Correlating Sensor Data Streams for Exercise Device Engagement
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Solution Overview
Problem
Existing exercising devices and mobile devices lack efficient integration for data correlation and synchronization, making it difficult to accurately track user activities and provide real-time analysis during training sessions.
Innovation Solution
An apparatus with a processing core and memory, configured to receive and correlate sensor data streams from exercising devices and mobile devices, enabling the determination of device engagement and estimation of activity types, allowing for remote analysis and control between devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If exercising devices and mobile devices operate independently with separate data storage, then device complexity is reduced, but data correlation and activity tracking accuracy deteriorate
Solution Approach 1:
The patent introduces an intermediary system (server or cloud platform) that receives sensor data from both exercising devices and mobile devices, performs correlation processing, and returns integrated results. This mediator handles the complex data matching and activity type determination, allowing individual devices to remain relatively simple while achieving high tracking accuracy through centralized processing.
Solution Approach 2:
The patent merges data from multiple sources (exercising device sensors and mobile device sensors) into a unified activity profile. By combining accelerometer data, gyroscope data, and other sensor inputs from both devices, the system creates a more accurate and comprehensive view of user activity than either device could achieve alone.
2Productivity
If sensor data is stored locally on exercising devices and mobile devices, then data privacy and accessibility are improved, but data correlation and real-time analysis capability deteriorate
Solution Approach 1:
The system performs preliminary data processing and correlation on the server side before results are returned to individual devices. Activity types are determined in advance based on correlated sensor data, and this pre-processed information is then made available to both exercising devices and mobile devices for immediate display and analysis without requiring real-time data exchange during exercise sessions.
3Measurement precision
If multiple sensor data streams are correlated between exercising devices and mobile devices, then activity type determination accuracy is improved, but processing time and computational resources deteriorate
Solution Approach 1:
The server performs data correlation and activity type determination in advance, before the exercise session concludes. By pre-processing the sensor data streams and determining activity types upfront, the system avoids real-time processing delays during exercise sessions, enabling quick results to be displayed immediately after the session ends.
Data Source
AI summary
According to an example aspect of the present invention, there is provided an apparatus comprising at least one processing core, at least one memory including computer program code, the at least one memory and the computer program code being configured to, with the at least one processing core, cause the apparatus at least to receive a first sensor data stream from an exercising device, receive a second sensor data stream from a mobile device, correlate the first data stream with the second data stream, determine that the exercising device is engaged with the mobile device, and provide indication to the exercising device and the mobile device that the devices are engaged with each other.