Predicting aircraft seat comfort using an artificial neural network

Abstract

Aircraft seat pitch is one of the most important factors affecting passengers ability to sit comfortably for a longer time on the plane. The purpose of this study was to illustrate the association between different seat pitches and overall comfort index, and seat‐interface pressure variables as well as try to predict aircraft seat comfort. Through an experimental study, 11 subjects (age, 26.3 ± 1.6; height, 169.8 ± 8.5; body mass, 65.1 ± 15.6) rated five different seat pitch settings (55 examples, 11 participants and five scenarios). Descriptive statistics, together with one‐way analysis of variance were used to determine which of the metrics could be used to distinguish the overall comfort index. The results show that overall comfort index was statistically significant (p < 0.05) between different seat pitches, but there was no statistically significant difference (p > 0.05) in interface pressure variables. In addition, a multilayer feed forward neural network with one hidden layer was proposed with the help of Matlab Neural Network Toolbox. The model explained 99% of the variance in overall comfort index with the root mean square error (RMSE) of 0.12551. The remainder of the total data was used for validation purposes; the correlation is r = 0.775, p < 0.01, and the RMSE is 1.21031. That suggests this model has a significant relationship between the actual and predicted overall comfort index.

Habitabilidad Inclusiva en Los Taxis De Santiago: Estado Del Arte Y Consideraciones Desde El Diseño Industrial

“…necesario que el peso tenga una mayor concentración en las caderas para mejorar el control, pues esta zona es la más influyente en la percepción de comodidad. Esto también se relaciona con la sensación de malestar que se produce por la carga física y el dolor (Zhao et al, 2017) en una posición prolongada. A pesar de ello, un exceso de fricción dificulta el deslizamiento necesario para salir del vehículo.…”

Effect of Personal Space Invasion on Passenger Comfort and Comfort Design of an Aircraft Cabin

“…As aircraft passenger comfort research has progressed, many achievements have been made in seat comfort design and other research areas [7][8][9]. Previous literature [10] shows that many studies have examined factors in aircraft seat comfort design such as seat height, seat pitch, seat width, seat pan length, and legroom [5,11,12]. Other areas of research include the physical comfort of aircraft passengers, such as seat posture, human-body load, seat and foot pressure measurements, vibration, noise, temperature, and air quality [13][14][15].…”

“…An ANN model has been applied to predict automobile seat comfort [42]. Zhao et al [12] established the prediction model of aircraft seat comfort by employing an ANN model. Studies like these have not been used to evaluate passenger comfort from an overall perspective.…”

Metrics of Comfort: Development of Physiological Correlates to Subjective Responses

“…Physical features of the chair (e.g., support provided) have been linked to assessments of discomfort (Bush & Hubbard, 2008). The assessment of comfort and discomfort while seated has been explored through subjective assessments, performance assessments, and postural measures (de Looze, 2003;Lueder, 1983;Openshaw, 2011) and even artificial neural networks that included seat pressures (Zhao, Yu, Miller, Ghulam, & Wang, 2019), but none have looked specifically at the reliability of physiological responses to predict comfort. Another important unknown regarding the measurements of comfort and discomfort is the relationship between the context, seat, human, and time.…”