Automated Verbal Interface for Patient Qualitative Assessment
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Solution Overview
Problem
Current medical assessments, especially in telemedicine, face limitations due to the reliance on subjective observations and the need for trained professionals to administer qualitative assessments, which can be inconsistent and resource-intensive, limiting the ability to efficiently collect diagnostic data and prioritize patient care.
Innovation Solution
A system utilizing machine learning models and wearable sensors to objectively assess patients through physical actions and verbal responses, generating motion data and determining qualitative assessment scores, allowing for automated and standardized data collection without the need for a trained professional.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If trained professionals administer qualitative assessments in person, then assessment reliability is improved, but resource availability deteriorates due to limited medical professional availability
Solution Approach 1:
The system enables patients to perform self-assessments through automated verbal interfaces and motion tracking, eliminating the need for trained professionals to administer each assessment. Patients follow standardized protocols independently, maintaining consistency while freeing medical professionals for critical care tasks.
Solution Approach 2:
The patent replaces the mechanical system of human professional administration with an automated computational system using voice recognition, motion sensors, and machine learning algorithms to collect and evaluate assessment data objectively and consistently.
2Measurement precision
If trained professionals perform qualitative assessments, then measurement precision is improved, but productivity deteriorates due to limited capacity to serve patients
Solution Approach 1:
Patients independently complete assessments using automated guidance, allowing unlimited parallel processing of assessments without additional professional resources. The system maintains measurement precision through standardized protocols while dramatically increasing patient throughput capacity.
Solution Approach 2:
The assessment process is segmented into standardized, modular components that can be independently administered and evaluated. This segmentation allows the system to process multiple assessments simultaneously while maintaining consistent measurement precision through automated quality control.
3Ease of operation
If subjective observations are used for assessment, then ease of operation is improved, but measurement precision deteriorates due to observer variability
Solution Approach 1:
The system replaces subjective human observation with automated motion tracking sensors and voice recognition technology that objectively measure patient responses. This substitution eliminates observer variability while maintaining ease of operation through automated data collection and analysis.
Solution Approach 2:
The patent transforms subjective qualitative assessments into objective quantitative parameters through sensor measurements and automated analysis. By changing the measurement parameters from subjective ratings to objective sensor data, the system improves precision while keeping the assessment process simple for patients.
Data Source
AI summary
Using artificial intelligence and data observed using sensors or imaging devices to prompt a patient to provide responses or perform actions and then observing the patient's responses to the prompts and performing an assessment resulting in a quantitative result. The quantitative result is then used to complete a clinical qualitative assessment of the patient.