People spend more and more time seated in transportation, at home, and at office. Comfort is not only an important sales argument for seat manufacturers, but is also well recognized as an important health factor for sitters. Long-term sitting may lead to discomfort (De Looze et al., 2003, Hiemstra-van Mastrigt et al., 2017), and even to pressure sores for wheelchair users (Olesen et al. 2010). Surprisingly little is known about the consequences of different support conditions on the human body due to its complexity as mechanical system (Ramussen et al., 2009).

Among the factors that generate the discomfort feeling, we can mention the soft tissue compression, muscular activity required for postural equilibrium, pressure between the intervertebral discs, shear at contact interface etc. Mastrigt et al. (2017) provided an extensive review on seating discomfort and found that interface pressure is affected by body size and posture, but their relationship cannot be quantified due to the lack of statistical evidence. Apart from the subjective responses via questionnaires, the experimental investigation is often limited to the analysis of the distribution of contact pressure between sitter and seat. Zemp et al. (2015) reviewed studies investigating the relationships between pressure and discomfort. They concluded that the question whether contact pressure measurements are suitable for assessing seating comfort or discomfort could not yet be answered definitely, due to limited available data. Internal load measurements can be obtained only invasively and thus only a limited number of studies exist in the literature (Andersson et al. 1974, Wilke et al. 1999). Computational human models are therefore needed to estimate these biomechanical variables indirectly.

Two types of human models have been developed, deformable finite element (FE; Savonnet et al., 2018) and rigid multi-body musculoskeletal (MSK; Rasmussen et al., 2009) models. FE models have advantage of being able to estimate soft tissue deformation. However, it is more difficult to create a personalized FE model and modify its posture corresponding to experimental conditions. Considering the contribution of muscle forces to intervertebral loading is also complex. In contrast, MSK models are easier to be personalized and positioned. They can be used to investigate the effects of different support conditions on muscle activity and spinal joint forces. However, these models are generally not validated under the conditions relevant for seating applications (Wang et al., 2019b). Relationships between biomechanical variables and discomfort are still unclear.

Most existing studies on seating comfort used a real or an experimental seat affording little opportunity to vary design parameters (Hiemstra-van Mastrigt et al., 2017). It is therefore difficult to isolate the effects of one particular seat parameter and to look at its interaction with other variables. Recently we built a multi-adjustable experimental seat equipped with force sensors (Beurier et al, 2017) and investigated the effects of seat parameters and anthropometric dimensions on preferred seat profile and contact forces (Wang et al, 2018 and 2019a). Results not only provide quantitative guidelines for designing future seats, but also data for validating computational human models and for defining comprehensive boundary conditions.

In parallel to experimental investigations, we also carried out a preliminary study with only 6 participants aiming to relate internal loads estimated by a MSK model and sitting discomfort (Theodorakos et al., 2018). Results showed that lower discomfort rated postures were associated with lower muscle activities and lower shear force at contact interface. Further studies with a larger sample are needed to confirm these preliminary findings.

Objective

The main objective is to investigate the relationship between subjective discomfort feeling and objective biomechanical measures. Several specific objectives are identified:

•To develop and validate a MSK model for estimating internal loads such as muscle activity and joint forces,

•To understand the role of seat supports and the causes of seating discomfort

Approach

A personalizable geometric model including the spine and the pelvis will be developed with help of anatomical points (Peng et al, 2015) or external envelope (Nérot et al, 2016). Then, a musculoskeletal model of the spine will also be set up to estimate the compression and shear in the intervertebral joints and the muscular activities of postural maintenance. It will be integrated into a musculoskeletal modeling tool such as Anybody or RPx developed at LBMC. Intervertebral compression obtained with the model will be validated with measurements from instrumented implants (Rohlmann et al. 2011).

The personalized model thus put in a seated position will be used to understand possible causes of sitting discomfort. The existing data collected in the past at LBMC will be further explored including a sample of differently sized participants testing a large number of seat configurations (Wang et al, 2018 and 2019a). Additional tests could be planned if necessary.

Planning and expected results

The research project will be divided in the following phases:

•Literature review on musculoskeletal modeling and seating comfort

•Building of a personalizable geometric model including in particular the spine and pelvis

•Development of MSK models and investigation on the relationships between biomechanical parameters and discomfort perception

•PhD thesis writing and defense

References

Andersson et al. (1974). Scand J Rehabil Med. 6(3): 128-133.

Beurier et al. (2017). SAE Technical Paper, No. 2017-01-1393.

De Looze et al. (2003). Ergonomics 46(10), 985–997.

Hiemstra-van Mastrigt et al. (2017). Ergonomics 60, 889–911.

Nérot et al. (2016). J Biomechanics 49, 3415-3422

Olesen et al. (2010). J Appl Physiol. 108: 1458-1464.

Peng et al. (2015) J Biomechanics 48, 396-400

Rasmussen et al. (2009). Int J Ind Ergonomics 39(1): 52-57.

Rohlmann et al. (2011). Spine, 11, no 9: 870-75

Savonnet et al. (2018). Comp Meth in Biomech and Biomed Eng 21 (4): 379 88.

Theodorakos et al. (2018). In Proceedings of the 20th Congress of IEA

Wang et al. (2018). App Erg 73, 13–21

Wang et al. (2019a). Ergonomics, 62:7, 891-902

Wang et al. (2019b). DHM and posturography, Ed. S. Scataglini and G. Paul. Academic Press, 643-659.

Wilke et al. (1999). Spine 24(8): 755-762.

Zemp et al. (2015). App Erg 48:273-82