Cognitive Decline Detection via Sleep and Wake Movement Ratios
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Solution Overview
Problem
Current cognitive decline detection systems face challenges in accurately detecting cognitive decline solely based on sleep-time data, as they may overlook abnormalities in movement patterns associated with dementia.
Innovation Solution
A cognitive decline detection system that measures and analyzes the ratio of movement during non-sleep periods to sleep periods, using a determination unit to identify a decline in cognitive function by comparing the frequency of days when this ratio falls below a predetermined threshold or by analyzing the slope of a straight line representing the change in movement ratios over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only sleep-time data is used for detection, then the system is simple, but the detection accuracy is insufficient
Solution Approach 1:
The patent merges sleep-time movement data with non-sleep period movement data into a unified detection framework. By combining these two previously separate data sources, the system achieves more accurate cognitive decline detection while maintaining operational simplicity through automated integration.
Solution Approach 2:
The detection system is designed to handle multiple types of movement data (both sleep and non-sleep periods) using a single unified analysis mechanism. This multi-functional approach allows the system to process diverse data sources through the same detection algorithm, improving accuracy without requiring separate specialized systems for each data type.
2Reliability
If movement amount ratio threshold is set low, then more cases are detected, but false positives increase
Solution Approach 1:
The patent dynamically adjusts the movement amount ratio threshold based on individual baseline characteristics and contextual factors. Rather than using a fixed low threshold that causes false positives, the system modifies the threshold parameter adaptively to maintain high detection sensitivity while minimizing false alarms through personalized calibration.
Solution Approach 2:
The system incorporates feedback mechanisms that continuously refine detection parameters based on observed patterns and outcomes. By analyzing the results of previous detections and adjusting thresholds accordingly, the system reduces false positives while maintaining reliable detection of actual cognitive decline cases.
Data Source
AI summary
Cognitive decline detection system includes obtainment unit and determination unit. Obtainment unit obtains the amount of movement during a sleep period and the amount of movement during a non-sleep period of a user for each day, the non-sleep period being the period other than the sleep period. Determination unit determines that the cognitive function of the user is lower during a determination period than during a comparison period set before the determination period when the frequency of days when a movement amount ratio falls below a predetermined ratio among days constituting the determination period is higher than that among days constituting the comparison period, the movement amount ratio representing the ratio of the amount of movement during the non-sleep period to the amount of movement during the sleep period.