Individuals with unilateral transfemoral amputation depend on compensatory muscle and joint function to generate motion of the lower limbs, which can produce gait asymmetry; however, the functional role of the intact and residual limb muscles of transfemoral amputees in generating progression, support, and mediolateral balance of the body during walking is not well understood. The aim of this study was to quantify the contributions of the intact and the residual limb's contralateral muscles to body center of mass (COM) acceleration during walking in transfemoral amputees. Three-dimensional subject-specific musculoskeletal models of 6 transfemoral amputees fitted with a socket-type prosthesis were developed and used to quantify muscle forces and muscle contributions to the fore-aft, vertical, and mediolateral body COM acceleration using a pseudo-inverse ground reaction force decomposition method during over-ground walking. Anterior pelvic tilt and hip range of motion in the sagittal and frontal planes of the intact limb was significantly larger than those in the residual limb (p<0.05). The mean contributions of the intact limb hip muscles to body COM support, forward propulsion and mediolateral balance were significantly greater than those in the residual limb (p<0.05). Gluteus maximus contributed more to propulsion and support, while gluteus medius contributed more to balance than other muscles in the intact limb than the residual limb. The findings demonstrate the role of the intact limb hip musculature in compensating for reduced or absent muscles and joint function in the residual limb of transfemoral amputees during walking. The results may be useful in developing rehabilitation programs and design of prostheses to improve gait symmetry and mitigate post-operative musculoskeletal pathology.

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.

Laboratory gait analysis or three-dimensional gait analysis (3DGA), which uses motion capture, force plates and electromyography (EMG), has allowed a better understanding of the underlying mechanisms of gait deterioration in patients with multiple sclerosis (PwMS). This review will summarize the current knowledge on multiple sclerosis (MS)-related changes in kinematics (angles), kinetics (forces) and electromyographic (muscle activation) patterns and how these measures can be used as markers of disease progression. We will also discuss the potential causes of slower walking in PwMS and the implications for 3DGA. Finally, we will describe new technologies and methods that will increase precision and clinical utilization of 3DGA in PwMS. Overall, 3DGA studies have shown that functionality of the ankle joint is the most affected during walking and that compensatory actions to maintain a functional speed may be insufficient in PwMS. However, altered gait patterns may be a strategy to increase stability as balance is also affected in PwMS.

Body-worn sensors allow assessment of gait characteristics that are predictive of fall risk, both when measured during treadmill walking and in daily life. The present study aimed to assess differences as well as associations between fall-related gait characteristics measured on a treadmill and in daily life. In a cross-sectional study, trunk accelerations of 18 older adults (72.3 ± 4.5 years) were recorded during walking on a treadmill (Dynaport Hybrid sensor) and during daily life (Dynaport MoveMonitor). A comprehensive set of 32 fall-risk-related gait characteristics was estimated and compared between both settings. For 25 gait characteristics, a systematic difference between treadmill and daily-life measurements was found. Gait was more variable, less symmetric, and less stable during daily life. Fourteen characteristics showed a significant correlation between treadmill and daily-life measurements, including stride time and regularity (0.48 < r < 0.73; p < 0.022). No correlation between treadmill and daily-life measurements was found for stride-time variability, acceleration range and sample entropy in vertical and mediolateral direction, gait symmetry in vertical direction, and stability estimated as the local divergence exponent by Rosenstein’s method in mediolateral direction (r < 0.16; p > 0.25). Gait characteristics revealed less stable, less symmetric, and more variable gait during daily life than on a treadmill, yet about half of the characteristics were significantly correlated between conditions. These results suggest that daily-life gait analysis is sensitive to static personal factors (i.e., physical and cognitive capacity) as well as dynamic situational factors (i.e., behavior and environment), which may both represent determinants of fall risk.

Age-related balance impairments, particularly in mediolateral direction (ML) may cause falls. Sufficiently sensitive and reliable ML balance tests are, however, lacking. This study is aimed to determine (1) the effect of age on and (2) the reliability of ML balance performance using Center of Mass (CoM) tracking. Balance performance of 19 young (26±3 years) and 19 older (72±5 years) adults on ML-CoM tracking tasks was compared. Subjects tracked predictable and unpredictable target displacements at increasing frequencies with their CoM by shifting their weight sideward. Phase-shift (response delay) and gain (amplitude difference) between the CoM and target in the frequency domain were used to quantify performance. Thirteen older and all young adults were reassessed to determine reliability of balance performance measures. In addition, all older adults performed a series of clinical balance tests and conventional posturography was done in a sub-sample. Phase-shift and gain dropped below pre-determined thresholds (−90 degrees and 0.5) at lower frequencies in the older adults and were even lower below these frequencies than in young adults. Performance measures showed good to excellent reliability in both groups. All clinical scores were close to the maximum and no age effect was found using posturography. ML balance performance measures exhibited small but systematic between-session differences indicative of learning. The ability to accurately perform ML-CoM tracking deteriorates with age. ML-CoM tracking tasks form a reliable tool to assess ML balance in young and older adults and are more sensitive to age-related impairment than posturography and clinical tests.