Wearable Physiological Data Tagging and Organization
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Solution Overview
Problem
Existing wearable devices generate vast amounts of physiological data that is difficult to search and utilize due to its voluminous and unorganized nature, often requiring frequent measurements and manual analysis to identify health state changes.
Innovation Solution
A method where a wearable device collects and transmits physiological data, allowing users to input tags based on their state or rules, which are then used to organize and store the data in a database, enabling easier searchability and analysis by associating data with specific tags, such as activity or health conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physiological data is collected continuously at high frequency, then measurement precision and health monitoring capability are improved, but data volume increases making storage and analysis difficult
Solution Approach 1:
The patent extracts and separates metadata (tags, contextual information, activity types) from the raw physiological data stream. This allows the system to handle large volumes of continuous data by organizing only the essential identifying information, reducing the burden of storing and analyzing complete raw datasets while maintaining health monitoring precision.
Solution Approach 2:
The patent segments physiological data into organized groups based on tags such as activity type, time, location, and health events. This segmentation transforms the voluminous continuous data stream into manageable, categorized units that are easier to store, retrieve, and analyze without losing measurement precision.
2Loss of information
If raw physiological data is stored without organization, then data completeness is maintained, but searchability and usability deteriorate
Solution Approach 1:
The patent applies preliminary organization by automatically tagging physiological data with metadata (activity type, location, time, health events) at the time of data collection. This preliminary action ensures data completeness is maintained while simultaneously improving searchability, as the data is already organized before retrieval is needed.
Solution Approach 2:
The patent introduces tags and metadata as intermediary elements between raw physiological data and user queries. These intermediaries enable efficient search and retrieval without compromising the completeness of the underlying data, acting as an indexing layer that improves usability.
3Measurement precision
If manual analysis of physiological data is performed, then data accuracy is maintained, but time consumption and productivity decrease
Solution Approach 1:
The patent implements self-service by enabling automatic tagging and organization of physiological data through contextual sensors and algorithms. The system automatically identifies activities, locations, and health events without manual intervention, maintaining data accuracy through consistent automated classification while dramatically improving analysis productivity.
Solution Approach 2:
The patent uses feedback from multiple sensor inputs (accelerometer, GPS, contextual sensors) to automatically classify and tag physiological data. This feedback mechanism enables the system to maintain high data accuracy through cross-validation of multiple data sources while eliminating time-consuming manual analysis.
Data Source
AI summary
A method for tagging and organizing data is provided. In one example, physiological data detected from a wearer of a wearable device is received and associated with a tag based, at least in art, on an input by the wearer. The input may be a state of the wearer, such as physical or mental state, or a rule. The collected physiological data may be organized based on the tag and, in some examples, on other types of received data, such as a wearer's personal data. In other example methods, data may be stored in a database based on one or more tags associated with the data.