To the Editor:Anterior cruciate ligament(ACL)rupture is a frequent knee injury that modifies knee joint kinematics,including intra-articular motions and forces,leading to recurrent functional instability of the knee.W...To the Editor:Anterior cruciate ligament(ACL)rupture is a frequent knee injury that modifies knee joint kinematics,including intra-articular motions and forces,leading to recurrent functional instability of the knee.With an estimated 200,000 ACL ruptures annually in the United States,ACL ruptures are prevalent,especially in young,physically active individuals.[1]Restoring knee morphology,stability,and function is the aim of conventional therapy,which is ACL reconstruction(ACLR).[2]Previous studies have evaluated gait function at different time points before and after ACLR to quantify impairments in movement patterns and knee joint biomechanics.[3]These investigations have consistently revealed substantial alterations in gait patterns induced by ACLR,with recovery persisting for at least 6 months post-procedure.[4]Majewska et al[4]pointed out that most studies focus on short-term follow-up within 6 months after surgery,while time-dependent changes in long-term dynamic functional recovery remain poorly studied.Accordingly,we aimed to perform gait analysis both pre-ACLR and throughout the 12 months postoperatively,complemented by standard assessments of knee joint function.展开更多
The use of parameterization in assessing gait waveforms has been widely accepted, although it is recognized that this approach excludes the majority of information contained in the waveform. Waveform analysis techniqu...The use of parameterization in assessing gait waveforms has been widely accepted, although it is recognized that this approach excludes the majority of information contained in the waveform. Waveform analysis techniques, such as principal component analysis (PCA), have gained popularity in recent years as a more effective approach to extracting important information from human movement waveforms, but are more challenging to interpret. Few studies have compared these two different approaches to determine which yields the most relevant information. This study compared the kinematic patterns during gait of six total knee arthroplasty (TKA) subjects (10 TKA knees), to a group of 10 age-matched asymptomatic control subjects (19 control knees). An eight-camera Vicon M-cam system was used to track movement and compute joint angles. Group differences in parameterization (max and min peaks) values and principal component scores were tested using one-way ANOVA and Kruskal-Wallis tests. Using parameterization, the TKA group was characterized by reduced hip extension, increased hip flexion, increased anterior pelvic tilt, increased trunk tilt, and reduced sagittal ankle angles compared to the control group. Waveform analysis, by means of PCA, showed-magnitude shifts in sagittal ankle waveforms between groups, rather than solely reporting differences in peaks. Waveform analysis also indicated a significant shift in the magnitude of the entire waveform for hip angles, pelvic tilt, and trunk tilt, indicating no change in range of motion between groups, but rather a change in the way in which range of motion is achieved at the hip. This study has identified several gait variables that were significantly different between the TKA and control groups. Our results suggest that waveform analysis is effective at identifying magnitude shifts as sources of variability between groups, which would not necessarily be analyzed using conventional parameterization techniques unless one knew a priori where the variability would exist.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2024YFC2510400)Key Research and development projects of Shanxi province(202202150401019)the Central Government Guides Local Science and Technology Development Funds(Grant No.YDZJSX2022B011).
文摘To the Editor:Anterior cruciate ligament(ACL)rupture is a frequent knee injury that modifies knee joint kinematics,including intra-articular motions and forces,leading to recurrent functional instability of the knee.With an estimated 200,000 ACL ruptures annually in the United States,ACL ruptures are prevalent,especially in young,physically active individuals.[1]Restoring knee morphology,stability,and function is the aim of conventional therapy,which is ACL reconstruction(ACLR).[2]Previous studies have evaluated gait function at different time points before and after ACLR to quantify impairments in movement patterns and knee joint biomechanics.[3]These investigations have consistently revealed substantial alterations in gait patterns induced by ACLR,with recovery persisting for at least 6 months post-procedure.[4]Majewska et al[4]pointed out that most studies focus on short-term follow-up within 6 months after surgery,while time-dependent changes in long-term dynamic functional recovery remain poorly studied.Accordingly,we aimed to perform gait analysis both pre-ACLR and throughout the 12 months postoperatively,complemented by standard assessments of knee joint function.
文摘The use of parameterization in assessing gait waveforms has been widely accepted, although it is recognized that this approach excludes the majority of information contained in the waveform. Waveform analysis techniques, such as principal component analysis (PCA), have gained popularity in recent years as a more effective approach to extracting important information from human movement waveforms, but are more challenging to interpret. Few studies have compared these two different approaches to determine which yields the most relevant information. This study compared the kinematic patterns during gait of six total knee arthroplasty (TKA) subjects (10 TKA knees), to a group of 10 age-matched asymptomatic control subjects (19 control knees). An eight-camera Vicon M-cam system was used to track movement and compute joint angles. Group differences in parameterization (max and min peaks) values and principal component scores were tested using one-way ANOVA and Kruskal-Wallis tests. Using parameterization, the TKA group was characterized by reduced hip extension, increased hip flexion, increased anterior pelvic tilt, increased trunk tilt, and reduced sagittal ankle angles compared to the control group. Waveform analysis, by means of PCA, showed-magnitude shifts in sagittal ankle waveforms between groups, rather than solely reporting differences in peaks. Waveform analysis also indicated a significant shift in the magnitude of the entire waveform for hip angles, pelvic tilt, and trunk tilt, indicating no change in range of motion between groups, but rather a change in the way in which range of motion is achieved at the hip. This study has identified several gait variables that were significantly different between the TKA and control groups. Our results suggest that waveform analysis is effective at identifying magnitude shifts as sources of variability between groups, which would not necessarily be analyzed using conventional parameterization techniques unless one knew a priori where the variability would exist.
