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  1. Statistical analysis of triaxial acceleration data of different fall scenarios

Statistical analysis of triaxial acceleration data of different fall scenarios

Delavarkhalafi, F ; Sharif University of Technology | 2023

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  1. Type of Document: Article
  2. DOI: 10.1109/ICBME61513.2023.10488525
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2023
  4. Abstract:
  5. Fall is a common event among elderly people which can cause significant injury and even death. Investigating the most common fall scenarios can lead to a better understanding of their differences and similarities and unveil their specific discriminative features. Triaxial acceleration signals were captured during the simulated falls of 1 elderly and 10 young persons, using a single Inertial Measurement Unit (IMU) mounted on their waist. In total, 12 different fall scenarios (direction/activity) were examined and their acceleration signals within a fall window, defined between 50 milliseconds before and after the main peak (range: 2-10 g), were compared via ANOVA test. Results indicated significant differences (p<0.05) between the forward accelerations of several fall scenarios, whereas the lateral and gravity accelerations displayed relatively comparable patterns across the scenarios. Also, comparison of the directional jerk data revealed larger forward jerks in the fast-forward falls. These findings exhibit the importance of considering the directional acceleration signals as an effective factor for detecting different fall scenarios. © 2023 IEEE
  6. Keywords:
  7. Acceleration ; ANOVA ; Elderly people ; Fall ; Wearable sensors
  8. Source: 2023 30th National and 8th International Iranian Conference on Biomedical Engineering, ICBME 2023 ; 2023 , Pages 321-327 ; 979-835035973-2 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/10488525