Thermal Sensor Depth Camera Fall Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing fall detection systems in institutional settings face challenges with false positives and false negatives, which can lead to delayed or inappropriate responses to patient falls, potentially worsening injuries and safety outcomes.
Innovation Solution
A system combining a depth camera and a thermal sensor, where the depth camera captures 3D point clouds and the thermal sensor differentiates between heat-emitting and non-heat-emitting objects, allowing for accurate detection of human falls by identifying heat signatures indicative of a human presence, thereby reducing false positives and negatives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a depth camera is used to detect falls by capturing 3D point clouds and identifying separation of portions, then fall detection capability is improved, but false positives occur when non-human objects are misidentified as falling patients
Solution Approach 1:
A thermal sensor is introduced as an intermediary device to work in conjunction with the depth camera. The thermal sensor captures thermal images that are processed to generate thermal point clouds, which serve as additional identifying characteristics. By combining depth information with thermal characteristics, the system can reliably distinguish between human patients and non-human objects, thereby reducing false positives while maintaining fall detection accuracy.
2Reliability
If thermal sensing is added to differentiate human falls from non-human objects, then false positive reduction is achieved, but device complexity increases
Solution Approach 1:
The system processes thermal image data by segmenting the thermal point cloud into multiple portions and comparing each portion against corresponding depth portions. This segmentation approach allows the system to evaluate identifying characteristics in a modular fashion, managing the increased complexity through systematic breakdown of the analysis process into discrete, manageable steps.
Solution Approach 2:
The monitoring system is designed to perform multiple functions using the same hardware components. The depth camera serves both fall detection and object identification purposes, while the thermal sensor provides both thermal imaging and additional identifying characteristics. This multi-functionality reduces the need for separate dedicated components, thereby limiting the increase in device complexity.
3Measurement precision
If multiple identifying characteristics are analyzed to confirm human presence, then detection accuracy is improved, but processing time increases
Solution Approach 1:
The system continuously captures and pre-processes thermal image data in the background, generating thermal point clouds and identifying characteristics before fall events occur. This preliminary action ensures that when a fall is detected by the depth camera, the thermal characteristics are already prepared and ready for immediate comparison, eliminating processing delays and maintaining rapid fall response time.
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 enhances the accuracy of fall detection by segregating human falls from non-human objects and reduces false alarms, ensuring timely and appropriate responses to patient falls, thereby mitigating injury risks and improving patient safety.
Implementation Method 1
the thermal sensor imaging heat emitted by the portion and the first point cloud
Data Source
AI summary
Systems and methods designed to detect a human being falling as opposed to an inanimate object. Generally, the systems and methods will utilize a depth camera, which will often image in the NIR spectrum to detect a falling object. The portion detected as a falling object will often be detected as separating from a point cloud indicative of one object in contact with another. Should such a separation be detected, the systems and methods will utilize a thermal sensor, often a camera imaging in the LWIR spectrum, to determine if the falling portion has a heat signature indicative of a human being.