International Business Machines Corporation

Susmita Saha

Paul R Bastide

Arun Vishwanath

Dwarikanath Mahapatra

Stefan Von Cavallar

Filiz Isabell Kiral-Kornek

Isabell Filiz Kiral-Kornek

Fang Lu

Stefan Harrer

Benjamin Scott Mashford

Subhrajit Roy

Color images of food a user consumes, text information associated with the food and audio information associated with the food may be received. Color images are converted into hyperspectral images. A machine learning model classifies the hyperspectral images into features comprising at least taste, nutrient content and chemical composition. A database of food consumption pattern associated with the user is created based on classification features associated with the hyperspectral images, the text information and the audio information. A color image of local food may be received and converted into a hyperspectral image. The machine learning model is run with the hyperspectral image as input, and outputs classification features associated with the local food. Based on whether the classification features associated with the local food satisfies the food consumption pattern associated with the user, the local food may be recommended.

Generating hyperspectral image database by machine learning and mapping of color images to hyperspectral domain

A computer-implemented method for determining routes includes receiving a user's location and health measures, for a plurality of users, analyzing the plurality of users and their corresponding locations to determine health behaviors at a given location and time, receiving a request from a user for a route, developing a route to the user's destination from a current location to obtain a target health behavior within a given threshold or constraint based on the plurality of user's healthy behaviors, and presenting the a route on a computing device.

Crowdsourcing health improvements routes

Providing an activity for a participant may include receiving at least location data specifying a location of the participant. An engagement level of the participant may be predicted based on the location data. Sensor data associated with the participant may be received, the sensor data comprising at least current physiological data associated with the participant. Based at least on the predicted engagement level and the sensor data, an exercise for the participant to perform may be determined. A notification signal may be transmitted to the participant to perform the exercise.

Machine learned optimizing of health activity for participants during meeting times

A method for neuromodulation includes monitoring brain activity of a patient using one or more electrodes attached to the patient, and using a first machine learning model to predict whether a patient will have a seizure based on the monitored brain activity of the patient. The method also includes, responsive to the first machine learning model predicting that the patient will have a seizure, using a second machine learning model to determine a neuromodulation signal pattern for preventing the predicted seizure. The method further includes using a neurostimulator to apply the determined neuromodulation signal pattern to the patient. The method also includes, after applying the determined neuromodulation signal pattern to the patient, detecting whether the patient had the predicted seizure based on the monitored brain activity of the patient. The method further includes adjusting at least the second machine learning model based on whether the patient had the predicted seizure.

Seizure detection, prediction and prevention using neurostimulation technology and deep neural network

A system to monitor visual health includes a processor operatively coupled to memory. The system further includes one or more subsystems configured to record data related to eye-health. The processor is configured to analyze the recorded data, detect a likelihood of eyestrain based on the analysis, and generate an alert to perform at least one action in response to the detection and based on the analysis.

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Melbourne, Australia

Susmita Saha