Biosensor-Based AI Conversation System for Impaired Users
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Solution Overview
Problem
Individuals with impaired abilities, such as those unable to speak or with limited mobility, face challenges in interacting with augmented and virtual reality systems, robotics, and artificial intelligence without assistance.
Innovation Solution
A system utilizing a biosensor and a perception engine to process biosignals and multimodal sensory data, generating prompts for a generative AI or generalist agent to facilitate AI-assisted conversations, allowing users to interact through a user experience engine with features like communication history and context data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional natural language interaction methods are used with AI systems, then users with full speech and mobility capabilities can effectively communicate, but users with impaired abilities (unable to speak or with limited mobility) cannot access these systems
Solution Approach 1:
The patent introduces biosensors as an intermediary that captures physiological signals (brain waves, heart rate, skin conductance) and converts them into actionable input for AI interaction. This mediator bridges the gap between users who cannot speak or move and the AI system, translating involuntary biological signals into meaningful commands and conversation inputs without requiring traditional speech or physical interaction
Solution Approach 2:
The patent replaces mechanical interaction methods (speech, typing, gesturing) with a physiological signal-based system. Instead of requiring users to physically produce speech or manipulate interfaces, the system captures involuntary biosignals and processes them through machine learning models to generate appropriate AI responses, substituting mechanical control with biological signal processing
2Adaptability or versatility
If biosensors and multimodal processing are integrated to enable AI-assisted conversation for impaired users, then accessibility and communication capability are improved, but system complexity increases
Solution Approach 1:
The patent creates a multi-functional integrated system where a single platform performs multiple functions: biosignal acquisition, physiological signal processing, natural language generation, and AI conversation management. This universal system serves diverse user needs (speech-impaired, mobility-impaired, cognitively challenged) and multiple interaction modes through one cohesive architecture, reducing the need for separate specialized systems
Solution Approach 2:
The patent merges previously separate components (biosensors, perception engines, language models, and AI conversation systems) into an integrated unified system. The biosensors are combined with machine learning models that process physiological data, which is then fed to language models for natural language generation, all managed within a single AI conversation framework, creating a streamlined multi-component system
Data Source
AI summary
A system and method for AI-assisted conversation utilize a biosensor to receive biosignals, which are analyzed by the perception engine. The engine generates context tags and text descriptions from multimodal sensory inputs and biosignal analysis. This information is then used by the conversation engine, along with memory engine data (conversation history, biographical background, keywords), to generate prompts for a language model. These prompts are displayed to a user through a computing device that presents various conversation features like communication history, context data, and selected content. The system enables interactive AI-assisted conversations between humans and machines or other humans.