Gait stability at early stages of multiple sclerosis using different data sources

BACKGROUND: People at early stages of multiple sclerosis have subtle balance problems that may affect gait stability. However, differences in methods of determining stability such as sensor type and placements, may lead to different results and affect their interpretation when comparing to controls and other studies. QUESTIONS: Do people with multiple sclerosis (PwMS) exhibit lower gait stability? Do location and type of data used to calculate stability metrics affect comparisons? METHODS: 30 PwMS with no walking impairments as clinically measured and 15 healthy controls walked on a treadmill at 1.2 ms-1 while 3D acceleration data was obtained from sacrum, shoulder and cervical markers and from an accelerometer placed at the sacrum. The local divergence exponent was calculated for the four data sources. An ANOVA with group (multiple sclerosis and control) and data source as main factors was used to determine the effect of disease, data source and their interaction on stability metrics. RESULTS: PwMS walked with significantly less stability according to all sensors (no interaction). A significant effect of data source on stability was also found, indicating that the local divergence exponent derived from sacrum accelerometer was lower than that derived from the other 3 sensor locations. SIGNIFICANCE: PwMS with no evident gait impairments are less stable than healthy controls when walking on a treadmill. Although different data sources can be used to determine MS-related stability deterioration, a consensus about location and data source is needed. The local divergence exponent can be a useful measure of progression of gait instability at early stages of MS

Increased ankle muscle coactivation in the early stages of multiple sclerosis

Background: Neural damage at early stages of multiple sclerosis (MS) can subtly affect gait muscle activation patterns. Detecting these changes using current clinical tools, however, is not possible. We propose using muscle coactivation measures to detect these subtle gait changes. This may also help in identifying people with MS (PwMS) that may benefit from strategies aimed at preventing further mobility impairments. Objective: We aimed to determine if coactivation of ankle muscles during gait is greater in PwMS with Expanded Disability Status Scale (EDSS) score <3.5. A secondary aim is to determine whether coactivation increases are speed dependent. Methods: For this study 30 PwMS and 15 healthy controls (HC) walked on a treadmill at 1.0 m/s, 1.2 m/s and 1.4 m/s. Electromyography was recorded from the tibialis anterior (TA), soleus (SO) and lateral gastrocnemius (LG). The coactivation index was calculated between SO/TA and LG/TA. Ankle kinematics data were also collected. Results: Compared with HC, PwMS exhibited significantly greater SO/TA and LG/TA coactivation, which was greater during early stance and swing phases (p < .01). Speed did not affect coactivation except during early stance. Ankle kinematic changes were also observed. Conclusion: PwMS exhibited greater ankle muscles coactivation than controls regardless of the speed of walking. These changes in muscle activation may serve as a biomarker of neurodegeneration occurring at early stages of the disease

Increased ankle muscle coactivation in the early stages of multiple sclerosis

Background: Neural damage at early stages of multiple sclerosis (MS) can subtly affect gait muscle activation patterns. Detecting these changes using current clinical tools, however, is not possible. We propose using muscle coactivation measures to detect these subtle gait changes. This may also help in identifying people with MS (PwMS) that may benefit from strategies aimed at preventing further mobility impairments. Objective: We aimed to determine if coactivation of ankle muscles during gait is greater in PwMS with Expanded Disability Status Scale (EDSS) score <3.5. A secondary aim is to determine whether coactivation increases are speed dependent. Methods: For this study 30 PwMS and 15 healthy controls (HC) walked on a treadmill at 1.0 m/s, 1.2 m/s and 1.4 m/s. Electromyography was recorded from the tibialis anterior (TA), soleus (SO) and lateral gastrocnemius (LG). The coactivation index was calculated between SO/TA and LG/TA. Ankle kinematics data were also collected. Results: Compared with HC, PwMS exhibited significantly greater SO/TA and LG/TA coactivation, which was greater during early stance and swing phases (p < .01). Speed did not affect coactivation except during early stance. Ankle kinematic changes were also observed. Conclusion: PwMS exhibited greater ankle muscles coactivation than controls regardless of the speed of walking. These changes in muscle activation may serve as a biomarker of neurodegeneration occurring at early stages of the disease

Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis

Subtle gait and balance dysfunction is a precursor to loss of mobility in multiple sclerosis (MS). Biomechanical assessments using advanced gait and balance analysis technologies can identify these subtle changes and could be used to predict mobility loss early in the disease. This update critically evaluates advanced gait and balance analysis technologies and their applicability to identifying early lower limb dysfunction in people with MS. Non-wearable (motion capture systems, force platforms, and sensor-embedded walkways) and wearable (pressure and inertial sensors) biomechanical analysis systems have been developed to provide quantitative gait and balance assessments. Non-wearable systems are highly accurate, reliable and provide detailed outcomes, but require cumbersome and expensive equipment. Wearable systems provide less detail but can be used in community settings and can provide real-time feedback to patients and clinicians. Biomechanical analysis using advanced gait and balance analysis technologies can identify changes in gait and balance in early MS and consequently have the potential to significantly improve monitoring of mobility changes in MS