Sensor-Triggered Imaging for Fall Detection
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Solution Overview
Problem
Existing monitoring systems in medical and nursing facilities face challenges in efficiently detecting falls and head injuries in patients, as they rely on cardiac potential and acceleration data, which may not accurately determine if a patient has fallen or hit their head, and continuous image recording imposes a heavy burden on users.
Innovation Solution
A monitoring system that includes a sensor data acquisition unit for activity information, a data analysis unit to detect abnormalities, an imaging control unit to instruct a camera to capture images upon detecting an abnormality, and an imaging data acquisition unit to store and output the recorded images, focusing on reducing user burden by only capturing and storing relevant data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a monitoring camera constantly captures images to accurately detect falls and head injuries, then detection reliability is improved, but user burden and data storage requirements increase
Solution Approach 1:
The system pre-processes sensor data (acceleration, cardiac potential) to detect abnormal patterns indicating falls or head injuries before triggering image capture. This preliminary detection action ensures that images are only captured when necessary, maintaining high detection reliability while avoiding continuous monitoring burden on users
Solution Approach 2:
Sensor data (acceleration sensors and cardiac potential monitors) serve as intermediaries between the user and the imaging system. These sensors continuously monitor physical parameters and trigger image capture only when abnormal patterns are detected, eliminating the need for constant camera operation and reducing user burden while maintaining reliable fall and injury detection
2Measurement precision
If a monitoring camera constantly records imaging data to ensure accurate detection, then detection precision is improved, but data storage requirements and processing burden increase
Solution Approach 1:
The system extracts only the essential information needed for fall and injury detection from sensor data (acceleration patterns, cardiac potential changes). By taking out only the critical detection triggers rather than processing all raw sensor data continuously, the system achieves high detection precision while minimizing the volume of imaging data that needs to be stored and processed
Solution Approach 2:
Instead of continuously capturing images, the system applies partial action by capturing images only during specific abnormal events detected by sensor analysis. This selective image capture provides sufficient detection precision for falls and head injuries while dramatically reducing the total quantity of imaging data generated and requiring storage
3Device complexity
If sensor data alone is used to detect falls, then device complexity is reduced, but detection accuracy deteriorates
Solution Approach 1:
The system merges multiple sensor types (acceleration sensors and cardiac potential monitors) into a unified detection framework. By combining data from these different sensor modalities, the system maintains relatively simple device architecture while significantly improving detection accuracy for falls and head injuries through multi-parameter analysis
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively detects falls and head injuries with reduced user burden by capturing and storing only necessary imaging data, allowing for timely notification and appropriate care.
Implementation Method 1
information on the user's activity including an acceleration of the user
Data Source
AI summary
A monitoring system includes a sensor data acquisition device configured to acquire information on an activity of a user; a data analyzer configured to analyze the acquired information on the activity of the user and detect occurrence of an abnormality in the activity of the user; an imaging controller configured to instruct an imaging terminal device that captures an image of the activity of the user to start capturing an image of the user and record imaging data in a case where the occurrence of the abnormality is detected by the data analyzer; an imaging data acquisition device configured to acquire the imaging data recorded by the imaging terminal device; a data storage device configured to store the imaging data acquired by the imaging data acquisition device; and an output device configured to output the imaging data.