Upper Body Gesture Control for Powered Lower Extremity Orthotics
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Solution Overview
Problem
Powered lower extremity orthotics, such as exoskeletons, require a means to interpret user intentions for leg movement, especially for paraplegic patients who are completely paralyzed, to enable walking and other mobility tasks, as existing systems lack effective human-machine interfaces to translate upper body gestures or signals into leg actions.
Innovation Solution
A system and method that uses sensors to monitor upper body arm movements, walking aid positions, and velocities to determine desired leg movements, integrating this information into a finite state machine that controls the sequential operation of powered lower extremity orthotic components, allowing users to convey intent through gestures and signals, thereby regulating the exoskeleton's actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If sensors monitor upper body arm movements and walking aid positions to determine desired leg movements, then the ability to enable walking and mobility tasks for paraplegic patients is improved, but the device complexity increases
Solution Approach 1:
The control system is segmented into multiple independent components: arm movement sensors, walking aid position sensors, finite state machine controller, and powered orthotic actuators. Each component performs a specific function, and they are integrated through a modular architecture that processes inputs separately before coordinated output, reducing overall system complexity while maintaining versatility
Solution Approach 2:
A finite state machine serves as an intermediary between the sensors (monitoring arm movements and walking aid positions) and the powered orthotic actuators. This intermediary layer translates complex sensor inputs into discrete, manageable control states that drive leg movements, simplifying the control architecture while enabling sophisticated mobility tasks
2Reliability
If a finite state machine controls sequential operation of powered lower extremity orthotic components, then safety and determinism in state transitions are improved, but the ease of operation decreases
Solution Approach 1:
The finite state machine implements dynamic state transitions that adapt to real-time sensor inputs from arm movements and walking aid positions. The system transitions between predefined safe states based on detected user intentions, maintaining deterministic behavior while responding dynamically to changing conditions, thus preserving reliability without requiring complex manual intervention
3Ease of operation
If the system interprets user intentions through upper body gestures and signals, then the ease of operation is improved for paraplegic users, but the measurement precision requirements increase
Solution Approach 1:
The system merges data from multiple sensor sources (arm movement sensors and walking aid position sensors) to interpret user intentions. By combining these measurement streams, the system achieves robust intention recognition that compensates for individual sensor precision limitations, maintaining ease of operation while managing measurement precision requirements through sensor fusion
Data Source
AI summary
A system and method by which movements desired by a user of a lower extremity orthotic is determined and a control system automatically regulates the sequential operation of powered lower extremity orthotic components to enable the user, having mobility disorders, to walk, as well as perform other common mobility tasks which involve leg movements, perhaps with the use of a gait aid.