Gait Recognition and Phase Detection Using WearableIMUSensorsand Neural Network Algorithms

Evci F., Saroglu Y., Konukseven E. I.

7th International Conference on Advances in Artificial Intelligence, ICAAI 2023, İstanbul, Türkiye, 13 - 15 Ekim 2023, ss.138-143 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1145/3633598.3633620
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.138-143
  • Anahtar Kelimeler: Biomechanics, Machine Learning, Prosthetic Knee Analysis
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

This study investigates the application of neural network algorithms in the domain of gait recognition, with a specific emphasis on their effectiveness. Using data acquired from wearable Inertial Measurement Units (IMUs) during controlled walking trials, we have designed and implemented neural network models for the precise identification of sub-phases within the gait cycle. Our research serves as a comprehensive exploration of the capabilities of neural networks in gait analysis. We discussed the details of model development, training, and evaluation, highlighting the achieved accuracy and reliability in sub-phase detection. The outcomes of this study contribute significantly to the assessment of neural network efficacy in gait recognition, highlighting the effectiveness of machine learning algorithms in improving walking performance for prosthetic knee joints, and showing their potential for transformative applications in the field.