Fall Detection Algorithm Using Gravity Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing fall detection devices face challenges in accurately distinguishing falls from other movements, leading to false alarms and high electrical consumption, particularly when worn by elderly individuals who often experience falls in water-prone environments like bathrooms, and require a compact, discreet, and cost-effective solution.
Innovation Solution
A method using a three-axis accelerometer to classify user behavior by extracting the gravity component from acceleration measurements, employing a Markov chain and hidden-state Markov automaton to differentiate between normal and abnormal activities, and triggering alerts only when confident of a fall, thereby reducing false alarms and conserving energy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors (shock sensors, inertial units, temperature sensors) are added to improve fall detection accuracy, then measurement precision improves, but device complexity and cost increase
Solution Approach 1:
The patent extracts only the necessary gravitational component from accelerometer measurements using signal processing algorithms, rather than adding multiple sensors. This isolates the useful information (gravity vector) from noise and irrelevant movements, achieving accurate fall detection with a single accelerometer.
Solution Approach 2:
The patent replaces mechanical sensor systems (multiple physical sensors) with a computational approach using signal processing algorithms. The system substitutes hardware complexity with software intelligence to distinguish falls from normal movements.
2Reliability
If multiple sensors are added to reduce false alarms, then reliability improves, but electrical energy consumption increases
Solution Approach 1:
The patent extracts the gravitational component from accelerometer data through signal processing, enabling reliable fall detection without continuously processing all sensor data. This selective extraction reduces computational energy consumption while maintaining detection reliability.
Solution Approach 2:
The system processes accelerometer data periodically rather than continuously, analyzing measurements at specific intervals to detect falls. This periodic processing significantly reduces electrical energy consumption compared to continuous monitoring, extending battery life while maintaining reliable detection.
3Ease of operation
If the device is made more compact and discreet, then ease of operation improves, but measurement precision may deteriorate
Solution Approach 1:
The patent uses sophisticated signal processing algorithms to compensate for the limitations of a compact wrist-worn device. The computational methods extract gravitational information accurately despite the small form factor and limited sensor capabilities, maintaining detection precision while enabling discreet wear.
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 method achieves reliable fall detection with reduced false alarms and extended battery life, ensuring the device remains functional for over a year with minimal power, making it suitable for continuous wear without compromising discretion or size.
Implementation Method 1
The sensor adopted by most prior art devices for fall detection is the accelerometer for measuring shocks and movements
Implementation Method 2
it is planned to extract the gravity component from the total acceleration in order to know the dynamic acceleration, called clean, undergone by the wearer
Data Source
AI summary
The method involves classifying characteristics of a user from user's activity indicators obtained from acceleration measurements acquired by an accelerometer (20) i.e. three-axis accelerometer, of a fall detection device (10), where the device is in the form of pendant, wrist-watch strap or belt. Actuation of an electromagnetic or radiofrequency alarm signal is delayed so as to avoid false alarms, where the signal is sent from a transmission unit (18) via a base connected to a telecommunication network e.g. Internet or global system for mobile communication (GSM) network. An independent claim is also included for a user fall detection device comprising a case enclosing a supply unit.