Use of kinematic algorithms to distinguish people with chronic non-specific low back pain from
asymptomatic subjects: a validation study
Sammanfattning
OBJECTIVE: To determine whether kinematic algorithms can distinguish subjects with chronic
non-specific low back pain from asymptomatic subjects and subjects simulating low back pain, during
trunk motion tasks.
DESIGN: Comparative cohort study.
SUBJECTS: A total of 90 subjects composed 3 groups; 45 chronic non-specific low back pain patients
in the CLBP group; 45 asymptomatic controls people in the asymptomatic controls group. 20/45
subjects from the asymptomatic controls group composed the CLBP simulators group as well.
Method: During performance of 7 standardized trunk motion tasks 6 spinal segments from the
kinematic spine model were recorded by 8 infrared cameras. Two logit scores, for range of motion
and speed, were used to investigate differences between the groups. Group allocation based on logit
scores was also calculated, allowing the assessment of sensitivity and specificity of the algorithms.
RESULTS: For the 90 subjects (pooled data), the logit scores for range of motion and speed
demonstrated highly significant differences between groups (p < 0.001). The logit score means and
standard deviation (SD) values in the asymptomatic group (n = 45) and chronic non-specific low back
pain group (n = 45), respectively, were -1.6 (SD 2.6) and 2.8 (SD 2.8) for range of motion and -2.6 (SD
2.5) and 1.2 (SD 1.9) for speed. The sensitivity and specificity (n = 90) for logit score for range of
motion were 0.80/0.82 and for logit score for speed were 0.80/0.87, respectively.
CONCLUSION: These results support the validity of using 2 movement algorithms, range of motion
and speed, to discriminate asymptomatic subjects from those with low back pain. However, people
simulating low back pain cannot be distinguished from those with real low back pain using this
method.