Wrist-Worn Motion Sensor Velocity Estimation via Arm Swing
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Solution Overview
Problem
Existing methods for determining the velocity of a runner or walker are limited in accuracy, particularly when using sensors placed on the arm, as they struggle to accurately estimate step length and speed due to the different trajectory of the arms compared to the user's center of mass, and fail to integrate effectively with heart rate estimation.
Innovation Solution
A method utilizing a three-dimensional motion sensor worn on the wrist to measure motion signals, which combines energy values, fundamental movement frequencies, and orientation features to estimate velocity, and incorporates a bio-mechanical model to compensate for inertia moments, along with a user-specific calibration factor to determine instant velocity, and uses this velocity to improve heart rate estimation, especially when optical signals are of poor quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an accelerometer is placed on the shoe, ankle or knee to measure vertical acceleration, then the device can measure step frequency, but it cannot accurately determine step length and velocity due to the different trajectory from the user's center of mass
Solution Approach 1:
The patent uses the arm's motion as an intermediary to infer the user's velocity. By placing the sensor on the arm and measuring its acceleration, the system indirectly determines the user's movement state through the relationship between arm swing and body motion, resolving the contradiction between easy sensor placement and accurate velocity measurement
Solution Approach 2:
The patent changes the measurement parameter from direct center of mass acceleration to arm acceleration, and introduces derived parameters such as fundamental movement frequency and orientation features. These parameter transformations enable velocity estimation from arm motion data, achieving accurate measurement without complex sensor placement
2Measurement precision
If an accelerometer is fastened close to the user's center of gravity to measure acceleration, then the device can more accurately reflect user motion, but it increases the device complexity and reduces ease of operation
Solution Approach 1:
The arm serves as an intermediary body part that is easily accessible for sensor placement while still providing useful motion data. The arm's swing characteristics correlate with the user's overall motion state, allowing velocity measurement without requiring the sensor to be placed at the center of gravity, thus maintaining ease of operation
Solution Approach 2:
The sensor device on the arm serves multiple functions: measuring acceleration for velocity determination, detecting fundamental movement frequency for step detection, and capturing orientation features for activity recognition. This multi-functionality compensates for the suboptimal sensor location, achieving accurate velocity measurement while maintaining ease of wear
3Ease of operation
If the arm trajectory is used to estimate velocity, then the device is easy to wear, but the different trajectory of the arm from the user's center of mass reduces measurement precision
Solution Approach 1:
The patent analyzes arm motion in multiple dimensions by considering both the vertical component (for step frequency) and the horizontal component (for velocity estimation). It also incorporates temporal dimension through fundamental movement frequency analysis and spatial dimension through orientation features, creating a comprehensive velocity estimation that compensates for the arm's different trajectory
Solution Approach 2:
The system transforms the raw acceleration signal into multiple derived parameters including fundamental movement frequency, orientation angles, and energy values. These parameter transformations extract meaningful velocity information from the arm's complex motion pattern, improving precision while maintaining ease of wearability
4Measurement precision
If traditional heart rate estimation methods are used without velocity information, then the system is simpler, but the heart rate estimation accuracy deteriorates especially when optical signals are poor
Solution Approach 1:
The system uses velocity information as feedback to improve heart rate estimation. The determined velocity serves as an additional input parameter that provides contextual information about the user's exertion level, allowing the system to correct and refine heart rate estimates, especially when optical signals are degraded by motion artifacts
Solution Approach 2:
The heart rate estimation system combines multiple data sources (optical signals and velocity data) to create a composite estimation. This composite approach leverages the strengths of each data source and compensates for their individual weaknesses, improving overall accuracy without requiring a fundamentally complex system architecture
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
This approach allows for accurate determination of velocity and improved heart rate estimation by correlating motion signals with heart rate data, enhancing the robustness of heart rate measurement and providing reliable estimates of distance and energy expenditure.
Implementation Method 1
a motion sensor (2) for measuring a motion signal representative of the user's movements
Implementation Method 2
a photodetector (4) for measuring a photoplethysmographic signal representative of a user's heartbeat
Data Source
Figure 1
AI summary
The present disclosure concerns a method for determining an instant velocity of a user using a sensing device (1) destined to be worn on an arm of the user and comprising a motion sensor (2) for measuring and delivering an motion signal representative of the user's movements when the sensing device (1) is worn; the method comprising: measuring the motion signal; identifying when the user is performing a rhythmical activity and estimating a fundamental movement frequency of the user from the measured motion signal; identifying when the user is walking or running by calculating an activity level of the user using the measured motion signal and the fundamental movement frequency; when the user is walking or running, providing a relationship between the measured motion signal and corresponding motion features relating to a propulsive impulsion of a user's step; estimating a frequency of the user's step and a user-relative step length of the user using the motion feature; and determining a user-relative instants velocity by combining the estimated step frequency and the estimated step length; the instant velocity being determined from the user-relative instant velocity using a calibration factor from the user-relative instant velocity using a calibration factor.