Monitoring System with Image Projection for Mood Response
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Solution Overview
Problem
Existing camera-based monitoring systems for individuals, such as infants or those with ambulatory and communication deficits, do not effectively detect eye gaze direction or determine when additional attention is required, limiting their ability to provide nuanced care or respond to the person's interests.
Innovation Solution
A monitoring system that incorporates a camera system with an image projector, a visual object library, and a preference tracking data structure, which detects eye gaze direction and facial expressions to project images of interest to the person, thereby responding to their mood and attention cues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the caregiver uses a remote monitoring system to attend to other activities, then the caregiver's productivity is improved, but the caregiver cannot scrutinize the video to understand the nuances of the person's state
Solution Approach 1:
The system introduces an intermediary intelligence (automated monitoring system with AI analysis) that acts as a mediator between the person being monitored and the caregiver. This intermediary continuously analyzes video feeds, detects facial expressions, eye gaze direction, and objects of interest, then selectively notifies the caregiver only when significant events occur or when the person shows signs of distress or boredom. This allows the caregiver to maintain productivity while the system preserves critical nuanced information about the person's state.
Solution Approach 2:
The monitoring system performs self-service by autonomously analyzing video content, detecting facial expressions, tracking eye gaze, identifying objects of interest, and determining when caregiver intervention is needed. The system independently processes the video stream, applies computer vision algorithms, and generates notifications without requiring continuous caregiver attention, thereby enabling the caregiver to attend to other activities while maintaining monitoring effectiveness.
2Reliability
If the monitoring system provides continuous video output, then the caregiver can monitor the person, but the system does not provide information about objects of interest to the person
Solution Approach 1:
The system extracts specific meaningful information from the continuous video stream by isolating and identifying objects of interest that capture the person's attention. Using computer vision and image recognition, the system detects and tracks objects within the field of view, determines which objects the person is looking at based on eye gaze direction, and extracts this information separately from the full video feed. This extracted object interest information is then provided to the caregiver through notifications or a separate interface, complementing the continuous monitoring capability.
3Adaptability or versatility
If the system detects facial expressions and eye gaze direction, then the system can respond to the person's mood, but the device complexity increases
Solution Approach 1:
The monitoring system achieves multi-functionality by integrating multiple capabilities into a single unified platform: video capture, facial expression recognition, eye gaze direction detection, object identification, and adaptive response generation. Rather than using separate specialized devices for each function, the system employs a single camera system with integrated computer vision processing that simultaneously performs all these tasks. This universal approach increases adaptability to the person's mood and needs while managing device complexity through consolidation rather than proliferation of components.
Data Source
AI summary
A monitoring system incorporates, and a method and a computer program product provide image projection of content of subjective interest to a person, responsive to a detected mood of the person. A controller of the monitoring system receives image stream(s) from a camera system, including a first image stream encompassing a face of a person. The controller compares facial expressions within the first image stream with facial expression trigger(s) in a visual object library. In response to determining that the first image stream includes facial expression trigger(s) among the visual object library, the controller determines one or more objects in the visual object library having an associated interest value, in a preference tracking data structure, above a threshold soothing value corresponding to the person. The controller triggers an image projector to present the object(s) within the field of view of the person to respond to the facial expression trigger.