A joint normalcy index to evaluate patients with gait pathologies in the functional aspects of joint mobility

Abstract

Gait analysis using 3D motion capture systems provides joint kinematic and kinetic analysis results such as joint relative angles and moments that can be use used to evaluate the degrees of pathological gait patterns. However, the complex data produced using these 3D motion capture systems can only analyzed by experts, because the gait analysis is highly coupled to the kinematics of each joint. Therefore, severalSeveral previous studies using gait analysis have relied on the data compression technique to represent gait deviation from the average normal profiles as a single value. Even though it is important to evaluate gait pathologies at the joint level, all these previous studies have just used a single value to evaluate the pathological gait pattern. Using just one variable for evaluation of a gait is limited in terms of determining which joint movement patterns are getting better during rehabilitation. Therefore, in this study, a method suitable for evaluating gait deviation during a gait was developed to provide three indices for the hip, knee and ankle joints. In addition, to validate the proposed method in clinical cases, experimental tests were conducted on thirty thirty-six normal walkers and six patients with cerebral palsy. Furthermore, to validate the proposed method in regards to rehabilitation, experimental tests were conducted on three classified walking groups with imposed ankle equinus constraints. The JNI for the hip joint, knee joint and ankle were 8.78 (±3.70), 2.92 (±3.25) and 8.79 (±4.38), respectively, in the normal walking group. However, these values were significantly different for the pathological walking group with cerebral palsy. The JNI of the hip joint, knee joint and ankle joint were 203.73 (±171.59), 81.23 (±52.13) and 248.39 (±149.99), respectively, for this group. There were also differences between any two of the three classified groups with imposed ankle equinus constraints. In particular, the JNI of the ankle joint was statistically different at the p<0.01 level, and this parameter clearly increased as the degree of the imposed ankle equinus was increased. These results demonstrate that the proposed JNI can be used as a scalar factor to evaluate the angular deviation of each joint in normal and patient groups. In addition, this approach can be adapted to evaluate rehabilitation and pre/post surgery.

A WEARABLE GAIT ANALYSIS SYSTEM USING INERTIAL SENSORS PART I - Evaluation of Measures of Gait Symmetry and Normality against 3D Kinematic Data

“…The magnitude of the projection of an abnormal data set onto this space is used as a normality index, known as the Gillette Gait Index (GGI). (Shin et al, 2010) used the same PCA approach to create three separate indices using variables related to ankle, knee and hip kinematics.…”

Leveraging Multivariable Linear Regression Analysis to Identify Patients with Anterior Cruciate Ligament Deficiency Using a Composite Index of the Knee Flexion and Muscle Force

“…Armstrong et al [ 22 ] used PCA to extract the feature points of kinematics and reconstruct the kinematics process. Based on multiple parameters extracted from gait data, some indexes were developed to identify walking patterns of normal [ 23 ] and abnormal [ 24 , 25 , 26 , 27 ] gait. Schutte et al [ 26 ] proposed a normalcy index to reflect gait deviations from the mean of normal gait.…”