Automated health data acquisition, processing and communication system and method

Abstract

In one or more implementations, the present application includes a system and method to classify user activity. A passive tracking device, a processor configured to receive information from the tracking device, and a database are disclosed, in which the database is accessible by the processor and stores tracking device information, user profile information and external information. The processor is configured to execute instructions that cause the processor to perform various steps, such as to define a first activity unit having a first start time that corresponds to detection of the user being engaged in an activity, and monitor the tracking device information, the external information or both. The processor is further configured to establish a first end time of the first activity unit using the monitored information, and automatically ascribe a classification of the first activity unit. The classification of the first activity unit is output to a display of a computing device, and the classification of the first activity unit is stored in the database. Moreover, a user interface is provided that includes selectable options associated with the first activity unit. Thereafter, in response to at least a received selection of at least one of the selectable options, the classification is revised by: joining the first activity unit and a second activity unit having a second start time and a second end time, such that the revised classification has a start time equal to the first start time and an end time equal to the second end time. Further, the first activity unit is merged with a second activity unit having a second start time and a second end time, such that the revised classification has a start time equal to the first start time and an end time equal to the second end time. Alternatively, the first activity unit is divided into at least two activity units, each of at least two activity units having a different respective start time and a different respective end time. The revised classification is output to a display of a computing device, the revised classification is stored in the database.

Description

FIELD[0001]The present application relates, generally, to automated health data acquisition and, more particularly, to automatically classifying health-related activity information in view of biological and / or behavioral tracking and / or external conditions.BACKGROUND OF THE INVENTION[0002]Despite advances in many areas of technology, there are still barriers to assessing the relative health of a person in a rapid, cost effective, and timely manner. With the increase in health care costs and prevalence of diseases related to unhealthy lifestyles such as diabetes and heart disease, it is important to assess the relative health of individuals, and this has not been adequately addressed. Moreover, in many areas of the world access to doctors is limited. Even in the developed world, a doctor's time is considered a precious commodity and there are often long waiting lists and doctor-to-specialist referral systems that have to be navigated before being seen. Accordingly, it can be very dif...

AI Technical Summary

Problems solved by technology

Despite advances in many areas of technology, there are still barriers to assessing the relative health of a person in a rapid, cost effective, and timely manner.

With the increase in health care costs and prevalence of diseases related to unhealthy lifestyles such as diabetes and heart disease, it is important to assess the relative health of individuals, and this has not been adequately addressed.

Moreover, in many areas of the world access to doctors is limited.

Accordingly, it can be very difficult to gain access to medical professionals in order to receive information about one's health.

Unfortunately, such tracking devices operate in an isolated fashion and do not collectively contribute to provide an accurate and timely representation of a person's biological, physiological and / or activity-based conditions.

Despite recent advances in fitness tracking technology, fitness activity continues to be represented in misleading ways and requires user input and manual intervention to correct for inaccuracy.

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