Physical Activity Analysis Using Multi-Sensor Deviation Detection
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Solution Overview
Problem
Existing physical activity measurement devices are limited in their functionality, primarily focusing on caloric aspects and step counting, and are not tailored for professional athletes or individuals with motor disorders like Parkinson's Disease, failing to provide comprehensive measurement and analysis for various activities and conditions.
Innovation Solution
A system and method that analyze physical activity by considering a user's specific needs, incorporating sensors to measure muscle pressure and body orientation, and using reference values from previous activities to detect deviations and recognize gestures, issuing commands or indicating condition changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional pedometers or accelerometers are used to measure steps or motion, then motion detection is achieved, but they cannot accurately distinguish between intentional exercise movements and incidental movements such as walking to catch a bus
Solution Approach 1:
The patent segments the measurement task into multiple independent sensors (accelerometer, gyroscope, magnetometer) that each capture different aspects of motion. By dividing the measurement function across multiple sensors, the system can analyze movement patterns from different dimensions and distinguish intentional exercise from incidental movement more accurately.
Solution Approach 2:
The patent creates a multi-functional measurement system where a single device integrates multiple sensor types (accelerometer, gyroscope, magnetometer) and processing capabilities. This universal device can detect various motion patterns, orientations, and intensities, enabling it to distinguish between different types of physical activity beyond what traditional single-function devices could achieve.
2Measurement precision
If multiple sensors are integrated to improve measurement accuracy, then exercise intensity detection is enhanced, but device complexity increases
Solution Approach 1:
The patent merges multiple sensor functions into a single integrated device. By combining the accelerometer, gyroscope, and magnetometer into one unit with unified processing, the system achieves high measurement precision while avoiding the complexity of multiple separate devices. The merged architecture allows coordinated operation of all sensors through a single processing system.
Solution Approach 2:
The patent implements self-service through automatic processing of sensor data. The system automatically analyzes data from multiple sensors, applies calibration, distinguishes between exercise and incidental movement, and generates activity classifications without requiring manual intervention. This automated self-processing reduces the operational complexity despite having multiple sensors.
3Productivity
If sensor data is continuously processed to provide real-time feedback, then user engagement is improved, but energy consumption increases
Solution Approach 1:
The patent employs periodic action by processing sensor data at strategically determined intervals rather than continuously. The system monitors for significant movement events and processes data primarily when changes are detected, reducing unnecessary processing during static periods. This periodic processing maintains real-time responsiveness while significantly reducing energy consumption compared to continuous processing.
Solution Approach 2:
The patent maintains continuity of useful action by keeping sensors active and ready to detect movement, while processing occurs continuously only when needed. The system maintains a continuous state of readiness to detect exercise activities, ensuring no useful measurement is lost, but actual processing is performed continuously only when movement events occur, optimizing the balance between real-time tracking and energy efficiency.
Data Source
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AI summary
A method of physical activity measurement and analysis, the method comprising computer-executed steps of: receiving at least one value extracted from measurements of a physical activity of a first user, and detecting a deviation of the physical activity of the first user from at least one previous physical activity using the received at least one value and at least one reference value calculated over at least one value extracted from measurements of the at least one previous physical activity.