Studying the gender effect on apparent mass during whole-body vibration using ANN

Mohammad AlShabi; Naser Nawayseh

doi:10.1117/12.2663986

14 June 2023 Studying the gender effect on apparent mass during whole-body vibration using ANN

Mohammad AlShabi, Naser Nawayseh

Proceedings Volume 12548, Smart Biomedical and Physiological Sensor Technology XX; 125480D (2023) https://doi.org/10.1117/12.2663986
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Conference Poster

Abstract

Artificial Neural Network (ANN) is a powerful tool to model a system using only the inputs and outputs of that system. In this paper, ANN is used to model the relation between the subject’s gender to its performance while been excited in a whole-body vibration machine (WBV). For training the ANN, 20 male and 20 female subjects were observed during an experimental setup using a WBV at different vibration frequencies in the range of 20 to 45 Hz. The apparent mass was measured for the subjects at different frequencies. The input to the ANN includes body mass index, mass, and gender of the subjects along with and the excitation frequency. The ANN shows a good performance and extract the relationship with a performance that has a root mean squared error of the relative percentage error less than 9%.

Citation Download Citation

Mohammad AlShabi and Naser Nawayseh "Studying the gender effect on apparent mass during whole-body vibration using ANN", Proc. SPIE 12548, Smart Biomedical and Physiological Sensor Technology XX, 125480D (14 June 2023); https://doi.org/10.1117/12.2663986

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