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Detection and classification methodology for movements in the bed that supports continuous pressure injury risk
Jonathan Duvall1, Patricia Karg1, David Brienza1
1University of Pittsburgh, Department of Rehabilitation Science and Technology, 6425 Penn Ave, Suite 401, Pittsburgh, PA, 15206, USA.
Insights
The E-scale, a bed monitoring system, accurately detects and classifies patient movements relevant to preventing costly pressure injuries. This technology can prompt care teams for timely interventions, improving patient outcomes.
Area of Science:
- Biomedical Engineering
- Clinical Nursing
- Healthcare Technology
Background:
- Pressure injuries represent a significant financial burden on healthcare systems and are largely preventable, yet their incidence remains high.
- Current recommendations emphasize continuous monitoring and care team prompts for effective pressure injury prevention.
- Existing monitoring systems may not adequately capture patient movement crucial for risk assessment.
Purpose of the Study:
- To evaluate the feasibility of the E-scale bed weight monitoring system for detecting and classifying patient movements.
- To assess the E-scale's potential role in pressure injury risk assessment and prevention strategies.
- To determine the accuracy of a threshold-based algorithm and K-nearest neighbor classification for movement analysis.
Main Methods:
- Utilized the E-scale, a system employing load cells under bed legs to monitor weight distribution and detect movement.
- Implemented a threshold-based detection algorithm to identify movement events.
- Employed a K-nearest neighbor classification approach to categorize different types of patient movements in bed.
Main Results:
- The E-scale system demonstrated high accuracy (>94%) in detecting and classifying four distinct movement types: rolls, turns in place, extremity movements, and assisted turns.
- The system proved effective in differentiating various patient repositioning activities.
- Movement data captured by the E-scale is relevant for pressure injury risk stratification.
Conclusions:
- The E-scale system is a feasible tool for monitoring patient movements in bed, offering valuable data for pressure injury prevention.
- This technology can serve as a prompt for healthcare providers, enabling timely interventions to mitigate pressure injury risk.
- The E-scale supports further research into the efficacy of different care plans and repositioning protocols for pressure injury management.
Abstract:
Pressure injuries are costly to the healthcare system and mostly preventable, yet incidence rates remain high. Recommendations for improved care and prevention of pressure injuries from the Joint Commission revolve around continuous monitoring of prevention protocols and prompts for the care team. The E-scale is a bed weight monitoring system with load cells placed under the legs of a bed. This study investigated the feasibility of the E-scale system for detecting and classifying movements in bed which are relevant for pressure injury risk assessment using a threshold-based detection algorithm and a K-nearest neighbor classification approach. The E-scale was able to detect and classify four types of movements (rolls, turns in place, extremity movements and assisted turns) with >94% accuracy. This analysis showed that the E-scale could be used to monitor movements in bed, which could be used to prompt the care team when interventions are needed and support research investigating the effectiveness of care plans.
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