Arm Movement Detection with Passive Motion Filtering
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Solution Overview
Problem
Existing devices for recording and evaluating movements are not suitable for specific body parts, particularly arms and fingers, which is a challenge in therapy and training, especially for stroke patients who require targeted rehabilitation.
Innovation Solution
A device comprising a computing unit, data memory, biometric sensor unit, and fastening device that filters passive arm movements from movement data, allowing for the efficient recording and evaluation of active arm movements, with features like a warning system and high-pass filtering to enhance data accuracy and user engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If general movement recording devices are used, then overall body movement can be tracked, but specific arm movements cannot be distinguished from passive body movements
Solution Approach 1:
The patent segments the movement detection function by separating arm-specific movement detection from general body movement. The sensor unit is specifically positioned on the arm to capture arm-specific acceleration patterns, while the evaluation module segments passive body movements from active arm movements through algorithmic differentiation. This segmentation enables precise arm movement measurement without requiring a completely new device architecture.
Solution Approach 2:
The evaluation module acts as an intermediary that processes raw movement data and distinguishes between passive body movements and active arm movements. It uses acceleration patterns and movement characteristics as intermediate parameters to filter and identify genuine arm movements, enabling precise measurement without direct complex sensor arrays on the arm.
2Measurement precision
If passive body movements are included in the data, then overall activity is captured, but active arm movements cannot be accurately evaluated
Solution Approach 1:
The evaluation module extracts and removes passive body movement data from the total movement dataset, isolating only the active arm movement components. By identifying characteristic patterns of passive movements (such as rhythmic patterns during walking) and excluding them, the system achieves accurate arm movement evaluation without compromising processing efficiency through complete data re-collection.
Solution Approach 2:
The system uses feedback mechanisms where the evaluation module continuously analyzes movement patterns and adjusts the filtering process based on detected passive movement characteristics. This feedback loop enables real-time differentiation between passive and active movements, maintaining high evaluation accuracy while optimizing data processing efficiency through adaptive filtering.
3Ease of operation
If the sensor unit is fastened to the arm, then arm movements can be recorded, but passive movements from body motion are also captured
Solution Approach 1:
The system dynamically adapts its evaluation criteria based on the detected movement patterns. The evaluation module adjusts its filtering parameters in real-time to distinguish between passive body movements and active arm movements, maintaining ease of arm movement recording while improving detection accuracy through dynamic pattern recognition and adaptive threshold adjustment.
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 efficient recording and evaluation of arm movements, providing users with insights into their activity levels and motivating them to improve their arm function through targeted training, with the ability to set and adjust movement goals.
Implementation Method 1
a sensor unit with at least one biometric sensor, preferably the acceleration sensor
Data Source
Figure 1
Figure 2~3
AI summary
The invention relates to a device (1) for detecting and evaluating movements of a user, comprising a computing unit (23), a memory (24), a sensor unit (25) having at least one biometric sensor, and a fastening means (3) for fastening the sensor unit (25) to an arm of the user. The computing unit (23) is configured for detecting movement data from movement signals generated by the sensor unit (25) and for storing the movement data in the memory (24). The device (1) further comprises an evaluation module (231), by way of which secondary movement data representing passive arm movements of the user can be filtered out of the movement data. The device (1) makes it possible to detect and evaluate the movements of an arm of the user in an efficient manner.