Radar Posture Tracking for Early Fall Risk Detection
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Solution Overview
Problem
Existing methods for fall prevention in elderly individuals, especially in private environments, are inadequate as they either restrict movement or rely on unreliable human intervention, failing to provide timely assistance for those who cannot request help.
Innovation Solution
A method and system using radar measurements to determine a person's posture by processing two-dimensional point cloud data, clustering, and tracking body parts to identify positional relationships, allowing for early detection of fall risks without restricting movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical restrictions (bed bars, wheelchair bars) are used for fall prevention, then fall protection is improved, but freedom of movement is worsened
Solution Approach 1:
The patent replaces mechanical restriction systems (bed bars, wheelchair bars) with a radar-based detection system. The radar system non-invasively monitors posture and fall risk without physical contact, eliminating the need for mechanical constraints while maintaining fall protection through early detection and alerting caregivers.
2Ease of operation
If automated sensor systems are implemented for fall detection, then freedom of movement is improved, but system complexity is worsened
Solution Approach 1:
The patent extracts and processes only the most critical information from radar measurements - specifically posture data and fall risk indicators. By focusing on key features (body position, movement patterns) rather than processing all raw sensor data, the system reduces computational complexity while maintaining effective fall detection capability.
3Device complexity
If human intervention is relied upon for fall prevention, then simplicity is improved, but reliability is worsened for cognitively impaired individuals
Solution Approach 1:
The radar system autonomously monitors individuals without requiring their active participation or cognitive understanding. It automatically detects posture changes and fall risks, providing continuous monitoring that works reliably for cognitively impaired individuals who cannot request or understand fall prevention interventions.
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
Enables reliable fall prevention by detecting early warning signs of balance loss or transition movements, reducing the risk of falls without limiting freedom, and providing timely assistance to confused or cognitively impaired individuals.
Implementation Method 1
obtaining measurement data from at least two dimensional radar measurements
Data Source
AI summary
In a method for determining a posture of a human being, in particular for fall prevention, measurement data is obtained from at least two dimensional radar measurements of a radar system. The measurement data is processed to obtain at least two dimensional point cloud data, in particular three dimensional point cloud data, wherein a position and local data is assigned to each of the points of the point cloud data. The point cloud data is clustered to obtain clustered data representing the human being by a plurality of clusters, and the clusters are tracked over time to define a plurality of objects. Body parts of the human being and positional relationships among them are identified based on the plurality of objects, wherein the identified body parts comprise the head and/or limbs, and the positional relationships are analyzed to determine the posture of the human being.