ArticleSensors (Basel, Switzerland)2018
On the Comparison of Wearable Sensor Data Fusion to a Single Sensor Machine Learning Technique in Fall Detection.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Human motion data expansion from arbitrary sparse sensors with shallow recurrent decoders.bioRxiv : the preprint server for biology · 2024Article
- Bedtime Monitoring for Fall Detection and Prevention in Older Adults.International journal of environmental research and public health · 2022Article
- Control of a Drone in Virtual Reality Using MEMS Sensor Technology and Machine Learning.Micromachines · 2022Article
- Smart Healthcare System for Severity Prediction and Critical Tasks Management of COVID-19 Patients in IoT-Fog Computing Environments.Computational intelligence and neuroscience · 2022Article
- Human Behavior Recognition Model Based on Feature and Classifier Selection.Sensors (Basel, Switzerland) · 2021Article
- Smart homes for the older population: particularly important during the COVID-19 outbreak.Reumatologia · 2021Review
- Machine Algorithm for Heartbeat Monitoring and Arrhythmia Detection Based on ECG Systems.Computational intelligence and neuroscience · 2021Article
- Accelerometer-Based Fall Detection Using Machine Learning: Training and Testing on Real-World Falls.Sensors (Basel, Switzerland) · 2020Article
- A Survey on Recent Advances in Wearable Fall Detection Systems.BioMed research international · 2020Review
- Elderly Fall Detection Systems: A Literature Survey.Frontiers in robotics and AI · 2020Review
- Human Activity Recognition Using Inertial Sensors in a Smartphone: An Overview.Sensors (Basel, Switzerland) · 2019Article
- Fusion of Spectroscopy and Cobalt Electrochemistry Data for Estimating Phosphate Concentration in Hydroponic Solution.Sensors (Basel, Switzerland) · 2019Article
- Real-Time Weighted Data Fusion Algorithm for Temperature Detection Based on Small-Range Sensor Network.Sensors (Basel, Switzerland) · 2018Article
- Comparison of Different Sets of Features for Human Activity Recognition by Wearable Sensors.Sensors (Basel, Switzerland) · 2018Article
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Authors and funding
2 authors.
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Abstract
In the context of the ageing global population, researchers and scientists have tried to find solutions to many challenges faced by older people. Falls, the leading cause of injury among elderly, are usually severe enough to require immediate medical attention; thus, their detection is of primary importance. To this effect, many fall detection systems that utilize wearable and ambient sensors have been proposed. In this study, we compare three newly proposed data fusion schemes that have been applied in human activity recognition and fall detection. Furthermore, these algorithms are compared to our recent work regarding fall detection in which only one type of sensor is used. The results show that fusion algorithms differ in their performance, whereas a machine learning strategy should be preferred. In conclusion, the methods presented and the comparison of their performance provide useful insights into the problem of fall detection.
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