Home Sensor Fusion for Detecting Cognitive Decline Patterns
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Solution Overview
Problem
Individuals with cognitive or health conditions may develop subtle signs that make it difficult for caregivers to determine their ability to live independently, as these conditions often develop slowly over time.
Innovation Solution
A system utilizing sensors in a home environment to capture data, analyze it for abnormalities or anomalies, and generate notifications to caregivers about potential conditions, potentially using machine learning to identify patterns and predict future conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are deployed to capture comprehensive data, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple sensor types (motion sensors, temperature sensors, humidity sensors, light sensors) into an integrated sensing system that operates as a unified whole. The sensor network is managed through a single processing unit that coordinates data collection from all sensors, merging their functions to detect cognitive conditions without requiring separate complex systems for each sensor type.
Solution Approach 2:
The processing unit serves multiple functions: it collects data from all sensor types, analyzes the data for abnormalities, identifies conditions, and generates notifications. This multi-functional design reduces overall system complexity by consolidating what would otherwise require separate dedicated components for each task.
2Productivity
If real-time data analysis is performed to identify conditions quickly, then productivity is improved, but use of energy increases
Solution Approach 1:
The system performs data analysis periodically rather than continuously. The processing unit analyzes sensor data at scheduled intervals to identify abnormalities and conditions, which reduces energy consumption compared to constant real-time processing while still maintaining timely detection of changes in an individual's condition.
Solution Approach 2:
The system uses the individual's own environmental data (sensor readings from their home) to monitor their condition, eliminating the need for external continuous monitoring equipment that would consume additional energy. The existing sensor infrastructure serves the dual purpose of environmental monitoring and health condition detection.
Data Source
AI summary
Systems and methods for identifying a condition associated with an individual in a home environment are provided. Sensors associated with the home environment detect data, which is captured and analyzed by a local or remote processor to identify the condition. In some instances, the sensors are configured to capture data indicative of electricity use by devices associated with the home environment, including, e.g., which devices are using electricity, what date/time electricity is used by each device, how long each device uses electricity, and/or the power source for the electricity used by each device. The processor analyzes the captured data to identify any abnormalities or anomalies, and, based upon any identified abnormalities or anomalies, the processor determines a condition (e.g., a medical condition) associated with an individual in the home environment. The processor generates and transmits a notification indicating the condition associated with the individual to a caregiver of the individual.