Cable Drive Training Unit With State Machine Feedback Control
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Solution Overview
Problem
Existing motorized cable-pull training units are monotonous and lack complex interaction, leading to user demotivation, especially for inexperienced or injured individuals, as they primarily operate in simple states with limited user influence and fail to emulate the varied interactions found in natural training environments.
Innovation Solution
A training unit incorporating multi-variable feedback motor control and state machines that allow complex sequential interactions by combining user input with predefined rules, enabling the unit to change states based on multiple physical parameters, including force, position, time, and user-specific measurements, allowing for dynamic and varied training sequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motorized cable-pull training units operate in simple states with limited user influence, then control precision and measurement accuracy are improved, but user motivation and training variety deteriorate
Solution Approach 1:
The training unit transitions from static, pre-programmed sequences to dynamic state machines that respond in real-time to user performance. The system continuously monitors kinematic quantities and adjusts training parameters dynamically, allowing the training program to adapt during execution rather than following fixed sequences.
Solution Approach 2:
The system implements comprehensive feedback loops where sensors continuously measure user performance (force, position, velocity) and feed this information back to the state machine controller. This feedback enables real-time adjustment of training states based on actual user capability, creating a responsive interaction that maintains both precision and variety.
2Device complexity
If training sequences are preprogrammed with fixed states, then device complexity is reduced, but user interaction complexity and motivation deteriorate
Solution Approach 1:
The system adds a temporal dimension to state machine operation by incorporating time as a explicit parameter in state transitions. Rather than simple condition-based transitions, the state machine evaluates time-dependent conditions and sequences, creating multi-dimensional interaction patterns that increase complexity without requiring proportionally more hardware components.
Solution Approach 2:
The training program is segmented into discrete states with clearly defined transition conditions. Each state represents a specific training phase or exercise configuration, and the state machine orchestrates transitions between these segments based on real-time sensor data and time parameters, breaking down complex training sequences into manageable, programmable units.
3Manufacturing precision
If training units provide accurate load dosing and measurement, then physiological training effectiveness is improved, but user motivation deteriorates due to monotonous repetitions
Solution Approach 1:
The state machine implements periodic variations in training parameters, alternating between different exercise types, resistance levels, and motion patterns. This periodic action maintains accurate load dosing within each phase while introducing variety through systematic alternation between different training states, preventing monotony while preserving physiological effectiveness.
Solution Approach 2:
The system dynamically changes multiple training parameters simultaneously (force magnitude, velocity, position, time) based on state transitions triggered by user performance and time conditions. This multi-parameter variation maintains precise control over load dosing while creating diverse training experiences that adapt to user response patterns.
4Adaptability or versatility
If state machines with multiple states and time parameters are implemented, then training variety and user interaction are improved, but device complexity and control difficulty increase
Solution Approach 1:
The state machine controller serves multiple functions simultaneously: it monitors sensor inputs, processes time parameters, evaluates transition conditions, executes state transitions, and controls motor output. This universal controller architecture consolidates what would otherwise require separate systems into a single integrated unit, managing complexity through functional consolidation rather than proliferation of components.
Data Source
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AI summary
The state controlled training unit for physical training with cable drive is relevant for people in want or need of specialized physical training, where force and motion can be transmitted through a cable, including athletes, fitness enthusiasts and rehab patients. The invention solve the problem of repetitive and monotonous physical interaction associated with existing cable drive training units. The novelty draw from framing the inherent exchange of force and motion between user and unit, with a combination of multivariable feedback control and interactive state machines, that can produce and recognize motion/force sequences that are vastly more complex than the static setting or binary back, forth, back, forth ... sequences, associated with previous technology. The invention can be implemented using component and techniques know to practitioners in the fields of automation and computer science.