Dynamic Home Themes With Sensor-Based AI for Early Condition Detection
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Solution Overview
Problem
There is a lack of resources and trained healthcare providers for early detection and treatment of disorders like depression and dementia, leading to inaccurate assessments and insufficient treatment, despite advancements in technologies like image processing in cancer diagnosis.
Innovation Solution
A system utilizing sensors, AI/ML models, and environmental stimulators to detect anomalies, associate conditions with treatments, and adapt the environment to mitigate symptoms, offering privacy-preserving solutions for early detection and treatment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional healthcare resources and trained providers are used for early detection and treatment, then accurate assessments can be achieved, but resource availability and scalability are limited
Solution Approach 1:
The patent creates virtual copies of healthcare providers through AI/ML models that analyze sensor data and provide diagnostic assessments. These digital twins can process multiple patient datasets simultaneously, multiplying the effective capacity of limited healthcare providers while maintaining assessment quality through algorithmic consistency and pattern recognition capabilities.
Solution Approach 2:
The patent replaces manual healthcare provider assessments with automated sensor-based monitoring systems. Sensors continuously collect physiological and behavioral data, and AI algorithms automatically analyze this data to detect anomalies and generate assessments, eliminating the need for constant human intervention while improving both scalability and consistency of care.
2Measurement precision
If advanced technologies like image processing are deployed, then diagnostic capability improves, but system complexity and infrastructure requirements increase
Solution Approach 1:
The patent employs multi-functional sensor arrays that can detect various physiological parameters (movement, temperature, sound, light) using a single integrated system. This universal sensing platform replaces multiple specialized devices, reducing infrastructure complexity while maintaining comprehensive diagnostic capability through a unified data collection framework.
Solution Approach 2:
The patent introduces AI/ML models as intermediary layers between raw sensor data and clinical decisions. These intermediaries process complex sensor inputs, extract meaningful patterns, and present simplified diagnostic recommendations to healthcare providers, thereby managing system complexity while enhancing diagnostic precision through algorithmic analysis.
3Measurement precision
If continuous monitoring is implemented, then early detection accuracy improves, but energy consumption and data processing requirements increase
Solution Approach 1:
The patent implements periodic sampling of sensor data rather than continuous monitoring. The system collects physiological and behavioral data at strategically determined intervals based on risk factors and detected anomaly patterns, maintaining early detection accuracy by focusing intensive monitoring on high-risk periods while reducing overall energy consumption during stable states.
Solution Approach 2:
The patent employs feedback mechanisms where the system learns from detected anomalies and adjusts its monitoring intensity accordingly. When anomalies are detected, the system increases monitoring frequency to confirm and track the anomaly; when no anomalies are present, it reduces monitoring intensity, thereby optimizing energy consumption while maintaining detection sensitivity through adaptive resource allocation.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, obtaining sensor data from a group of sensors arranged within an environment, the sensor data including observations of an individual. The sensor data is analyzed to obtain an analysis result and a condition of the individual is detected according to the analysis result. A treatment is associated with the condition and an environmental theme applied to the environment according to the treatment. Other embodiments are disclosed.