Using ANN to study the gender effect on horizontal transmissibility to the head during whole-body vibration

Mohammad AlShabi; Naser Nawayseh

doi:10.1117/12.2632218

6 June 2022 Using ANN to study the gender effect on horizontal transmissibility to the head during whole-body vibration

Mohammad AlShabi, Naser Nawayseh

Proceedings Volume 12113, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications IV; 1211328 (2022) https://doi.org/10.1117/12.2632218
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Conference Poster

Abstract

In this article, an Artificial Neural Network (ANN) has been used to model the relationship between the gender of human subject to its response to whole-body vibration (WBV). To train, validate and test the model, an experiment was conducted on 20 female and 20 male subjects at different vibration frequencies in the range of 20 to 45 Hz. The response was measured by taking the ratio between the subject head’s horizontal acceleration to the platform’s vertical acceleration. The subjects’ body mass index, mass, height, gender, and age, and the excitation frequency were used as inputs to the ANN. The ANN model showed a good performance of 98.645% matching regression, and RMSE and MAE of 0.0128 and 0.0483, respectively.

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Citation Download Citation

Mohammad AlShabi and Naser Nawayseh "Using ANN to study the gender effect on horizontal transmissibility to the head during whole-body vibration", Proc. SPIE 12113, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications IV, 1211328 (6 June 2022); https://doi.org/10.1117/12.2632218

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