Platform Lift Usage Pattern Detection for Caregiver Alerts
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing platform lifts do not adequately differentiate between users and provide alerts when a user deviates from their typical usage patterns, potentially leading to unsafe situations.
Innovation Solution
Implement a method to determine the way of usage of a platform lift, compare it to predefined alert definitions, and generate alerts if the usage does not conform, using user inputs or self-learning algorithms, with alerts sent to a secondary user via a mobile device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a platform lift is used to transport impaired mobility users, then the users can move between floors safely, but there is no mechanism to detect unusual usage patterns or alert caregivers of potential emergencies
Solution Approach 1:
The system continuously monitors usage patterns and provides feedback by comparing actual usage against learned normal patterns. When deviations are detected, the system generates alerts to caregivers, creating a closed-loop safety mechanism that maintains reliability without requiring complex manual monitoring
Solution Approach 2:
The system performs self-learning of usage patterns automatically over time, adapting to each user's individual habits without requiring manual programming or configuration. This self-service capability reduces the complexity burden on users and caregivers while maintaining high reliability through personalized monitoring
2Reliability
If the system monitors usage patterns continuously, then unusual situations can be detected early, but this increases the processing requirements and system complexity
Solution Approach 1:
The system applies partial monitoring by focusing only on the most critical usage parameters (seat position, movement patterns, timing) rather than attempting to monitor every possible variable. This selective approach maintains detection accuracy while reducing processing complexity to manageable levels
Solution Approach 2:
The system performs preliminary learning of normal usage patterns during an initial period before full monitoring begins. This preliminary action establishes a baseline that simplifies subsequent detection operations, reducing the computational burden during actual monitoring phases
3Reliability
If alerts are generated for all usage deviations, then no safety issue is missed, but false alarms increase and reduce system effectiveness
Solution Approach 1:
The system applies different alert thresholds and monitoring strictness to different usage parameters. Critical parameters (e.g., unexpected stops, abnormal seat positions) trigger alerts more readily, while less critical variations tolerate more flexibility. This localized quality approach maintains comprehensive safety coverage while reducing false alarms from minor deviations
Data Source
AI summary
The present disclosure for raising an alert in connection with the use of a platform lift, in particular a stairlift, the lift havinga rail,a drive unit having a platform, a chair (8), for driving along the rail,at least one control unit arranged at the drive unit. The method including determining the way of usage of the platform lift, comparing the way of usage with an alert definition, determining whether the way of usage confirms with the alert definition, determining whether the way of usage confirms with the alert definition, generating an alert, if the way of usage conforms to the alert definition and providing the alert to a user.