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Dergiler / Hittite Journal of Science and Engineering / 2021 / Cilt: 8 - Sayı: 3

Elderly Fall Detection and Fall Direction Detection via Various Machine Learning Algorithms Using Wearable Sensors

Yılmaz Güven
Sıtkı Kocaoğlu
Sayfa
197–205
Yayın Tarihi
2022-10-18
DOI
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Yapay Zeka Hızlı Bakış & Çıkarımlar

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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The classification via the test data corresponding to 30% of the total data, which was never used during the training phase, has been performed with 99.4% accuracy, and then 97.2% success has been achieved in determining the direction of falling.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:The world population is aging rapidly.
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Temel Bulgular & Veri:In this study, a two-step fall detection and fall direction detection system has been developed by using a public dataset and by testing 5 different machine learning algorithms comparatively.
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Sonuç & Katkı:The classification via the test data corresponding to 30% of the total data, which was never used during the training phase, has been performed with 99.4% accuracy, and then 97.2% success has been achieved in determining the direction of falling.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Fall Detection · Falling Direction Detection · Machine Learning

Abstract

The world population is aging rapidly. Some of the elderly live alone and it is observed that the elderly who live with their families frequently have to stay at home alone, especially during the working hours of adult members of the family. Falling while alone at home often results in fatal injuries and even death in elderly individuals. Fall detection systems detect falls and provide emergency healthcare services quickly. In this study, a two-step fall detection and fall direction detection system has been developed by using a public dataset and by testing 5 different machine learning algorithms comparatively. If a fall is detected in the first stage, the second stage is started and the direction of the fall is determined. In this way, the fall direction of the elderly individual can be determined for use in future researches, and a system that enables necessary measures such as opening an airbag in the direction of the fall is developed. Thus, a gradual fall detection and fall direction detection system has been developed by determining the best classifying algorithms. As a result, it has been determined that Ensemble Subspace k-NN classifier performs a little more successful classification compared to other classifiers. The classification via the test data corresponding to 30% of the total data, which was never used during the training phase, has been performed with 99.4% accuracy, and then 97.2% success has been achieved in determining the direction of falling.

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Bu Makaleye Atıf Yap

Güven, Y., Kocaoğlu, S. (2022). Elderly Fall Detection and Fall Direction Detection via Various Machine Learning Algorithms Using Wearable Sensors. Hittite Journal of Science and Engineering, Cilt: 8 - Sayı: 3, 197–205. https://ajindex.com/articles/537899

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Kaynakça (3)

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