Sawicki, Aleksander ; Saeed, Khalid
Współtwórca:Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.
Tytuł:A quaternion-based augmenting method dedicated to biometric gait systems
Tytuł publikacji grupowej: Temat i słowa kluczowe:biometrics ; MEMS ; CNN ; augmentation
Abstract:Collecting large amounts of real-world data can be expensive, time-consuming, or even impossible in some cases. This situation can be particularly acute for IMU-based gait-analysis data due to participant fatigue, changing walking surfaces, and instrumentation positioning. These factors can provoke changes in the characteristics (drift or distribution shift) of data collected over long durations or on different days, making analysis difficult. Ideally, one would prefer a larger data set whose distributional characteristics do not change. ; Data augmentation can help address this limitation by creating more training data from what is already available. It is a technique used to artificially increase the amount of data available for training machine learning models. It works by creating new data points from existing data through various modifications. We present a new data-augmentation technique based on modelling three types of common sensor disturbances: alignments, vibrations and drift. ; The new approach is compared to three state-of-the-art methods, and validated on three different data sets: two from publicly accessible repositories, and one from our own laboratory with 100 participants and 30 gait cycles per person. Improvements in classification accuracy are obtained for each data set: 35%, 90% and 21%, respectively. The experiments show that the use of data augmentation has a positive impact on the metrics of the gait biometric system. It enables increased efficiency in identifying subjects from a limited sample of data and does not require a problematic data acquisition process.
Wydawca:Zielona Góra: Uniwersytet Zielonogórski
Data wydania: Typ zasobu: DOI: Strony: Źródło:AMCS, volume 35, number 4 (2025) ; kliknij tutaj, żeby przejść
Jezyk: Licencja CC BY 4.0: Prawa do dysponowania publikacją: