cardiff

Pietro Ferraro

Paul Dermot Cuffe

Systems and techniques are disclosed to adjust programming of an implantable electrical neurostimulation device for treating chronic pain of a human subject, through the use of a dynamic model adapted to identify pain treatment parameters for a human patient and determine a best device operational program to implement the pain treatment parameters to address the chronic pain condition. In an example, the system to adjust programming of the neurostimulation device performs operations that: obtain data related to a state of pain of the human subject; identify pain treatment parameters using a dynamic model adapted to evaluate the pain treatment parameters in the human subject over a time period, based on the data related to the state of pain; and select a neurostimulation program for the neurostimulation device, corresponding to at least a portion of the identified pain treatment parameters.

Adaptive chronic pain relief via implanted electrical neurostimulation

Systems and techniques are disclosed to establish programming of an implantable electrical neurostimulation device for treating chronic pain of a human subject, through the use of a dynamic model adapted to determine pain treatment parameters for a human patient and identify a new device operational program to implement the pain treatment parameters to address the chronic pain condition. In an example, the system to establish programming of the neurostimulation device performs operations that: obtain state data indicating a measured value that is correlated to pain experienced by the human subject; determine neurostimulation programming parameters, using a dynamic model, for pain treatment in the human subject, as the dynamic model is used to identify values of the neurostimulation programming parameters that predict an improvement to the measured value; and indicate a neurostimulation program for the neurostimulation device, that includes the neurostimulation programming parameters for the implantable electrical neurostimulation device.

Adaptive electrical neurostimulation treatment to reduce pain perception

Embodiments for identifying stochastic models representing the individual decision makers in a computing environment by a processor. One or more non-deterministic (stochastic, probabilistic) models may be identified according to a sequence of outcomes from decisions of each of a plurality of decision makers.

Identification of non-deterministic models of multiple decision makers

Techniques regarding pain treatment are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can include: a data collection component that can determine at least one parameter associated with a pain perception of a subject, a computing component that can determine a relationship between the pain perception and the at least one parameter using artificial intelligence, and can determine a treatment for the subject based on the relationship; and a treatment component that can cause a device associated with the subject to apply at least a portion of the treatment.

Adaptive pain management and reduction based on monitoring user conditions

Provided are an apparatus and system for directing power flow between multiple devices, the apparatus comprising: one or more inlet ports for connection to one or more devices; a plurality of outlet ports configured for supplying electrical power; and a computing device configured to route power from the one or more inlet ports to the outlet ports. The system comprises a plurality of the apparatus connected to each other.

Apparatus for directing power flow between multiple devices

In an approach for determining the illumination necessary along a vehicle's planned trajectory, a processor receives information relevant to the trajectory of a vehicle. A processor estimates the position of the vehicle at the particular time on the trajectory of the vehicle, using the data from the sensors. A processor estimates an illumination of the trajectory of the vehicle, using the model of the illumination of the road network and the data from the sensors, wherein a threshold is employed. A processor determines the threshold is exceeded. A processor changes a setting of the at least one headlight on the vehicle. A processor determines the threshold is exceeded. A processor alerts the user of the vehicle when adjustments to the at least one headlight that are necessary to illuminate the trajectory of the vehicle exceed physical limitations of the at least one headlight.

Adaptive headlights for the trajectory of a vehicle

Embodiments for implementing an intelligent health recommendation service by a processor. A health state of a user may be learned according to user behavior, physical conditions of the user, activities of daily living (ADL) and associated context of daily living (CDL) of the user, or a combination thereof. One or more applications, one or more application components, one or more internet of things (IoT) devices, or a combination thereof may be identified and recommended to minimize one or more possible negative impacts upon the health state of the user.

Intelligent health recommendation service

A system and method for cognitive journey monitoring are presented. Embodiments comprise journey prediction, parsing of data sources, risk assessment and mitigation, and natural-language user interaction by a cognitive processor. Data is gathered from a plurality of data sources and analyzed in the context of one or more of the user's intention(s). A dialogue with the user, in natural language, aims to provide and select one or more suggestions relating to the one or more user intention(s) such that the risk(s) relating to the one or more user's intention(s) is reduced. During the dialogue, cognitive reasoning may be performed, wherein the cognitive reasoning includes the ability to justify each suggestion and the ability to infer information from the interaction such as, for example, data obtained in a dialogue may inform subsequent inferences. The embodiments may use speech synthesis and speech recognition in an interactive spoken dialogue.

Cognitive journey companion system

Embodiments for planning vehicular driving actions in the presence of non-recurrent events by a processor. One or more dynamics of non-recurrent events in a transport network may be learned according to one or more contextual factors. One or more vehicle-specific factors may be learned in relation to a historical journey and current journey of a vehicle. One or more action responses associated with the one or more non-recurrent events and the one or more vehicle-specific factors may be generated.

Vehicular driving actions in the presence of non-recurrent events

Embodiments for testing embedded systems and their applications in an Internet of Things (IoT) environment by a processor, denoted as a Hardware-in-the-Loop as a Service (HiLaaS). In a simulated environment, one or more simulated entities and one or more real entities in a networked system may be tested in real-time according to received control parameters, for a price. The price is estimated by the system, based on other parameters, and offered to the user to accept or reject. Alternatively, the user may specify the price, the system estimates control parameters, and the user can accept or reject the control parameters. One or more properties of the one or more entities, the network system, or combination thereof may be estimated based on the testing of the one or more simulated entities, when the price and control parameters are accepted.

Testing embedded systems and application using hardware-in-the-loop as a service (HILAAS)

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Dublin, Ireland

Giovanni Russo