IHS Posture Detection via Segmented Image Analysis
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Solution Overview
Problem
Prolonged use of Information Handling Systems (IHS) without ergonomic breaks can lead to physical and psychological harm due to non-ergonomic postures, and existing solutions do not effectively assess and mitigate these risks in varying user environments.
Innovation Solution
Integration of cameras and time-of-flight sensors in IHS to generate two- and three-dimensional images of users, classify their posture relative to known environments, and calculate an ergonomic risk score using the Rapid Upper Limb Assessment (RULA) system, scaling the score based on the probability of ergonomic posture in different settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users operate IHS for long intervals without breaks, then productivity increases, but physical harm occurs due to non-ergonomic postures
Solution Approach 1:
The system continuously monitors user posture through camera-based image processing and provides real-time feedback by calculating ergonomic risk scores. The system segments images to isolate the user, classifies physical environments, and generates feedback loops that alert users when non-ergonomic postures are detected, enabling corrective action without interrupting productivity
Solution Approach 2:
The patent replaces traditional mechanical posture monitoring devices with optical sensing systems (cameras and image processing). Instead of mechanical sensors attached to the user, the system uses computer vision to detect posture, segment images to isolate the user from the environment, and analyze spatial relationships to assess ergonomic risk
2Object-affected harmful factors
If existing solutions assess ergonomic posture, then physical harm is mitigated, but they fail to account for varying user environments
Solution Approach 1:
The system segments the captured image into multiple components: user region, physical environment region, and background. This segmentation allows independent analysis of user posture and environmental context. The physical environment is further classified into known categories (e.g., office, home, public space) with associated ergonomic probability profiles, enabling environment-specific risk assessment
Solution Approach 2:
The system dynamically adjusts ergonomic risk assessment parameters based on classified physical environments. Each environment type has associated probability values that modify the base ergonomic risk score. The system changes assessment sensitivity and thresholds according to environmental context, recognizing that acceptable postures may vary by setting (e.g., standing at a kitchen counter vs. sitting at an office desk)
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
Effectively monitors and mitigates ergonomic risks by providing users with real-time feedback on their posture, reducing the likelihood of physical strain and improving ergonomic positioning during prolonged IHS use across various environments.
Implementation Method 1
utilize a time-of-flight sensor of the IHS to generate a three-dimensional image of the user
Implementation Method 2
utilize the one or more cameras of the IHS to generate a two-dimensional image of a user of the IHS and of a portion of the physical environment
Data Source
AI summary
Systems and methods detect the posture of a user of an IHS (Information Handling System). An image is generated of a user and of the physical environment in which the user is operating the IHS. The image is processed to generate segregated images of the user and of the physical environment. The segregated image of the physical environment is classified as corresponding to a known environment in which the user has operated the IHS and that is associated with a probability of an ergonomic posture being used while in that particular environment. The segregated image of the user is processed to determine a physical posture of the user relative to the IHS. An ergonomic risk score is generated based on deviations of the user's posture from an ideal posture. The ergonomic risk score is scaled based on the probability of an ergonomic posture being used, due to the environment.