Biometric Measurement Adjustment for Activity Tracking
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Solution Overview
Problem
Conventional fitness tracking devices provide inaccurate biometric estimates for users with disabilities or those using assistive devices, as existing solutions are manual and prone to inaccuracies, requiring users to manually edit biometric data without context-specific adjustments.
Innovation Solution
A method that identifies user activities and determines the impact of biometric-affecting aspects, such as disabilities or assistive devices, to dynamically adjust estimated biometric measurements, using a processor and memory device to automatically adjust calorie burn and other biometric estimates based on user-specific data and sensor inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual editing of biometric data is used, then users can customize their biometric information, but accuracy and reliability are reduced due to lack of context-specific adjustments
Solution Approach 1:
The system automatically identifies biometric-affecting aspects and adjusts biometric measurements without requiring user intervention. The device performs self-service by detecting activities, identifying relevant aspects from stored information, and computing adjusted measurements autonomously, eliminating manual editing while maintaining accuracy.
Solution Approach 2:
The system dynamically changes biometric measurement parameters based on detected activities and identified biometric-affecting aspects. Different adjustment factors are applied depending on the specific activity context, transforming static biometric data into dynamically adjusted measurements that reflect actual physiological conditions.
2Measurement precision
If conventional biometric tracking is used, then device complexity is minimized, but measurement precision deteriorates for users with disabilities or assistive devices
Solution Approach 1:
The system performs preliminary actions by pre-storing information about biometric-affecting aspects associated with different activities before actual measurement occurs. This advance preparation allows the device to quickly retrieve and apply relevant adjustment factors during activities without complex real-time analysis, reducing operational complexity while maintaining precision.
Solution Approach 2:
The system introduces an intermediary layer that sits between raw biometric data and final measurements. This intermediary component identifies biometric-affecting aspects and applies adjustment factors, acting as a mediator that translates basic sensor data into contextually accurate biometric measurements without requiring the entire system to become complex.
3Reliability
If manual biometric editing is required, then adaptability to individual user needs is improved, but reliability deteriorates due to user inaccuracies and lack of context
Solution Approach 1:
The system implements feedback by continuously monitoring activity detection results and using this information to automatically adjust biometric measurements. The feedback loop ensures that biometric-affecting aspects are consistently identified and applied, maintaining reliability while adapting to different activity contexts without requiring manual user input.
Data Source
AI summary
One embodiment provides a method, including: identifying, using an information handling device, an activity engaged in by a user; determining, using a processor, whether a biometric of the user during the activity is affected by a biometric-affecting aspect; and adjusting, responsive to determining that the biometric is affected by the biometric-affecting aspect, an estimated measurement for the biometric. Other aspects are described and claimed.