Motion Recognition Device Using Sensor Fusion
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Solution Overview
Problem
Conventional wearable motion-sensing devices can only count motion cycles and lack the ability to recognize different types of motions, restricting their effectiveness in providing feedback to users during physical exercises.
Innovation Solution
A motion recognition device with a sensing unit and processing unit that generates and processes signals to recognize specific motion types, including variations in exercises, by using a combination of accelerometer and gyroscope signals to determine motion parameters and identify effective reference signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional motion-sensing devices are used to count motion cycles, then the device structure remains simple, but the device cannot recognize motion types or motion modes
Solution Approach 1:
The patent combines accelerometer and gyroscope sensors into a single motion recognition device, merging multiple sensing functions to achieve both motion cycle counting and motion type recognition. The processing unit integrates signals from both sensors to provide comprehensive motion analysis, resolving the contradiction by combining simple counting functionality with advanced recognition capabilities through signal fusion.
Solution Approach 2:
The motion recognition device is designed with multi-functionality to perform various tasks including motion cycle counting, motion type identification, and motion mode recognition. The processing unit can analyze different motion characteristics and provide diverse feedback to users, making the device universally applicable to various exercise types and fitness scenarios without requiring multiple separate devices.
2Reliability
If the device only counts motion cycles, then the device complexity is low, but the feedback effectiveness to users during exercise is insufficient
Solution Approach 1:
The patent implements a feedback mechanism where the processing unit analyzes motion signals and provides real-time feedback to users about their exercise form and technique. The system identifies specific motion types and modes, compares them against target exercise patterns, and delivers actionable feedback to help users improve their performance, thereby enhancing reliability of the feedback effectiveness.
Solution Approach 2:
The processing unit acts as an intermediary between the raw sensor signals and the user feedback. It processes and interprets the complex motion data, extracts meaningful patterns, and translates them into understandable feedback information. This intermediary function bridges the gap between simple data collection and effective user guidance, enhancing feedback reliability.
3Measurement precision
If the device recognizes detailed motion variations, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent segments the motion analysis process into distinct stages: raw signal collection from accelerometers and gyroscopes, signal fusion and filtering, motion characteristic extraction, and motion type classification. By dividing the complex analysis into manageable segments, the system achieves high measurement precision for detecting detailed motion variations while maintaining manageable processing complexity through structured algorithm design.
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
Enables accurate recognition of various body motions, providing feedback to users on their exercise form and efficiency, helping to improve training outcomes by distinguishing between different motion types and suggesting improvements.
Implementation Method 1
generates a sense signal in response to a body motion occurring at a specific position on a user's body
Implementation Method 2
using a combination of accelerometer and gyroscope signals to determine motion parameters
Data Source
AI summary
A motion recognition device includes a sensing unit and a processing unit. The sensing unit generates a sense signal in response to a body motion occurring at a specific position on a user's body, wherein the sense signal includes a first sense signal portion and a second sense signal portion different from the first sense signal portion, and the body motion belongs to a motion segment of a motion type. The processing unit processes the sense signal to generate a motion parameter signal structure including a fusion signal of the first and the second sense signal portions, and recognizes the specific position to determine an effective reference signal for recognition of the motion type based on the motion parameter signal structure.