Fall Detection System Using Acceleration and Orientation Sensors
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Solution Overview
Problem
Existing fall detection systems for firefighters and consumers take too long to enter full alarm mode after a fall event, often activate during non-fall situations, and fail to detect the type of fall or user orientation relative to a reference plane, which can lead to delayed assistance and diversion of attention during critical situations.
Innovation Solution
A fall detection system equipped with sensors to detect acceleration and orientation, a controller to analyze data for fall event parameters such as acceleration thresholds and orientation changes, and indicator devices for immediate alarm activation, eliminating pre-alarm periods and providing specific alerts based on fall types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing PASS devices use a pre-determined pre-alarm period before full alarm mode, then false alarms during routine operations are reduced, but the response time to actual fall events is delayed
Solution Approach 1:
The alarm detection process is segmented into multiple independent criteria: acceleration threshold detection, orientation change detection, and post-fall motion detection. Each criterion independently contributes to fall detection, allowing the system to eliminate the pre-alarm delay while maintaining reliability through multi-factor verification
Solution Approach 2:
The system changes from using a single time-based parameter (pre-alarm period duration) to using multiple physical parameters simultaneously (acceleration magnitude, orientation angles, post-fall motion characteristics). This parameter transformation enables immediate alarm activation upon detecting the specific pattern of a fall event
2Difficulty of detecting and measuring
If existing fall detection devices activate after detecting acceleration exceeding a pre-determined threshold, then fall events can be detected, but non-fall situations such as jumping from elevated positions cause false activations
Solution Approach 1:
The system merges multiple detection criteria into a unified fall detection algorithm: initial acceleration threshold detection, orientation change detection, and post-fall motion detection. All criteria must be satisfied simultaneously, combining their strengths while compensating for individual weaknesses to eliminate false activations
Solution Approach 2:
The system incorporates feedback from multiple sensors (accelerometer and orientation sensor) and multiple time periods (during fall and after impact). The post-fall motion detection provides feedback that confirms whether the user actually fell, allowing the system to distinguish between true fall events and non-fall situations
3Ease of operation
If existing devices are worn loosely on the user's body, then ease of wear is improved, but the ability to detect user orientation relative to a reference plane is lost
Solution Approach 1:
The system transitions from relying solely on acceleration magnitude (one-dimensional detection) to incorporating orientation angles relative to the ground (three-dimensional detection). This dimensional expansion allows the system to detect user orientation even when worn loosely, as orientation relative to gravity is independent of device position on the body
4Productivity
If existing PASS devices monitor movement using a 3-axis accelerometer and require no motion for 30 seconds total, then fall events are detected, but the system cannot differentiate between types of fall events or provide information about user distress
Solution Approach 1:
The system uses orientation angles as 'color codes' to characterize different fall types. By measuring the orientation of the user relative to the ground after impact, the system can categorize falls into different types (e.g., backward fall, sideways fall, forward fall) and provide this information through different alarm patterns or notifications
Solution Approach 2:
The system dynamically adapts its detection criteria based on the detected fall characteristics. After detecting an acceleration event and impact, the system transitions to monitoring post-fall motion and orientation, dynamically adjusting what it looks for based on the sequence of events rather than using a fixed detection algorithm
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 rapidly activates an alarm upon detecting a fall, differentiating between fall types and user orientations, ensuring timely assistance and minimizing attention diversion during emergency situations.
Implementation Method 1
at least one sensor configured to detect acceleration of a host
Implementation Method 2
at least one sensor configured to detect orientation of a host
Data Source
AI summary
A fall detection system includes at least one sensor configured to detect acceleration and orientation of a host, at least one indicator device having an alarm mode, and a controller operatively connected to the at least one sensor and the at least one indicator device. The controller is programmed to receive data generated by the at least one sensor, compare at least a portion of the received data with at least one specified parameter indicative of a fall event, and, based on the comparison, activating the at least one indicator device to enter the alarm mode. The at least one specified parameter includes at least one of the following: an acceleration exceeding a predetermined threshold, a change between a starting and a final orientation of the host before and after an acceleration event, a lack of movement of the host for a predetermined time after the acceleration event, or any combination thereof.