Pelvic movement variability of healthy and unilateral hip joint involvement individuals. (February 2017)

• Record Type: Journal Article
• Authors: Andrade, Adriano O.; Ferreira, Luiz Cláudio Vieira; Rabelo, Amanda G.; Vieira, Marcus Fraga; Campos, Alexwell Rodrigues; Gonçalves, Bruno Ferreira; Pereira, Adriano A.
• Is Part Of: Biomedical signal processing and control. Volume 32(2017)
• Page Start: 10
• Page End: 19
• Publication Date: 2017-02
• Subjects: Gait variability -- Inertial sensors -- Hip disorders -- Pelvic movement analysis; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2016.10.008
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: The gait analysis of persons in healthy and hip disorder conditions is proposed. Step and stride periods were detected by using accelerometers. Data analysis was performed by using two sets of 3D inertial sensors on the pelvis. The variability of step and stride times was higher for persons with hip condition. Pelvic movement features had higher variability for persons with hip condition. Abstract: Data variability analysis has been the focus of a number of studies seeking to capture differences of patterns generated by biological systems. Although there are several studies reporting variability in gait analysis we still have lack of researches that employ inertial sensors for the characterization of the variability of the duration of the gait cycle and pelvic movements for groups of individuals in healthy and hip joint involvement conditions. In this research this variability is characterized within the step and stride time intervals. Data were collected with subjects walking on a treadmill at a velocity of 2 km/h, being the group G1 with 10 healthy subjects (30.7 ± 6.75 years old) and G2 with 24 individuals with unilateral hip joint involvement (65 ± 8.5 years old). Two sets of inertial measurement units were employed for movement detection, and then features were extracted for the characterization of their variability. The coefficient of variation was used for assessing the variability. Significant differences (p < 0.05) were found between the mean step and stride times of the groups. The variability of the step and stride times, and also of the investigated features, were larger for the group G2 (p < 0.05). The proposed methods used in this study showed to be adequate for the measurement of the variability of biomechanical parameters, represented by their features. All the studied features were able to discriminate the groups. Both ageing and pathological factors may have jointly contributed to the G2 group increased variability.