Biology subjects

Riemer, R.

Publications and source records attributed to Riemer, R..

3 recordsLinked to original sources

bioRxiv2023

Validation of marker-less pose estimation for 3D kinematics during upper limb reaching

Kinematic analysis of movement following brain damage is key for diagnosing motor impairments and for recovery assessment. Advances in computer vision offer novel marker-less tracking tools that could be implemented in the clinic due to their simple operation and affordability. An important question that arises is whether marker-less technologies are sufficiently accurate compared to well established marker-based technologies. This study aims to perform validation of kinematic assessment using two high-speed cameras and a 3D pose estimation model. Four participants performed reaching movements with the upper limb between fixed targets, in different velocities. Movement kinematics were simultaneously measured using the DeepBehavior model and marker-based optical motion capture (QTM), as a gold standard. The differences in corresponding joint angles, estimated from the two different methods throughout the analysis, are presented as a mean absolute error (MAE) of the elbow angle. Quantitatively, the MAE of all movements was relatively small across velocity and joints (~2{degrees}). In a condition where the movements were made towards the DeepBehavior cameras, and the view of the elbow was occluded in one of the cameras, the errors were higher. In conclusion, the results demonstrated that marker-less motion capture is a valid alternative to marker-based motion capture. Inaccuracies of the DeepBehavior system could be explained by occlusions of key-points and are not associated with failure of the pose estimation algorithm.

bioengineering↗

bioRxiv2020

Mechanics and energetics of walking and running up and downhill: A joint-level perspective to guide design of lower-limb exoskeletons

Lower-limb wearable robotic devices can provide effective assistance to both clinical and healthy populations; however, how assistance should be applied in different gait conditions and environments is still unclear. We suggest a biologically-inspired approach derived from knowledge of human locomotion mechanics and energetics to establish a roadmap for wearable robot design. In this study, we characterize the changes in joint mechanics during both walking and running across a range of incline/decline grades and then provide an analysis that informs the development of lower-limb exoskeletons capable of operating across a range of mechanical demands. Eight subjects (6M,2F) completed five walking (1.25 m -1) trials at -15%, -10%, 0%, 10%, and 15% grade and five running (2.25 m s-1) trials at -10%, -5%, 0%, 5%, and 10% grade on a treadmill. We calculated time-varying joint moment and power output for the ankle, knee, and hip. For each gait, we examined how individual limb-joints contributed to total limb positive, negative and net power across grades. For both walking and running, changes in grade caused a redistribution of joint mechanical power generation and absorption. From level to incline walking, the ankles contribution to limb positive power decreased from 44% on the level to 28% at 15% uphill grade (p < 0.0001) while the hips contribution increased from 27% to 52% (p < 0.0001). In running, regardless of the surface gradient, the ankle was consistently the dominant source of lower-limb positive mechanical power (47-55%). In the context of our results, we outline three distinct use-modes that could be emphasized in future lower-limb exoskeleton designs 1) Energy injection: adding positive work into the gait cycle, 2) Energy extraction: removing negative work from the gait cycle, and 3) Energy transfer: extracting energy in one gait phase and then injecting it in another phase (i.e., regenerative braking).

bioengineering↗

bioRxiv2018

Preferred walking speed on rough terrain; is it all about energetics?

Humans have evolved the ability to walk very efficiently. Further, humans prefer to walk at speeds that approximately minimize their metabolic energy expenditure per unit distance (i.e. gross cost of transport, COT). This has been found in a variety of population groups and other species. However, these studies were performed on smooth, level ground or on treadmills. We hypothesized that the objective function for walking is more complex than only minimizing the COT. To test this idea, we compared the preferred speeds and the relationships between COT and speed for people walking on both a smooth, level floor and a rough, natural terrain trail. Rough terrain presumably introduces other factors, such as stability, to the objective function. 10 healthy men walked on both a straight, flat, smooth floor and on an outdoor trail strewn with rocks and boulders. In both locations, subjects performed 6-8 trials at different speeds relative to their preferred speed. The COT-speed relationships were similarly U-shaped for both surfaces, but the COT values on rough terrain were approximately 215% greater. On the smooth surface, the preferred speed (1.24+/-0.14 m/sec) was 5.1% faster (p>0.05) than the speed that minimized COT (1.18 m/sec) but on rough terrain, the preferred speed (1.06+/-0.07 m/sec) was 6.2% slower (p>0.05) than the COT minimum speed (1.13 m/sec). This suggests that the objective function when walking on rough terrain includes additional factors such as stability.\n\nSummary statement: On rough terrain, humans do not choose their walking speed based on metabolic energy minimization alone.

evolutionary biology↗