AI Assistant Ambient Audio Cognitive Decline Detection

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Solution Overview

Problem

Existing assistive call systems require active user input or distress triggers, failing to detect gradual cognitive decline or other subtle health changes in patients over time, as they typically exclude ambient audio not related to human speech and lack continuous monitoring capabilities.

Innovation Solution

An AI assistant device captures and analyzes ambient audio to build a language tracking model, detecting changes in speech patterns and generating condition notifications, enabling passive monitoring of patients' cognitive health and health conditions without requiring explicit user cues.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If active call response systems are used, then user control over monitoring is improved, but ability to detect gradual cognitive decline is worsened

Engineering Contradiction:

Improveuser controlVSAvoiddetection of gradual cognitive decline

Core Design Contradiction:

Ease of operationVSDifficulty of detecting and measuring

Solution Approach 1:

The system continuously captures and analyzes ambient audio in the background, maintaining constant monitoring without requiring user activation. This continuous operation enables detection of subtle speech pattern changes that indicate gradual cognitive decline, while the system remains dormant until needed, preserving user control when active.

Inventive Principle:

Principle #20Continuity of useful action

2Reliability

If vital sign monitoring is used, then emergency detection is improved, but detection of subtle health changes over time is worsened

Engineering Contradiction:

Improveemergency detectionVSAvoiddetection of subtle health changes

Core Design Contradiction:

ReliabilityVSMeasurement precision

Solution Approach 1:

The system replaces mechanical/vital sign monitoring with acoustic field analysis. By capturing ambient audio and analyzing speech patterns, tone, and language usage, the system detects subtle cognitive and health changes that vital sign monitors cannot detect, while maintaining reliability for emergency situations through continuous monitoring.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Duration of action of moving object

If ambient audio analysis is implemented, then continuous monitoring is improved, but device complexity is worsened

Engineering Contradiction:

Improvecontinuous monitoringVSAvoidsystem complexity

Core Design Contradiction:

Duration of action of moving objectVSDevice complexity

Solution Approach 1:

The system uses a multi-functional approach where a single AI assistant device performs multiple tasks: capturing ambient audio for various purposes, analyzing speech patterns for cognitive health monitoring, detecting emergency situations, and providing user interactions. This consolidation of functions into one device enables continuous monitoring without proportionally increasing complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20230317274A1Patient monitoring using artificial intelligence assistants

Publication Date: 2023.10.05 MATRIXCARE INC

AI summary

Embodiments herein include methods and a device to track and monitor a patient's condition over time to detect a change in a patient condition (including cognitive decline) using personal artificial intelligence (AI) assistants. The present embodiments improve upon the base functionalities of the assistant devices by using engaging with a monitored patient and tracking changes in a patient condition overtime using various learning models to detect changes in the patient's speech, mood, and other conditions.