Fitness System Automated Workout Tracking via Sensor Fusion
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Solution Overview
Problem
Existing fitness tracking systems require manual input of workout information, which can be inaccurate and inconvenient, and may not respect user privacy or utilize sensors in all fitness equipment.
Innovation Solution
A fitness system comprising a wearable device, local server, and remote server that automatically tracks workout data from both the user and exercise equipment, processing this data to provide exercise recommendations and information without requiring special gym equipment or compromising user privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual input of workout information is used, then users can track their workouts, but accuracy decreases and convenience is reduced
Solution Approach 1:
The system enables automatic tracking of workout data by having the equipment and wearable device self-report information to the computing system without requiring user intervention. The equipment sensors detect exercise parameters and the wearable device tracks user metrics, both automatically transmitting data to generate workout records.
Solution Approach 2:
The patent replaces the mechanical manual input system with an automated electronic sensing and data transmission system. Sensors on the equipment and wearable device electronically capture and transmit workout data, eliminating the need for manual writing or digital entry by the user.
2Extent of automation
If automated tracking using sensors is implemented, then data accuracy improves and manual input is eliminated, but device complexity increases
Solution Approach 1:
The computing system serves multiple functions: it receives data from various equipment types, processes information from different wearable devices, associates users with equipment, generates workout summaries, and provides recommendations. This multi-functionality consolidates complexity into a single central system rather than requiring complex functionality in each individual component.
Solution Approach 2:
The computing system acts as an intermediary that receives data from multiple independent sources (equipment sensors and wearable devices) and translates them into unified workout information. This mediator approach simplifies the overall system architecture by centralizing data processing and coordination functions.
3Measurement precision
If user sensor data and equipment sensor data are processed together, then accurate workout association is achieved, but data processing complexity increases
Solution Approach 1:
The system uses feedback from multiple data sources to verify and refine workout associations. By comparing user sensor data (such as motion patterns and physiological metrics) with equipment sensor data (such as weight moved and repetitions), the system can confirm proper association and correct any mismatches, improving accuracy through iterative verification.
Data Source
AI summary
A fitness system includes a computing system in communication with a wearable device and multiple pieces of exercise equipment. The wearable device is associated with a user, includes a user sensor for detecting motion, and outputs user sensor data. The multiple pieces of exercise equipment are configured to be used by the user to perform an exercise therewith, include an equipment sensor for detecting motion, and output equipment sensor data. The computing system receives and processes the user sensor data collected at a first time and the equipment sensor data collected from the multiple pieces of exercise equipment at the first time to associate the user with one of the multiple pieces of exercise equipment used by the user at the first time, determines exercise information, exercise recommendations, or both, and transmits the exercise information, the exercise recommendations, or both.