Wearable Stabilization Support for Predictive Fall Prevention
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Solution Overview
Problem
Existing fall prevention systems either react after a fall has occurred or actively support movement, failing to prevent falls effectively, and are often cumbersome and inflexible, restricting user mobility.
Innovation Solution
A motion-dependent stabilization support system using sensors and actuators that detect impending instability based on movement parameters and a biomechanical model, selecting a stabilization strategy to control actuators and prevent falls by restricting movement into unstable positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If exoskeletons with active movement support are used to prevent falls, then fall prevention capability is improved, but the system becomes heavy, inflexible, and energy-intensive
Solution Approach 1:
The system performs preliminary stabilization by detecting impending falls through sensor data analysis and biomechanical modeling before the actual fall occurs. The control unit calculates future body positions and activates actuators in advance to prevent instability, rather than reacting after a fall has occurred or providing continuous active support.
Solution Approach 2:
The invention replaces heavy mechanical exoskeleton structures with a control-based system that uses sensors, a biomechanical movement model, and selective actuator activation. Instead of continuous mechanical support, the system uses intelligent prediction and targeted intervention to achieve fall prevention with minimal mechanical intervention.
2Reliability
If exoskeletons with active movement support are used to prevent falls, then fall prevention capability is improved, but the system becomes inflexible and difficult to wear
Solution Approach 1:
The system activates stabilization measures only when impending fall is detected through sensor analysis and biomechanical modeling. Rather than requiring the wearer to continuously engage with a rigid exoskeleton, the system performs preliminary detection and intervention only when needed, making the device flexible and comfortable for everyday wear.
Solution Approach 2:
The system transitions from a static, continuously supportive exoskeleton to a dynamic system that adapts its level of support based on real-time sensor data and predicted body movements. The actuators are selectively activated only when stabilization is needed, allowing the system to be both effective and flexible during normal activities.
3Measurement precision
If optical devices are used to observe trajectories for learning systems, then movement guidance is achieved, but spatial constraints and reduced flexibility occur
Solution Approach 1:
The invention replaces optical observation devices with an inertial sensor-based biomechanical modeling system. The sensors attached to the body directly measure movement parameters and the biomechanical model calculates future positions, eliminating the need for external optical devices and their associated spatial constraints.
Solution Approach 2:
The system introduces a biomechanical movement model as an intermediary between sensor measurements and stabilization control. This model processes sensor data to predict future body positions and determines appropriate stabilization strategies, enabling flexible adaptation to various movement scenarios without spatial constraints.
4Reliability
If continuous actuator control is used to maintain stability, then prevention of impending fall is improved, but energy consumption increases
Solution Approach 1:
The system uses preliminary detection through sensor analysis and biomechanical modeling to identify impending falls before they occur. Actuator control is activated only when stabilization is needed based on predicted future positions, rather than continuous control, significantly reducing energy consumption while maintaining effective fall prevention.
Solution Approach 2:
The system implements periodic sensor measurements and evaluation rather than continuous actuator control. The control unit continuously monitors sensor data and predicts future body positions at discrete intervals, activating actuators only when stabilization strategies are required, creating an energy-efficient periodic control rhythm.
Data Source
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AI summary
The invention relates to a movement-dependent stabilisation support system (100) for stabilising a moving body (200), which comprises a plurality of sensors (110), a plurality of actuators (120) and a control unit (130). The plurality of sensors (110) continuously detects movement parameters of the body (200), on which basis the control unit (130) determines whether there is an instability of the body (200). If it is determined that there is an instability, the control unit (130) selects a stabilisation strategy, according to which the actuators (120) are controlled. When controlled, the actuators (120) attached to the body (200) stiffen and limit the freedom of movement of the body (200), such that a movement in the direction of the upcoming unstable state is prevented or suppressed. In this way, the body (200) is supported in its stabilisation and an upcoming fall is prevented.