An active lifestyle can mitigate physical decline and cognitive impairment in older adults. Regular walking exercises for older individuals result in enhanced balance and reduced risk of falling. In this article, we present a study on gait monitoring for older adults during walking using an integrated system encompassing an assistive robot and wearable sensors. The system fuses data from the robot onboard Red Green Blue plus Depth (RGB-D) sensor with inertial and pressure sensors embedded in shoe insoles, and estimates spatiotemporal gait parameters and dynamic margin of stability in real-time. Data collected with 24 participants at a community center reveal associations between gait parameters, physical performance (evaluated with the Short Physical Performance Battery), and cognitive ability (measured with the Montreal Cognitive Assessment). The results validate the feasibility of using such a portable system in out-of-the-lab conditions and will be helpful for designing future technology-enhanced exercise interventions to improve balance, mobility, and strength and potentially reduce falls in older adults.

In this paper, a parametric analysis of the inverse dynamics of an upright partially unloaded walking is performed. This motion is produced through a gait-training machine emulating the over-ground walking using a body weight support mechanism and a cable-driven robot. The input motion is the kinematics of a normal gait, and the ultimate output result is the required tensions to be generated by the cable robot in order to drive the lower limb. The dynamic analysis is carried out based on the Newton–Euler approach. A Matlab Simscape model is also built to validate the analytical results. The obtained dynamic model is used to investigate the effect of the variation of the gait simulation parameters on the actuation wrench and the cable tensions. The obtained results could be used to determine the optimal design of the gait trainer actuators and they are useful in estimating optimal gait training parameters.

In this paper, we investigate dynamic walking as a convergence to the system's own limit cycles, not to artificially generated trajectories, which is one of the lessons in the concept of passive dynamic walking. For flexible walking, gait transitions can be performed by moving from one limit cycle to another one, and thus, the flexibility depends on the range in which limit cycles exist. To design a bipedal walker based on this approach, we explore period-1 passive limit cycles formed by natural dynamics and analyze them. We use a biped model with knees and point feet to perform numerical simulations by changing the center of mass locations of the legs. As a result, we obtain mass distributions for the maximum flexibility, which can be attained from very limited location sets. We discuss the effect of parameter variations on passive dynamic walking and how to improve robot design by analyzing walking performance. Finally, we present a practical application to a real bipedal walker, designed to exhibit more flexible walking based on this study.

Biomechanical investigation into locomotor pathology in commercial pigs is lacking despite this being a major concern for the industry. Different floor types are used in modern, intensive pig production systems at different stages of the pigs’ production cycle. The general perception holds that slatted and/or hard solid concrete surfaces are inferior to soft straw-covered floors regarding healthy musculoskeletal development. Previous studies have compared pigs housed on different floor types using clinical, subjective assessment of leg weakness and lameness. However, reliability studies generally report a low repeatability of clinical lameness scoring. The objective of this study was to quantitatively assess the long-term effect of pen floors, reflected in the biomechanical gait characteristics and associated welfare of the pigs. A cohort of 24 pigs housed on one of three different floor types was followed from 37 to 90 kg average liveweight, with gait analysis (motion capture) starting at 63 kg. The three floor types were fully slatted concrete, partly slatted concrete and deep straw-bedded surfaces, all located within the same building. Pigs underwent five repeated camera-based motion captures, 7 to 10 days apart, during which 3D coordinate data of reflective skin markers attached to leg anatomical landmarks were collected. Pigs walked on the same solid concrete walkway during captures. One-way ANOVA and repeated measures ANOVA were used to analyse the gait data. Results revealed changes over time in the spatiotemporal gait pattern which were similar in magnitude and direction for the pigs from different floor types. Significant increases in elbow joint flexion with age were observed in all pigs (P⩽0.050; +6°). There were few differences between floor groups, except for the step-to-stride ratio in the hind legs being more irregular in pigs housed on partly slatted floors (P=0.012; 3.6 times higher s.d.) compared with those on 5 to 10 cm straw-bedding in all pen areas. As the level of clinical problems was generally low in this cohort, it may be that floors elicit problems only when there is a primary predisposing factor increasing weakness in susceptible tissues.

