Rotation Axis Estimation Algorithm for Mobile Accelerometers
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Solution Overview
Problem
Current mobile phones with accelerometers face challenges in accurately identifying user-imposed rotational movements due to parasitic accelerations from gravity and environmental noise, limiting their usage to simple tasks like screen orientation and shock detection.
Innovation Solution
A method that estimates a unique axis of rotation using an algorithm that leverages the difference between gravitational and user-imposed accelerations, projecting these differences to form a cloud of points and calculating the most probable axis of rotation, allowing for the triggering of applications without manual key manipulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If complex rotational movements are applied to the mobile phone to enable gesture control, then the versatility and ease of operation are improved, but the difficulty of detecting and measuring the movements increases due to parasitic accelerations from gravity and environmental noise
Solution Approach 1:
The patent converts the harmful parasitic acceleration from gravity into a useful reference signal. By continuously measuring the gravitational acceleration vector and comparing it with the total acceleration measured by the accelerometer, the system can isolate the user-imposed movement component. This allows the system to detect rotational movements accurately despite the presence of gravitational interference, enabling gesture control functionality.
2Adaptability or versatility
If the accelerometer is used to measure complex rotational movements, then the adaptability and versatility are improved, but the measurement precision deteriorates due to the low signal-to-noise ratio from parasitic accelerations
Solution Approach 1:
The patent segments the acceleration measurement into distinct components: gravitational acceleration and user-imposed acceleration. By separating these components through vector subtraction (total acceleration minus gravitational acceleration), the system isolates the signal of interest (user movement) from the noise (gravitational interference). This segmentation enables precise measurement of complex rotational movements while maintaining adaptability to various movement types.
3Ease of operation
If the skeletal chain movements are used for gesture control, then the ease of operation is improved, but the difficulty of detecting and measuring increases due to the large number of degrees of freedom and muscles involved
Solution Approach 1:
The patent creates a universal measurement approach that can detect various types of rotational movements (horizontal rotation, vertical rotation, diagonal rotation) using a single accelerometer-based system. By establishing a reference frame and calculating angular velocities from the acceleration data, the system can identify different gesture types without requiring separate sensors or complex mechanical structures. This multi-functionality enables the system to handle the complexity of skeletal chain movements through a unified detection mechanism.
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
Enhances the recognition of complex arm movements, expanding the capabilities of mobile phone accelerometers beyond basic functions by improving estimation precision and robustness, enabling features like gesture-controlled app activation.
Implementation Method 1
The accelerations due to the movement imposed by the user are much lower than the acceleration due to terrestrial gravitation
Implementation Method 2
accelerometers are increasingly common electronic components in everyday objects such as video game console controllers
Data Source
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AI summary
The present invention relates to a method for identifying a unique axis of rotation (P) for reconstructing a rotational movement (12) imposed by a user on a mobile application system (10) such as a mobile phone (150). The method of the invention comprises an algorithm for estimating the most probable axis of rotation from data provided by the embedded three-axis accelerometer (11). The algorithm of the invention projects the provided data onto a given module to obtain a point cloud (Ti) in a plane. From this point cloud, the algorithm of the invention calculates an estimate of the most probable axis of rotation. Then, an application (29b) associated with this estimated axis of rotation is triggered by the mobile system.