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Processing stomach expansion and heart data to identify food intolerance reactions

IP.com Disclosure Number: IPCOM000255678D
Publication Date: 2018-Oct-09
Document File: 2 page(s) / 18K

Publishing Venue

The IP.com Prior Art Database

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Processing Stomach Expansion and Heart Data to Identify Food Intolerance Reactions

Problem Statement

Whilst the food intolerance market is growing, associated technologies for intolerance detection are not being developed at the same speed. Currently, the industry-standard solution for food intolerance diagnosis and management is a self-maintained food and symptom diary, coupled with dietician consultation.

            Stomach expansion, or bloating, is a key indicator of food intolerance to be tracked.

            However, there is no existing technology that allows us to adequately gather, process and show stomach expansion data. The system here is a food intolerance diagnosing tool.

            The system will collect data about stomach expansion, heart rate and other body metrics. The system allows leverage and processing stomach expansion data and cross referencing it with heart rate information to deliver insights to users about any food intolerance issues.

            The advantage of this solution is that the user no longer needs to observe their own body and make subjective calls of what is a food intolerance reaction. Combined with existing food tracking application, the system would be able to pinpoint what food caused a food intolerance reaction, a capability not available today.

            The system allows processing data from sensors and user context to determine food intolerance. The implementation would be as follows:

1.            Using existing technologies and body sensors in the market, gather data on:

a.            Heart rate

b.            Expansion of specific body parts (such as upper stomach)

c.            Body sweat

d.            Body heat

e.            Gyroscope and accelerometers on fitness devices

2.            Whenever the fitness devices detect that the person is doing exercise, the system will stop and ignore the data coming from heart rate and body part expansions. Other contextual factor will help avoid false positives, like for example their smartphone can pick up information of...

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