Multi-Body Motion Energy Estimation for Accurate Wearable Calorie Tracking
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Solution Overview
Problem
Existing wearable devices fail to provide real-time and accurate energy consumption data during exercise due to the lack of comprehensive data collection, particularly neglecting the energy expenditure of lower limbs.
Innovation Solution
A data processing method and device that acquires exercise data from a user's head, hands, and legs, using a pre-trained energy determination model to determine energy consumption by inputting this data and physical parameters such as height and weight, enabling accurate real-time energy calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wearable devices collect exercise data from multiple body parts (head, hand, and leg), then energy consumption measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent divides the exercise data collection into separate modules for different body parts (head, hand, leg), with each module independently acquiring and processing data. This segmentation allows the system to achieve comprehensive measurement precision while managing complexity through modular architecture, where each module can be optimized independently.
Solution Approach 2:
The patent implements a universal data processing system that handles multiple types of exercise data (head, hand, leg) through a single integrated energy determination model. This multi-functional approach allows one system to accurately measure energy consumption across different body parts without requiring separate specialized devices for each measurement.
2Measurement precision
If the system processes exercise data from head, hand, and leg to determine energy consumption, then energy consumption determination accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent merges the processing of exercise data from multiple body parts (head, hand, leg) into a single integrated energy determination model. By combining these data streams and processing them simultaneously through a unified model, the system achieves accurate energy consumption determination while reducing the complexity that would arise from separate processing pipelines.
Solution Approach 2:
The patent performs preliminary data processing and feature extraction for each body part before feeding the data into the energy determination model. This preliminary action organizes and pre-processes the complex data from head, hand, and leg sensors, reducing the computational burden on the main processing system and simplifying the overall data processing architecture.
Data Source
AI summary
The present disclosure provides a data processing method and device, the method includes: acquiring exercise data of a user in a preset time period and a physical parameter preset by the user, wherein the exercise data comprises exercise data of a head, a hand and a leg of the user; and inputting the exercise data and the physical parameter into a pre-trained energy determination model for processing to obtain energy consumed by the user in the preset time period.