The variability in dairy cow gait characteristics, determined by measurements of footprints (trackway measurements), was analysed. Seven gait parameters were determined from 32 non-lame dairy cows during free-speed walking on a slatted concrete walkway. The footprints were revealed by application of a thin lime powder-slurry layer to the walkway surface. The cows were observed on two test occasions with a 3-week interval, with measurements from four consecutive strides used within each test session. The variance components for cow, test and cow–test interaction were estimated by a residual (restricted) maximum likelihood method. The percentage of each variance component was calculated to assess the relative impact of each factor on total variance. Between-test variation was generally low, suggesting that cows maintain the same average gait pattern, at least over a 3-week period. The proportion of within-test variation was considerable for most trackway measurements. Stride length, step angle, step width and tracking (overlap) showed low to moderate within-test variation (12% to 27%), whereas for mediolateral displacement of rear feet and step length it was rather high (54% and 62%, respectively). Within-test variation in step asymmetry was very high (77%), suggesting the occurrence of natural, non-systematic changes in inter-limb coordination in non-lame cows. For better understanding the gait pattern in non-lame cows, linear associations between the trackway measurements and with body size were assessed. It was concluded that trackway measurements were able to describe the gait pattern in walking cows under dairy farm conditions. However, considering the relatively high within-test variation in gait, several strides should be used to obtain a representative gait pattern.

The most popular techniques used for studying equine kinematics are videographic recording combined with the analysis using a commercial software package or optoelectronic systems based on emission and detection of infrared or visible light. Such systems can be expensive, complicated to use and their use may be restricted to indoor use (in the case of infrared systems) or a limited number of strides when used outdoors. Recently, there has been considerable interest in monitoring motion using inertial measuring systems. The purpose of the present study was to determine the accuracy of the Pegasus system (European Technology for Business Ltd., Codicote, UK), which determines stride frequency directly when mounted on the withers. Eight horses of different breeds and sizes (447–588 kg) were studied at walk, trot and two speeds at canter on a treadmill. Simultaneous measurements of stride were made using the Pegasus and ProReflex motion capture systems. Mean stride frequencies (n = 8 horses) for the ProReflex and Pegasus systems at walk (0.86 ± 0.05 and 0.87 ± 0.05 strides per second, respectively), trot (1.36 ± 0.07 and 1.36 ± 0.07 strides per second, respectively) and canter (7 m s− 1: 1.92 ± 0.05 and 1.92 ± 0.05 strides per second, respectively; 8 m s− 1: 1.93 ± 0.05 and 1.94 ± 0.05 strides per second, respectively) were not significantly different (P>0.05). The mean difference between the two systems for all four speeds was − 0.002 strides per second (lower 95% CI: − 0.016; upper 95% CI: 0.011; P = 0.309). In conclusion, the differences between stride frequency measurements made with the Pegasus and ProReflex systems in horses exercising at walk, trot and slow canter on a treadmill are < 1% and not likely to be of physiological significance.

Temporal stride characteristics of the canter were compared between performance-shod (PS) and light-shod (LS) Tennessee Walking Horses, which generally differ in training and shoeing methods. Four consecutive strides for ten PS and ten LS horses were filmed (30 Hz), and frame-by-frame analysis performed to determine stride duration and individual limb stance duration. Also analysed was the percentage of stride duration devoted to single, bipedal or tripedal limb support. Footfall sequence for PS was trailing hind (TrH), leading hind (LdH), trailing fore (TrF) and leading fore (LdF), whereas footfall sequence for LS horses varied, with the majority of LS performing a sequence of TrH–TrF–LdH–LdF. Stride duration was greater for PS. As a percentage of stride duration, PS demonstrated greater duration of TrF and LdF, while LS demonstrated greater LdH duration. Hind and fore single limb support, and tripedal support, were greater for LS; however, PS utilized bipedal support to a larger extent than LS. Hind or forelimb bipedal support was demonstrated only in PS, while only LS demonstrated lateral bipedal support. Thus, while both performance- and light-shod Tennessee Walking Horses perform the canter, temporal variables for this gait differ dramatically between the two groups.