Supervised walking exercise therapy improves gait biomechanics in patients with peripheral artery disease.

OBJECTIVE: In patients with peripheral artery disease (PAD), supervised exercise therapy is a first line of treatment because it increases maximum walking distances comparable with surgical revascularization therapy. Little is known regarding gait biomechanics after supervised exercise therapy. This study characterized the effects of supervised exercise therapy on gait biomechanics and walking distances in claudicating patients with PAD. METHODS: Forty-seven claudicating patients with PAD underwent gait analysis before and immediately after 6 months of supervised exercise therapy. Exercise sessions consisted of a 5-minute warmup of mild walking and stretching of upper and lower leg muscles, 50 minutes of intermittent treadmill walking, and 5 minutes of cooldown (similar to warmup) three times per week. Measurements included self-perceived ambulatory limitations measured by questionnaire, the ankle-brachial index (ABI), walking distance measures, maximal plantar flexor strength measured by isometric dynamometry, and overground gait biomechanics trials performed before and after the onset of claudication pain. Paired t-tests were used to test for differences in quality of life, walking distances, ABI, and maximal strength. A two-factor repeated measures analysis of variance determined differences for intervention and condition for gait biomechanics dependent variables. RESULTS: After supervised exercise therapy, quality of life, walking distances, and maximal plantar flexor strength improved, although the ABI did not significantly change. Several gait biomechanics parameters improved after the intervention, including torque and power generation at the ankle and hip. Similar to previous studies, the onset of claudication pain led to a worsening gait or a gait that was less like healthy individuals with a pain-free gait. CONCLUSIONS: Six months of supervised exercise therapy produced increases in walking distances and quality of life that are consistent with concurrent improvements in muscle strength and gait biomechanics. These improvements occurred even though the ABI did not improve. Future work should examine the benefits of supervised exercise therapy used in combination with other available treatments for PAD.

Linear and Nonlinear Measures of Postural Control in a Toddler With Cerebral Palsy: Brief Report.

PURPOSE: The purpose of this study was to describe changes in linear and nonlinear measures of postural control along with motor outcomes in a young child with cerebral palsy. SUMMARY OF KEY POINTS: Posturography in sitting and standing, the Gross Motor Function Measure-66 (GMFM-66), and the Early Clinical Assessment of Balance (ECAB) were performed prior to, during, and after physical therapy. The child demonstrated independent sitting throughout the study and developed independent standing during the study. He made improvements in the GMFM-66 and ECAB throughout the study. Higher average values were found in all linear and nonlinear measures in standing when compared to sitting, which may indicate less predictable movement due to less experience with standing. RECOMMENDATIONS FOR CLINICAL PRACTICE: Greater variability and lower predictability in postural control likely reflect early stages of skill acquisition. Research is needed to understand the optimal levels of movement variability and predictability.

Association of mechanical temporal summation of pain with muscle co-contraction during walking in people with knee osteoarthritis.

BACKGROUND: People with knee osteoarthritis walk with excessive muscle co-contraction that can accelerate disease progression. Central pain sensitization is common in people with knee osteoarthritis and may be related to walking patterns. The objective of this study was to examine the relation of central pain sensitization with muscle co-contraction during walking in people with knee osteoarthritis. METHODS: This study reports secondary analysis from baseline data of two clinical trials (n = 90 participants with knee osteoarthritis). The presence of central pain sensitization was measured by mechanical temporal summation at the patella and the wrist. Quadriceps and hamstrings activation was assessed using surface electromyography during walking at self-selected and fast paces. Muscle co-contraction indices for vastus medialis-medial hamstrings and vastus lateralis-lateral hamstrings muscle pairs were calculated during stance phases. Co-contraction outcomes were compared between people with and without mechanical temporal summation at each site, adjusting for age, sex, and body mass index. FINDINGS: People with mechanical temporal summation at the knee had greater vastus lateralis-lateral hamstrings co-contraction while walking at a fast pace (P = 0.04). None of the other differences was statistically significant, but the overall trends and effect sizes indicated greater co-contraction in people with temporal summation at the knee irrespective of gait phase, walking speed, or muscle pairs. INTERPRETATION: Central pain sensitization, assessed as mechanical temporal summation at the knee, is related to greater knee muscle co-contraction during fast walking in people with knee osteoarthritis. Thus, mitigating central sensitization may be an interventional target to reduce muscle co-contraction for people with knee osteoarthritis.

Filtering affects the calculation of the largest Lyapunov exponent.

The calculation of the largest Lyapunov exponent (LyE) requires the reconstruction of the time series in an N-dimensional state space. For this, the time delay (Tau) and embedding dimension (EmD) are estimated using the Average Mutual Information and False Nearest Neighbor algorithms. However, the estimation of these variables (LyE, Tau, EmD) could be compromised by prior filtering of the time series evaluated. Therefore, we investigated the effect of filtering kinematic marker data on the calculation of Tau, EmD and LyE using several different computational codes. Kinematic marker data were recorded from 37 subjects during treadmill walking and filtered using a low pass digital filter with a range of cut-off frequencies (23.5-2Hz). Subsequently, the Tau, EmD and LyE were calculated from all cut-off frequencies. Our results demonstrated that the level of filtering affected the outcome of the Tau, EmD and LyE calculations for all computational codes used. However, there was a more consistent outcome for cut-off frequencies above 10 Hz which corresponded to the optimal cut-off frequency that could be used with this data. This suggested that kinematic data should remain unfiltered or filtered conservatively before calculating Tau, EmD and LyE.