November 4, 2025Open Access

Wearable Sensor Gait Analysis of Fall Detection using Attention Network

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Authors

HYHaben Yhdego JLJiang LiOld Dominion University CPChristopher Paolini

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Implication

Analysis shows improved fall detection in geriatric population using wearable sensors, suggesting advanced models enhance protection through pneumatic actuation.

Key Points

Fall detection improved using deep neural networks for gait analysis and wearable sensors, targeting elderly safety.
Proposed model reduces false positives and negatives, achieving better specificity and sensitivity than existing methods.
Gait analysis leverages attention networks within deep neural networks to analyze acceleration data effectively.
Support for pneumatic actuation during falls may mitigate injury risks among senior adults if detection is timely.

Cite This Study

Yhdego et al. (2021) studied this question.

synapsesocial.com/papers/690aab1a5b68e76fd9e7a4b1 https://doi.org/10.1109/bibm52615.2021.9669795

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Implication

Analysis shows improved fall detection in geriatric population using wearable sensors, suggesting advanced models enhance protection through pneumatic actuation.

Wearable Sensor Gait Analysis of Fall Detection using Attention Network

Discussion

Member takes

Implication

Key Points

Cite This Study

Wearable Sensor Gait Analysis of Fall Detection using Attention Network

Discussion

Member takes

Implication

Key Points

Cite This Study

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