Microsoft Technology Licensing, LLC

Siddharth Khullar

Daniel Morris

T Scott Saponas

Neel Suresh Joshi

Oscar Beijbom

Desney S Tan

Morgan Dixon

Harshvardhan Vathsangam

A 'Food Logger' provides various approaches for learning or training one or more image-based models (referred to herein as 'meal models') of nutritional content of meals. This training is based on one or more datasets of images of meals in combination with &#x201c;meal features&#x201d; that describe various parameters of the meal. Examples of meal features include, but are not limited to, food type, meal contents, portion size, nutritional content (e.g., calories, vitamins, minerals, carbohydrates, protein, salt, etc.), food source (e.g., specific restaurants or restaurant chains, grocery stores, particular pre-packaged foods, school meals, meals prepared at home, etc.). Given the trained models, the Food Logger automatically provides estimates of nutritional information based on automated recognition of new images of meals provided by (or for) the user. This nutritional information is then used to enable a wide range of user-centric interactions relating to food consumed by individual users.

Food logging from images

Restaurant-specific food logging from images

A system and method to determine pulse transit time using a handheld device. The method includes generating an electrocardiogram (EKG) for a user of the handheld device. Two portions of the user's body are in contact with two contact points of the handheld device. The method also includes de-noising the EKG to identify a start time when a blood pulse leaves a heart of the user. The method further includes de-noising a plurality of video images of the user to identify a pressure wave indicating an arterial site and a time when the pressure wave appears. Additionally, the method includes determining the PTT based on the de-noised EKG and the de-noised video images.

Determining pulse transit time non-invasively using handheld devices

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Seattle, WA, United States of America

Siddharth Khullar