Neural Network Dementia Behavior Detection for Caregiver Support
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Solution Overview
Problem
Existing systems fail to adequately support caregivers in providing appropriate assistance to individuals with dementia by digitizing their intuition or tacit knowledge, leading to inconsistent and potentially inadequate care.
Innovation Solution
An information processing device and method that utilizes a neural network to determine abnormal behaviors in dementia patients based on dementia level, environmental, excretion, and sleep information, and outputs support information to caregivers for effective assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional systems are used without machine learning, then the system complexity is low, but the measurement precision of abnormal behavior detection is insufficient
Solution Approach 1:
A neural network model serves as an intermediary between raw sensor data and behavior determination. The model processes multiple types of data (sensor information, care information, behavioral information) and outputs determined behavioral information that indicates abnormal behaviors. This intermediary layer enables precise detection without requiring complex manual analysis systems.
Solution Approach 2:
The system creates a digital model (neural network) that copies and learns from expert caregiver knowledge and medical expertise. By training the neural network with labeled data representing normal and abnormal behaviors, the system captures expert judgment patterns and applies them automatically, achieving high detection precision without replicating the full complexity of human expertise.
2Reliability
If multiple types of information are collected and processed, then the reliability of behavior determination is improved, but the loss of time for data processing increases
Solution Approach 1:
The neural network model is trained in advance with large amounts of labeled behavioral data before deployment. This preliminary training action enables the model to quickly process new data without requiring extensive computation at runtime. The system performs the heavy processing work beforehand, allowing rapid real-time determination of abnormal behaviors when actual sensor data is collected.
3Productivity
If comprehensive sensor information is collected, then the productivity of care support is improved, but the device complexity increases
Solution Approach 1:
The neural network model is designed to process multiple types of input data (sensor information, care information, behavioral information) through a unified architecture. This multi-functional processing capability allows the system to handle diverse data sources without requiring separate specialized systems for each data type, improving care support productivity while managing device complexity through consolidation.
Data Source
AI summary
The information processing device includes a factor determination unit configured to determine whether the behavior of an assisted person is an abnormal behavior of a dementia factor based on (1) information on a dementia level of the assisted person and (2) at least one of an environmental information, an excretion information, and a sleep information of the assisted person, and a support information output unit configured to output the support information to support an assistance of the assisted person by a caregiver based on the determination result of the factor determination unit and sensor information that is a sensing result about the assisted person or the caregiver assisting the assisted person.