Design and analysis of comparative experiments to assess the (dis-)comfort of aircraft seating

Vanacore, Amalia; Lanzotti, Antonio; Percuoco, Chiara; Capasso, Agostino; Vitolo, Bonaventura

doi:10.1016/j.apergo.2018.12.012

Cited by 16 publications

(14 citation statements)

References 29 publications

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“…(2) seat, such as dimensions, shape, and reclined backrest angle; and (3) context, which include activities and the environment. A similar research by Vanacore et al (2019) on posture induced by activity (Kamp et al, 2011;Ellegast et al, 2012;Groenesteijn et al, 2012), and effect of posture on seat-interface pressure distribution (Vos et al, 2006;Moes, 2007;Tessendorf et al, 2009;Kyung and Nussbaum, 2013), showed the closest correlation between objective measure and subjective (dis-)comfort rating. Thus, human anthropometry, seat, and context should be involved in the study of sitting postures.…”

Section: Introductionmentioning

confidence: 63%

Sitting posture detection and recognition of aircraft passengers using machine learning

Cun

Chu

et al. 2021

AIEDAM

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Prolonged sitting in a fixed or constrained position exposes aircraft passengers to long-term static loading of their bodies, which has deleterious effects on passengers’ comfort throughout the duration of the flight. The previous studies focused primarily on office and driving sitting postures and few studies, however, focused on the sitting postures of passengers in aircraft. Consequently, the aim of the present study is to detect and recognize the sitting postures of aircraft passengers in relation to sitting discomfort. A total of 24 subjects were recruited for the experiment, which lasted for 2 h. Furthermore, a total of 489 sitting postures were extracted and the pressure data between subjects and seat was collected from the experiment. After the detection of sitting postures, eight types of sitting postures were classified based on key parts (trunk, back, and legs) of the human bodies. Thereafter, the eight types of sitting postures were recognized with the aid of pressure data of seat pan and backrest employing several machine learning methods. The best classification rate of 89.26% was obtained from the support vector machine (SVM) with radial basis function (RBF) kernel. The detection and recognition of the eight types of sitting postures of aircraft passengers in this study provided an insight into aircraft passengers’ discomfort and seat design.

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Section: Introductionmentioning

confidence: 63%

Sitting posture detection and recognition of aircraft passengers using machine learning

Cun

Chu

et al. 2021

AIEDAM

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“…An important limitation of this study and the previous study on staggered seats (Liu et al 2021) is that the participants tested the seat for only 10 min. Smulders et al (2016), Li et al (2017) and Vanacore et al (2019) show that discomfort increases over time. Therefore, long term tests are needed in order to confirm whether the observed effects hold for a 6-12 h flight.…”

Section: Discussionmentioning

confidence: 97%

A Staggered Seat is Beneficial for the Flying V Aircraft

Vink

Anjani

Percuoco

et al. 2021

Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021)

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Staggered seats might be a solution for a V-shaped aircraft (the Flying V). The cabin longitudinal axis of this airplane has a 26°angle with respect to the direction of flight. When seats are positioned in the direction of flight, they consequently have an angle to the cabin and become staggered. It is unknown whether the comfort of this staggered seat is appreciated. In this study, 117 participants tested the comfort and the privacy experience in this staggered seat compared with a regular aircraft seat. The experiment showed that both comfort and privacy were significantly better in the staggered seats. However, the analysis is based on short-term evaluations, which means that long-term effects still need to be studied and also the effects of groups travelling together need to be investigated.

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“…body pressure distribution, body movement and EMG. A lightweight seat has a higher level of comfort in an aircraft (Vanacore, Lanzotti, Percuoco, Capasso, & Vitolo, 2019). Any seat movement introduced to the driving seat is slow, smooth, and small to minimize the effect on the driving task (Varela et al, 2019)a control (no movement.…”

Section: Introductionmentioning

confidence: 99%

Design of Ergonomic Chair for Grinding Operation

2020

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One of essential production activities is grinding process. This process mainly involves the constant activity of eroding a surface to be smoother or more evenly, cutting a workpiece, creating profiles like angles and arches, sharpening a cutting tool, and finishing a final product. Meanwhile, there is no study evaluating the risk levels of workers working on grinding, and there is no unique chair specifically designed for the process. Therefore, this study aims to assess the risk levels of a grinding worker and to propose the design of an ergonomic chair that is adjustable, comfortable, durable, and keen to be used. The risk levels of the grinding workers were evaluated using REBA, while the ergonomic chair design was based on anthropometric data taken from 4 grinding workers in Bantul, Special Region of Yogyakarta, Indonesia. The researchers selected a buttock-popliteal length (seat depth), lower leg length (popliteal height) and hip breadth sitting as anthropometric measures to make a chair design for the grinding operations. After that, the existing adjustable chair designs were also considered and evaluated to get better adjustable-ergonomic chair design for the grinding operations. The results show that it is important that the stakeholders improve most of the grinding operations of the workers, especially by using an ergonomic chair design for grinding operation that is adjustable, comfortable, durable, and reliable. The chair height can be adjusted from 361-414 mm to adapt with the users, and the variation in product height aims to prevent bending on the back. Finally, the grinding chair can reduce the risk level from the high and medium level to the low-risk levels of working postures.

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Design and analysis of comparative experiments to assess the (dis-)comfort of aircraft seating

Cited by 16 publications

References 29 publications

Sitting posture detection and recognition of aircraft passengers using machine learning

Sitting posture detection and recognition of aircraft passengers using machine learning

A Staggered Seat is Beneficial for the Flying V Aircraft

Design of Ergonomic Chair for Grinding Operation

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