Lumbopelvic-Hip Rhythm in People with Lumbar Flexion-with-Rotation Syndrome during Hip Internal Rotation

Background

According to previous research, hip internal rotation (HIR) aggravates low back pain (LBP) symptoms, especially in patients with lumbar flexion with rotation (F + R) syndrome. Therefore, the present study aimed to examine the lumbopelvic-hip rhythm during the HIR test in patients with this syndrome.

Methods

In this cross-sectional study, 20 men without LBP and 20 matched men with LBP, subcategorized in the F+R subgroup, participated. The participants performed the HIR test. Kinematics data were recorded using a motion analysis system. After processing the kinematics, a comparison was made in the hip and pelvic kinematics between the groups.

Results

A statistical analysis based on an independent t test revealed a significant increased (P < 0.05) pelvic rotation during the tests with the dominant ( P = 0.007) and nondominant limbs (P = 0.025) in those with LBP. The analysis also showed that during the test with the dominant lower limb, the pelvis and hip moved with a more synchronized pattern in patients with LBP (P = 0.001).

Conclusion

In the patients with lumbar F + R syndrome, there was a tendency for early pelvic rotation during the dominant HIR test. Moreover, LBP people also exhibited a greater pelvic rotation range of motion in the first half and whole pathways of the test. These impairments could be a risk factor for the development of LBP symptoms in these patients.

ALTERNATIVE METHOD FOR PAIN ASSESSMENT USING EMG AND GSR

Most of the existing pain estimation techniques depend on the response of the subject through verbal or nonverbal communication which does not suit infants, senseless and injured persons, and subjects with cognitive impairment. To bridge this gap, researchers have explored the potential of facial video- and image-based pain recognition methods. However, it provides limited classification performance with complex computation and costly frameworks including a large storage capacity. The dependence of autonomic nervous system (ANS) activities on stimulus like pain provides an alternative pathway to assess pain subjected to external stimuli through ANS-related biosignals. In this article, processing and analysis technique of electromyogram and galvanic skin response signals for assessment of pain for noncooperative subjects are presented and validated against BioVid heat pain database. Different intensities of pain are considered and characterized with the statistical features extracted from the said biosignals. It is noticed that the accuracy level of pain estimation increases with the rise in pain intensity. For highest pain level, 80% detection accuracy is achieved which outperforms the performances of facial expression-based pain assessment techniques.