Wearable Movement State Identification Using Acceleration and Heart Rate
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Solution Overview
Problem
Conventional movement state monitoring devices struggle to accurately distinguish between pacing and running, and they often misclassify periods of inactivity as sleep, known as 'fox sleep', leading to inaccurate health status analysis.
Innovation Solution
A wearable device equipped with a three-axis acceleration sensor and a human physical sign sensor, such as a heart rate sensor, calculates walking step frequency and physical sign frequency to differentiate between pacing and running states, and detects instantaneous abnormal motions to accurately identify sleep or wake states, using thresholds to determine the movement state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional step counting solution using acceleration sensor is used, then step number can be obtained by statistics, but it cannot effectively distinguish pacing and running states
Solution Approach 1:
The patent changes the parameters used for movement state identification from only acceleration-based step counting to multiple parameters including step frequency, heart rate, and their correlation. By analyzing the relationship between step frequency and heart rate frequency, the system can distinguish between pacing and running states with higher accuracy.
Solution Approach 2:
The patent introduces feedback mechanisms by continuously monitoring both acceleration signals and human physical sign signals, comparing their frequencies, and using the correlation between them to dynamically determine movement state. This feedback loop enables real-time distinction between pacing and running.
2Quantity of substance
If conventional sleeping statistic method based on duration is used, then sleeping quality can be recorded, but it causes fox sleep problem where device placed statically is misjudged as sleeping
Solution Approach 1:
The patent uses feedback by continuously comparing acceleration signals with human physical sign signals during supposed sleep periods. If the device is placed statically (fox sleep), the human physical sign sensor will not detect proper physiological signals, allowing the system to identify and exclude false sleep recordings.
Solution Approach 2:
The patent introduces human physical sign signals as an intermediary verification mechanism. Instead of relying solely on acceleration data, the system uses physiological signals (heart rate, etc.) as a mediator to confirm whether the user is actually sleeping or if the device has been misplaced.
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
The solution effectively distinguishes pacing and running states and accurately identifies sleep or wake states, reducing misclassification errors and providing more reliable health status analysis.
Implementation Method 1
providing a three-axis acceleration sensor and a human physical sign sensor in a wearable device; determining according to acceleration signals that are collected by the three-axis acceleration sensor
Implementation Method 2
calculating a corresponding physical sign frequency during the walking process according to a physical sign signal that is collected by the human physical sign sensor
Data Source
AI summary
A method and device for identifying a human movement state that includes: determining according to acceleration signals that are collected by a three-axis acceleration sensor that a human is in a walking state, calculating a walking step number of the human, and calculating a walking step frequency according to the number; calculating a corresponding physical sign frequency during the walking process according to a physical sign signal that is collected; and comparing the walking step frequency and the physical sign frequency that are obtained by calculating respectively with a step frequency threshold and a physical sign frequency threshold, and if the walking step frequency is greater than the step frequency threshold, and the physical sign frequency is greater than the physical sign frequency threshold, determining that the human movement state is a running state, and recording the calculated walking step number to be a running step number.