Motor Function Assistance Apparatus Using Hypothesis Inference
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Solution Overview
Problem
Existing technologies lack an apparatus capable of improving motor functions, particularly in rehabilitation settings where consistent physiotherapy is challenging due to variability in therapist competence and lack of explicit recording of evaluation processes.
Innovation Solution
A motor function improvement assistance apparatus that utilizes background knowledge associating body part states with kinematic problems through causal relationships, receives medical and examination data, generates hypotheses of kinematic problems via hypothesis inference, and combines these hypotheses to identify interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual physiotherapy evaluation is performed by therapists, then motor function improvement can be achieved, but consistency and reliability vary due to differences in therapist competence and experience
Solution Approach 1:
The system copies and reproduces the clinical inference processes of expert therapists through hypothesis inference algorithms. It generates hypotheses about kinematic problems by inferring from observation data, thereby replicating expert therapeutic reasoning without requiring human therapists for each evaluation.
Solution Approach 2:
The patent replaces the mechanical system of manual therapist evaluation with an automated information processing system. The hypothesis inference apparatus processes observation data through logical reasoning to generate motor function improvement plans, substituting human expertise with computational intelligence.
2Reliability
If detailed clinical evaluation processes are recorded, then improvement plan consistency can be enhanced, but the complexity of recording and processing increases
Solution Approach 1:
The system segments the complex clinical evaluation process into distinct modular components: observation data collection, hypothesis inference processing, and improvement plan generation. This segmentation allows each component to be processed independently and systematically, reducing overall complexity while maintaining thoroughness.
Solution Approach 2:
The hypothesis inference apparatus acts as an intermediary between raw observation data and final improvement plans. It processes and transforms the data through systematic logical reasoning, serving as a mediator that simplifies the connection between data collection and treatment planning.
3Reliability
If hypothesis inference is used to generate motor function improvement plans, then consistency can be improved, but the complexity of the inference system increases
Solution Approach 1:
The hypothesis inference apparatus is designed as a universal system that can handle multiple types of observation data and generate various kinds of improvement plans. It performs multiple functions including data processing, hypothesis generation, and plan creation within a single integrated framework, reducing overall system complexity.
Data Source
AI summary
Provided are a motor function improvement assistance apparatus, a motor function improvement assistance method, and a motor function improvement assistance program that are capable of improving a motor function. The motor function improvement assistance apparatus includes: a background knowledge storage unit that stores background knowledge in which a state of an observable body part and a kinematic problem of the state of the body part are associated with each other, based on a causal relationship; an observation reception unit that receives an observation including examination information and medical interview information of a subject; a hypothesis generation unit that generates, based on the background knowledge and the observation, a plurality of kinematic problem hypotheses by using hypothesis inference; and a hypothesis link generation unit that generates a combination of hypotheses that include an interaction therebetween.