Triaxial Acceleration Sensor Signal Analysis for Human Motion State Classification
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Solution Overview
Problem
Existing sports monitoring devices are limited in their ability to comprehensively and automatically track various human body movement states, including sleeping conditions, round-the-clock, which is crucial for determining health and fitness improvements.
Innovation Solution
A method and device utilizing a triaxial acceleration sensor to calculate energy and average power of acceleration signals, determining movement states (sleeping, light, fierce, irregular, and regular) by setting thresholds and quasi-periodicity analysis, and accumulating time and energy data for each state, with optional step counting and display of movement metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a pedometer is used to monitor movement, then step counting function is provided, but other movement forms and sleeping conditions cannot be monitored
Solution Approach 1:
The monitoring device integrates multiple monitoring functions into a single system. The processor analyzes acceleration signals to simultaneously detect sleeping conditions, various movement states (light, fierce, irregular), and step counting, replacing the need for multiple separate devices and enabling comprehensive health monitoring
2Adaptability or versatility
If comprehensive movement monitoring is implemented, then all movement forms and sleeping conditions can be tracked, but human operation intervention is required
Solution Approach 1:
The device automatically distinguishes between sleeping state and various movement states through algorithmic analysis of acceleration signal characteristics. The processor autonomously calculates average power, compares it against thresholds, and identifies states without user intervention, enabling continuous automated monitoring
Solution Approach 2:
The system continuously analyzes acceleration signals and provides real-time state identification through feedback loops. The processor monitors signal characteristics, adjusts state determination based on calculated parameters, and maintains continuous automatic monitoring through this closed-loop feedback mechanism
3Productivity
If simple threshold comparison is used for state determination, then processing is fast, but sleeping abnormal movements cannot be accurately detected
Solution Approach 1:
The monitoring approach is segmented into different processing paths based on state type. For sleeping state detection, the system applies specialized analysis including abnormal movement identification algorithms, while other states use simpler threshold-based methods, optimizing both precision for critical detections and speed for general monitoring
4Duration of action of moving object
If continuous monitoring is implemented, then round-the-clock tracking is achieved, but energy consumption increases
Solution Approach 1:
The device performs periodic monitoring at defined sampling intervals rather than continuous processing. The processor analyzes acceleration signals at specific time periods, determining states at each interval, which reduces computational load and energy consumption while maintaining comprehensive monitoring coverage throughout the day
Data Source
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AI summary
The present invention provides a human body movement state monitoring method and device. The method comprises the following steps performed repeatedly: obtaining acceleration signals having a set sampling time period from output of a triaxial acceleration sensor worn on a human body, and calculating the energy and average power of the acceleration signals; determining a human body movement state according to the average power of the acceleration signals, and if the average power of the acceleration signals is more than a predetermined fierce movement threshold, determining that the human body is in a fierce movement state, if the average power of the acceleration signals is less than a predetermined sleeping threshold, determining that the human body is in a sleeping state, if the average power of the acceleration signals is less than the fierce movement threshold and is more than the sleeping threshold, determining that the human body is in a light movement state; if the human body is in the fierce movement state, further determining whether the acceleration signals have quasi-periodicity, if the acceleration signals do not have quasi-periodicity, determining that the human body is in an irregular fierce movement state, if the acceleration signals have quasi-periodicity, determining that the human body is in a regular fierce movement state. The method can automatically, comprehensively, round-the-clock, accurately monitor various movement states of a person.