ArticleSensors (Basel, Switzerland)2016
Effectiveness of a Batteryless and Wireless Wearable Sensor System for Identifying Bed and Chair Exits in Healthy Older People.
Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Nurses' Perspectives and Experiences of Using a Bed-Exit Information System in an Acute Hospital Setting: Mixed Methods Study.JMIR formative research · 2025Article
- Analysis of Hospital Safety and Risk of Falls in the Elderly: A Cross-Sectional Study in Brazil.International journal of environmental research and public health · 2024Article
- Non-redundant implicational base of formal context with constraints using SAT.PeerJ. Computer science · 2024Article
- Risk of Falling in a Timed Up and Go Test Using an UWB Radar and an Instrumented Insole.Sensors (Basel, Switzerland) · 2021Article
- Step by Step Towards Effective Human Activity Recognition: A Balance between Energy Consumption and Latency in Health and Wellbeing Applications.Sensors (Basel, Switzerland) · 2019Review
- Energy-Efficient Elderly Fall Detection System Based on Power Reduction and Wireless Power Transfer.Sensors (Basel, Switzerland) · 2019Article
- Alarming and/or Alerting Device Effectiveness in Reducing Falls in Long-Term Care (LTC) Facilities? A Systematic Review.Healthcare (Basel, Switzerland) · 2019Article
- Novel Hierarchical Fall Detection Algorithm Using a Multiphase Fall Model.Sensors (Basel, Switzerland) · 2017Article
- A battery-less and wireless wearable sensor system for identifying bed and chair exits in a pilot trial in hospitalized older people.PloS one · 2017Article
- A Wireless and Batteryless Intelligent Carbon Monoxide Sensor.Sensors (Basel, Switzerland) · 2016Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aging populations are increasing worldwide and strategies to minimize the impact of falls on older people need to be examined. Falls in hospitals are common and current hospital technological implementations use localized sensors on beds and chairs to alert caregivers of unsupervised patient ambulations; however, such systems have high false alarm rates. We investigate the recognition of bed and chair exits in real-time using a wireless wearable sensor worn by healthy older volunteers. Fourteen healthy older participants joined in supervised trials. They wore a batteryless, lightweight and wireless sensor over their attire and performed a set of broadly scripted activities. We developed a movement monitoring approach for the recognition of bed and chair exits based on a machine learning activity predictor. We investigated the effectiveness of our approach in generating bed and chair exit alerts in two possible clinical deployments (Room 1 and Room 2). The system obtained recall results above 93% (Room 2) and 94% (Room 1) for bed and chair exits, respectively. Precision was >78% and 67%, respectively, while F-score was >84% and 77% for bed and chair exits, respectively. This system has potential for real-time monitoring but further research in the final target population of older people is necessary.
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