Wearable Heart Rate Tracking Context Filtering
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Solution Overview
Problem
Existing wearable devices for tracking heart rate data often face inaccuracies and usability issues due to interference from other data and environmental factors, making it difficult to collect and process reliable heart rate information.
Innovation Solution
A wearable computing device equipped with sensors that can detect and collect heart rate data, determine appropriate algorithms for processing based on context, and present the data in a meaningful manner, allowing for different techniques to be used in various situations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple heartrate collection techniques are used simultaneously, then the quantity of heartrate data collected increases, but the reliability of the data decreases due to interference and inaccuracies
Solution Approach 1:
The patent segments the heartrate collection process by identifying and separating different collection techniques (e.g., optical sensors, electrical sensors) and their respective data streams. By segmenting the data collection methodology, the system can selectively apply processing algorithms to each technique's data, filtering out unreliable measurements while preserving accurate ones, thus maintaining high reliability even as quantity increases.
Solution Approach 2:
The patent extracts and removes unreliable data artifacts from the heartrate dataset using contextual information and processing algorithms. By taking out corrupted or inaccurate measurements caused by interference or sensor limitations, the system preserves the integrity of the remaining data, ensuring high reliability while maintaining comprehensive data collection.
2Measurement precision
If context-aware processing algorithms are applied, then the measurement precision of heartrate data improves, but the device complexity increases
Solution Approach 1:
The patent implements preliminary action by pre-defining contextual categories (e.g., exercise, sleep, stress) and their associated processing algorithms before actual measurement occurs. When heartrate data is collected, the system quickly matches the current context to predefined categories and applies the corresponding algorithms, avoiding the need for complex real-time analysis while maintaining high measurement precision.
Solution Approach 2:
The patent applies parameter changes by adjusting processing algorithm parameters based on detected context. Instead of using a single complex processing system, the system changes parameters such as filtering thresholds, sampling rates, and algorithm selection according to the contextual situation, achieving high precision with simpler, adaptable processing rather than consistently complex processing.
3Adaptability or versatility
If multiple sensors and algorithms are deployed, then the adaptability of heartrate tracking to different situations improves, but the ease of operation decreases due to difficulty in making sense of data
Solution Approach 1:
The patent implements feedback by continuously monitoring contextual information and adjusting data processing algorithms accordingly. The system provides feedback to the user through simplified presentations of heartrate data that are already processed and contextualized, making the data easier to interpret while maintaining high adaptability to different situations through automated contextual adjustment.
Solution Approach 2:
The patent introduces an intermediary processing layer that translates complex sensor data into simplified, context-aware representations. This intermediary layer acts as a mediator between the multiple sensors and the user, automatically interpreting and presenting data in an easy-to-understand format while preserving the adaptability provided by multiple sensors and algorithms.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution enables improved heart rate tracking by filtering out unnecessary data artifacts and using context-appropriate algorithms, resulting in more accurate and usable heart rate data.
Implementation Method 1
a photodetector configured to sense changes in light transmission through the body
Data Source
AI summary
An example technique may include tracking motion of a user wearing the wearable device using at least first sensors of one or more sensors of the wearable device. The technique may also include tracking a physical state of the user using at least second sensors of the one or more sensors of the wearable device. The technique may also include determining whether an application of the wearable device has been launched. The technique may also include determining an action category of the user based at least in part on at least one of the motion of the user, the physical state of the user, or whether the application has been launched. The technique may also include collecting heartrate data of the user. The technique may also include categorizing the heartrate data based at least in part on the determined action category.