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Journals / Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi / 2021 / Cilt: 21 - Sayı: 2

Gait Analysis of Smart Phones with The Help of The Accelerometer Sensor

Akıllı Telefonların İvmeölçer Sensörü Yardımıyla Yürüyüş Deseni Analizi

Emrah AYDEMİR
İbrahim KARSLIOĞLU
Pages
283–299
Publication Date
2022-10-12
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

With this method, it is thought that moreeconomical methods will be developed instead of high-cost devices in detecting gait disorders.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The ability to measure human movements in sports fields is among the important issues forperformance measurement and development.
📊
Key Findings & Data:In this study, walking data of 50 different people were used in a 100-meter-long corridor.The walking dataset was obtained from the accelerometer sensor with a software developed for thesmartphone.
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Conclusion & Impact:With this method, it is thought that moreeconomical methods will be developed instead of high-cost devices in detecting gait disorders.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The ability to measure human movements in sports fields is among the important issues forperformance measurement and development. This instance is also an important part of clinicalevaluations. Electromagnetic systems are among the most widely used methods to evaluate humanmovements. In this study, walking data of 50 different people were used in a 100-meter-long corridor.The walking dataset was obtained from the accelerometer sensor with a software developed for thesmartphone. Three-dimensional Local Binary Pattern (LBP) method was applied to the dataset and atotal of 768 features were generated. Datasets were made with different classification algorithms and97.2% successful classification was achieved with Subspace KNN. In the classification according togender, 99.7% successful classification was obtained. With this method, it is thought that moreeconomical methods will be developed instead of high-cost devices in detecting gait disorders.

Özet

Spor alanlarında insan hareketlerini ölçme yeteneği performans ölçüm ve gelişimi için önemli konular arasındadır. Bu durum aynı zamanda klinik değerlendirmelerin de önemli bir parçasıdır. Özellikle elektromanyetik sistemler insan hareketlerini değerlendirmek için en yaygın kullanılan yöntemler arasında yer alır. Buradaki çalışmada 100 metre uzunluğunda bir koridorda 50 farklı kişinin yürüme verileri kullanılmıştır. Yürüme verileri akıllı telefon için geliştirilen bir yazılım ile ivmeölçer sensöründen elde edilmiştir. Verilere üç boyutlu Local Binary Pattern (LBP) yöntemi uygulanmış ve toplam 768 öznitelik çıkarılmıştır. Farklı sınıflandırma algoritmaları ile testler yapılmış ve Subspace KNN ile %97,2 başarılı sınıflandırma elde edilmiştir. Cinsiyete göre yapılan sınıflandırmada ise %99,7 başarılı sınıflandırma elde edilmiştir. Bu yöntem ile yürüme bozukluğu tespitinde yüksek maliyetli cihazlar yerine daha ekonomik yöntemler geliştirileceği düşünülmektedir.

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Cite This Article

AYDEMİR, E., KARSLIOĞLU, İ. (2022). Gait Analysis of Smart Phones with The Help of The Accelerometer Sensor. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, Cilt: 21 - Sayı: 2, 283–299. https://ajindex.com/articles/429628

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