Evaluation of Accelerometer-Based Fall Detection Algorithms on Real-World Falls
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DOI: 10.1371/journal.pone.0037062
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Cited by:
- Cheng-Wen Lee & Hsiu-Mang Chuang, 2021. "Elderly Fall Detection Devices Using Multiple AIoT Biomedical Sensors," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(6), pages 1-1.
- Carlos Medrano & Raul Igual & Inmaculada Plaza & Manuel Castro, 2014. "Detecting Falls as Novelties in Acceleration Patterns Acquired with Smartphones," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-9, April.
- José Carlos Castillo & Davide Carneiro & Juan Serrano-Cuerda & Paulo Novais & Antonio Fernández-Caballero & José Neves, 2014. "A multi-modal approach for activity classification and fall detection," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(4), pages 810-824, April.
- Dave Archer & Michael A August & Georgios Bouloukakis & Christopher Davison & Mamadou H Diallo & Dhrubajyoti Ghosh & Christopher T Graves & Michael Hay & Xi He & Peeter Laud & Steve Lu & Ashwin Machan, 2022. "Transitioning from testbeds to ships: an experience study in deploying the TIPPERS Internet of Things platform to the US Navy," The Journal of Defense Modeling and Simulation, , vol. 19(3), pages 501-517, July.
- Melissa C Kilby & Semyon M Slobounov & Karl M Newell, 2014. "Postural Instability Detection: Aging and the Complexity of Spatial-Temporal Distributional Patterns for Virtually Contacting the Stability Boundary in Human Stance," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-12, October.
- Ionut Anghel & Tudor Cioara & Dorin Moldovan & Marcel Antal & Claudia Daniela Pop & Ioan Salomie & Cristina Bianca Pop & Viorica Rozina Chifu, 2020. "Smart Environments and Social Robots for Age-Friendly Integrated Care Services," IJERPH, MDPI, vol. 17(11), pages 1-31, May.
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