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Title:
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CLASSIFICATION OF METHODS AND ALGORITHMS
FOR DETECTION OF FALLS IN OLDER ADULTS |
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Author(s):
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Manuel Erazo-Valadez, Javier Ortiz-Hernandez, Angel Israel Daza-Castillo,
Juan Antonio Miguel-Ruiz, Alicia Martínez-Rebollar and Yasmin Hernandez |
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ISBN:
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978-989-8704-38-2 |
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Editors:
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Piet Kommers, Inmaculada Arnedillo Sánchez and Pedro Isaías |
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Year:
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2022 |
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Edition:
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Single |
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Keywords:
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Fall Detection, Methods and Algorithms, Wearable Sensors, Older Adults |
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First Page:
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77 |
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Last Page:
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84 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Approximately 30% of older adults fall at least once a year and 50% of that number will fall twice. Likewise, the number
of falls that an older adult may suffer rises with increasing age. Falls have a high morbidity and mortality rate and are
considered a major public health problem. It is estimated that 7% of hospital visits by older adults are the result of a fall
and 40% of these require hospitalization. This article presents some of the main detection methods and algorithms used for
fall detection and discusses their advantages and disadvantages. Each of these methods and algorithms directly or indirectly
requires varying processing, connectivity, storage, and portability capabilities and provides varying degrees of accuracy.
Based on this analysis, an experimental development for fall arrest in older adults will be proposed that aims to achieve
95% accuracy using a minimally invasive wearable sensor. |
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