Mechanical load on the lumbar spine could influence the risk of low back pain (LBP). According to the global burden of disease study, between 1990–2013, LBP’s prevalence and years lived with disability (YLDs) both increased by 57% (Atun, 2015). It is one of the top ten for prevalence and the first leading cause of YLDs in 188 and 86 countries (45 to 50 developed countries) respectively. In addition, LBP ranks high (second or third) among other disabilities in 67 countries (Atun, 2015). Hence, the cause and treatment of LBP becomes difficult when it becomes chronic (CLBP), and in some case requires stabilization surgery (Fritzell et al., 2001). Given the role of lumbar surgery in restoring normal biomechanical function, understanding the normal biomechanical function of the lumbar spine is necessary. Intervertebral mobility and movement patterns are thought to be factors influencing return to normal function and reduction of disability. However, some studies have reported adjacent segment degeneration and decrease in maximum forward flexion as result of spinal fusion surgery (Nagata et al., 1993, Stief et al., 2015) thus, any decrease in the mobility of a lumbar level could increase mobility and load on its adjacent segments.

To investigate spinal mobility and movement patterns, a range of variables and procedures have been used that consider simultaneously lumbar intervertebral motion and their interactions. This information might be used to determine fusion surgery strategies (Lawrence et al., 2012). Range of motion (ROM) is a common variable to consider mobility and is different between lumbar levels. It may be used to reveal interactions between and across levels. Inflexion point timing may also provide valuable information about temporal interplay and can be extracted from the intervertebral angle’s first derivative during motion at individual and grouped levels (i.e., separate and stepwise). Specifically, the inflexion point is one data point that shows changes in the angle’s curve concavity and rate of change (Nematimoez and Thomas, 2022).

Some studies have attempted to characterize lumbar motion patterns using non-medical imaging systems (e.g., motion capture and inertial sensors). Utilizing different variables, various lumbopelvic motion patterns have been attributed to some individual and task characteristics (Zawadka et al., 2018). Pries et al., (2015) studied the lumbar/pelvic (L/P) ratio in 309 young to elder asymptomatic subjects (134 males and 175 females). Although this ratio was highly variable among participants, opposite trends were observed in the L/P ratio for older versus younger males, while during the middle and late phases of flexion, the contribution of the pelvis was reportedly larger in females than in males (Pries et al., 2015). The direction of motion can also change the coordination of these two segments; indeed, a greater in-phase pattern has been reported during trunk flexion than return (Zhou et al., 2016). Pal et al. (2007) have found that the pelvis initiated flexion motion later than the lumbar spine (i.e., 25.9 ± 4.4% vs. 16.0 ± 3.5%). They also reported a subgroup of participants (20%, n=4/20) with a similar pattern during both flexion and return phases (Pal et al., 2007). Tafazzol et al., (2014) demonstrated simultaneous rhythms for the pelvis and lumbar spine except that for the early and final stages of flexion the pelvis was dominant, with implications for reducing lumbar loads (Tafazzol et al., 2014). Lumbopelvic motion patterns have also been studied as clinical tools for discriminating asymptomatic and low back patients (Kim et al., 2013, Sanchez-Zuriaga et al., 2015). However, technical differences between the data acquisition systems used (e.g. medical imaging vs motion analysis) may, for the time being, make conclusions about the nature of lumbopelvic spatio-temporal interactions difficult.

The lumbar segments generally tend to work in tandem or in compensation (du Rose and Breen, 2016). Breen et al. (Breen and Breen, 2018) suggested less intervertebral motion sharing inequality and less variability as indices for a pain free lumbar spine and Gatton et al. (Gatton and Pearcy, 1999) demonstrated between-subject variability and complexity of interactions among lumbar vertebrae in a small participant sample (n=14). Additionally, discussion has arisen around whether segmental flexion and extension patterns should be simultaneous or sequential (Breen and Breen, 2018, du Rose and Breen, 2016, Gatton and Pearcy, 1999, Lawrence et al., 2012, Nematimoez and Thomas, 2022). In a study that categorized ninety adults into four and three groups according to the degree of total ROM of flexion and extension respectively, the greatest segmental contributions to lumbar flexion occurred in the upper segments (Miyasaka et al., 2000). Wong et al. (Wong, Leong, Chan, Luk, & Lu, 2004) also observed more flexibility in the cranial region for one hundred subjects, reporting that physiologic ROM decreased in people aged 51 years or older. However, the lumbar kinematics literature is inconsistent on this, leading to difficulties with clinical interpretations, with different authors measuring different kinematic variables and numbers of vertebrae.

The purpose of this study was therefore to categorize intervertebral angular motion in a substantial dataset of asymptomatic subjects based on a group of clustering criteria utilizing spatial and temporal variables recorded during continuous motion for individual and segmentally grouped flexion. It was hypothesized that the lumbar segments’ ROM and angle time series would be different among clusters during the flexion phase of movement.