AI-Based Exoskeleton Performance Evaluation Using Multi-Sensor Data
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Solution Overview
Problem
Existing exoskeleton performance evaluation relies solely on subjective wearer feedback, lacking objective indicators for personalized and effective assistance.
Innovation Solution
A system and method using load cells, force sensing resistors, and torque sensors to measure user interaction forces, combined with AI models for analyzing exoskeleton performance, providing objective evaluation and personalized assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If subjective wearer feedback is used for performance evaluation, then the evaluation process is simple, but the measurement precision and objectivity are insufficient
Solution Approach 1:
The patent replaces the mechanical/subjective feedback mechanism with an AI-based intelligent evaluation system that processes sensor data objectively. The AI model analyzes multiple sensor inputs (load cell, FSR, angle, speed, torque) to generate performance evaluations, substituting human subjective judgment with automated intelligent analysis that provides both simplicity and precision.
2Measurement precision
If multiple sensors are integrated for objective measurement, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent merges multiple sensor types (load cell, FSR, angle sensors, speed sensors, torque sensors) into a unified evaluation system. By combining these sensors and integrating their data through a single AI model, the system achieves comprehensive measurement precision while managing complexity through unified data processing rather than separate analysis for each sensor.
Solution Approach 2:
The AI model serves as a universal processing unit that handles data from multiple different sensor types. This multi-functional approach allows the system to process diverse sensor inputs through a single intelligent algorithm, reducing the complexity that would otherwise arise from needing separate processing paths for each sensor type.
3Measurement precision
If AI model is used for performance analysis, then the evaluation accuracy and personalization improve, but the computational requirements and system complexity increase
Solution Approach 1:
The patent performs preliminary data processing and feature extraction before feeding data to the AI model. By pre-processing sensor data and extracting relevant features in advance, the system reduces the computational burden on the AI model during real-time evaluation, thereby managing system complexity while maintaining high accuracy.
Data Source
AI summary
Disclosed is a system for analyzing performance of an exoskeleton using an artificial intelligence model. The system for analyzing performance of an exoskeleton using an artificial intelligence model includes: an exoskeleton data measurement unit that measures usage data using a sensor attached to a muscle-enhancing wearable device, an exoskeleton data transmission unit that transmits data measured by the exoskeleton data measurement unit, an AI model management unit for performance analysis of an exoskeleton that generates an AI model for analyzing the performance of the exoskeleton, and an exoskeleton performance prediction unit that predicts the performance of the exoskeleton using the AI model.