Adaptive Training Device Using Feedback-Controlled Stimulus Signals
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Solution Overview
Problem
Current training devices lack an effective method to restore function in paralyzed arms using stimulus signals, particularly for individuals with disabilities, as they fail to provide personalized and adaptive stimulation for rehabilitation purposes.
Innovation Solution
A training device comprising an information outputter, exercise status detector, arithmetic processor, and stimulus signal generator, which evaluates and adjusts the stimulus signal based on the trainee's movement data to enhance rehabilitation effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a stimulus signal is applied to stimulate nerves and muscles for rehabilitation training, then training effects are enhanced, but the device complexity increases due to the need for evaluation and adjustment mechanisms
Solution Approach 1:
The arithmetic processor evaluates the degree of matching between training action instructions and actual body movements detected by sensors, then uses this evaluation result to adjust stimulus signal parameters. This closed-loop feedback mechanism ensures reliable rehabilitation effects while automating the adjustment process.
Solution Approach 2:
The system automatically adjusts stimulus signal parameters based on real-time movement evaluation without requiring manual intervention from trainers. The arithmetic processor self-regulates the stimulus signal generation unit according to the evaluated matching degree, making the device self-adjusting and reducing operational complexity.
2Adaptability or versatility
If the stimulus signal parameters are manually adjusted for each trainee, then personalized rehabilitation is achieved, but the loss of time increases due to manual adjustment processes
Solution Approach 1:
The arithmetic processor automatically evaluates movement data from sensors and adjusts stimulus signal parameters without manual intervention. The system serves itself by autonomously personalizing rehabilitation parameters based on real-time performance feedback, eliminating time-consuming manual adjustment processes.
Solution Approach 2:
The system pre-establishes the relationship between movement evaluation results and stimulus signal parameter adjustments in the arithmetic processor. When training begins, the processor immediately applies pre-programmed adjustment logic to evaluate and modify parameters in real-time, avoiding delays associated with manual decision-making.
3Reliability
If the stimulus signal strength is increased to improve rehabilitation effects, then training effectiveness improves, but harmful factors increase such as over-stimulation or discomfort
Solution Approach 1:
The system continuously monitors the degree of matching between intended and actual movements, and uses this feedback to dynamically adjust stimulus signal parameters. When movement quality is good, stimulus parameters are increased to enhance effectiveness; when movement quality deteriorates or discomfort is detected, parameters are reduced to prevent over-stimulation.
Solution Approach 2:
The stimulus signal parameters are made dynamic rather than static, automatically adjusting their strength based on real-time evaluation of movement quality and trainee response. This dynamic adjustment ensures optimal stimulation levels that maximize rehabilitation effects while preventing harmful over-stimulation.
Data Source
AI summary
A training device includes an information outputter, an exercise status detector, an arithmetic processor, and a stimulus signal generator. The information outputter includes at least one of an image output unit and an audio output unit. The exercise status detector includes a body portion, a first grip portion and a second grip portion provided on the body portion, and sensors that detect a motion of the body portion. The arithmetic processor issues training action instruction information through the information outputter, and evaluates a matching degree between the contents of the training action instruction information and the motion of the body portion, based on output signals from the sensors of the exercise status detector. The stimulus signal generator applies a stimulus signal to the arm of a trainee.