The energetic basis for smooth human arm movements

The central nervous system plans human reaching movements with stereotypically smooth kinematic trajectories and fairly consistent durations. Smoothness seems to be explained by accuracy as a primary movement objective, whereas duration seems to economize energy expenditure. But the current understanding of energy expenditure does not explain smoothness, so that two aspects of the same movement are governed by seemingly incompatible objectives. Here we show that smoothness is actually economical, because humans expend more metabolic energy for jerkier motions. The proposed mechanism is an underappreciated cost proportional to the rate of muscle force production, for calcium transport to activate muscle. We experimentally tested that energy cost in humans (N=10) performing bimanual reaches cyclically. The empirical cost was then demonstrated to predict smooth, discrete reaches, previously attributed to accuracy alone. A mechanistic, physiologically measurable, energy cost may therefore explain both smoothness and duration in terms of economy, and help resolve motor redundancy in reaching movements.

Control of Upper Limb Active Prosthesis Using Surface Electromyography

Electromyographic prosthesis with higher degrees of freedom is an expanding area of research. In this paper, active prosthesis with four degrees of freedom has been investigated, which can be used to fit a limb with amputation below elbow. The system comprises of multichannel inputs which correspond to the flexion and extension as well as supination and pronation. To find maximum surface neural activity, accurate placement of electrodes has been carried out on 10 subjects aged between 22-30 years. Signals (0-500 hertz) acquired from contracting voluntary muscles with minimum cross talk and common mode noise. Clean filtered EMG signal is then amplified precisely. Finally digitization is being done to drive bionic hand. Practical demonstration on a simple DC motor proved providential using this method for the two motions of an actual human arm. EMG Signals emanating from muscles dedicated to individual fingers have been recorded. Moreover modern classifiers; KNN and NN have been investigated carefully with selected features through different time and noise levels.

Operation Safety of a 2-DoF Planar Mechanism for Arm Rehabilitation

The operation safety of rehabilitation devices must be addressed early in the development process and before being tested on people. In this paper, the operation safety of a 2-DoF (degrees of freedom) planar mechanism for arm rehabilitation is addressed. Then, the safety and efficiency of the device operation is assessed through the Transmission Index (TI) distribution in its workspace. Furthermore, the produced stresses on the human arm are assessed via the FEM (finite element method) when the rehabilitation device reaches five critical positions within its workspace. The TI distribution showed that the proposed design has a proper behaviour from a force transmission point of view, avoiding any singular configuration that might cause a control failure and subsequent risk for the user and supporting the user’s motion with a good efficiency throughout its operational workspace. The FEM analysis showed that Nurse operation is safe for the human arm since a negligible maximum stress of 6.55 × 103 N/m2 is achieved by the human arm when the device is located on the evaluated critical positions.

Combined Feedback Feedforward Control of a 3-Link Musculoskeletal System Based on the Iterative Training Method

The investigation and study of the limbs, especially the human arm, have inspired a wide range of humanoid robots, such as movement and muscle redundancy, as a human motor system. One of the main issues related to musculoskeletal systems is the joint redundancy that causes no unique answer for each angle in return for an arm’s end effector’s arbitrary trajectory. As a result, there are many architectures like the torques applied to the joints. In this study, an iterative learning controller was applied to control the 3-link musculoskeletal system’s motion with 6 muscles. In this controller, the robot’s task space was assumed as the feedforward of the controller and muscle space as the controller feedback. In both task and muscle spaces, some noises cause the system to be unstable, so a forgetting factor was used to a convergence task space output in the neighborhood of the desired trajectories. The results show that the controller performance has improved gradually by iterating the learning steps, and the error rate has decreased so that the trajectory passed by the end effector has practically matched the desired trajectory after 1000 iterations.

A novel human-robot interface based on soft skin sensor designed for the upper-limb exoskeleton

The upper-limb exoskeleton is capable of enhancing human arm strength beyond normal levels, whereas deriving the operator’s desired action straightforward turns out to be one of the significant difficulties facing human-robot interaction research. In the study, the human-robot interface was presented to regulate the exoskeleton tracking human elbow motion trajectory that employed the contact force signals between the exoskeleton and its operator as the primary means of information transportation. The signals were recorded by adopting the novel soft skin sensors attached to the bracket on the exoskeleton linkage, which could reflect the human arm motion intention through the virtual admittance model and adaptive control. Subsequently, a 1-DOF upper-limb exoskeleton was designed to illustrate the performance of the proposed sensor and the interaction control method in the human-robot cooperation experiment.

Motor learning in reaching tasks leads to homogenization of task space error distribution

A human arm, up to the wrist, is often modelled as a redundant 7 degree-of-freedom serial robot. Despite its inherent nonlinearity, we can perform point-to-point reaching tasks reasonably fast and with reasonable accuracy in the presence of external disturbances and noise. In this work, we take a closer look at the task space error during point-to-point reaching tasks and learning during an external force-field perturbation. From experiments and quantitative data, we confirm a directional dependence of the peak task space error with certain directions showing larger errors than others at the start of a force-field perturbation, and the larger errors are reduced with repeated trials implying learning. The analysis of the experimental data further shows that a) the distribution of the peak error is made more uniform across directions with trials and the error magnitude and distribution approaches the value when no perturbation is applied, b) the redundancy present in the human arm is used more in the direction of the larger error, and c) homogenization of the error distribution is not seen when the reaching task is performed with the non-dominant hand. The results support the hypothesis that not only magnitude of task space error, but the directional dependence is reduced during motor learning and the workspace is homogenized possibly to increase the control efficiency and accuracy in point-to-point reaching tasks. The results also imply that redundancy in the arm is used to homogenize the workspace, and additionally since the bio-mechanically similar dominant and non-dominant arms show different behaviours, the homogenizing is actively done in the central nervous system.

Neuromuscular Analysis Of Various Release Mechanisms In Archery: A Study Of The Preparatory Response Between Trigger And Back-Tension Releases

Archery was originally a tool for hunting but since has been transformed into a sport. Archery technology has evolved with little focus as to its effect on humans. Archery requires high levels of concentration and static muscle activity, which has not been analyzed to be successful. By observing the muscle activity in the bow arm and measuring the vibration effects from the bow, it was determined a presence of an impact to the human arm, which the human then creates anticipation for and braces against. To mitigate this anticipation, another technology was introduced to create a surprise factor in the shooting. To reduce the frequency of archers bracing up for the shot, knowledge of when the shot is going off was taken away. It was observed that the new technology did introduce a surprise factor, but it did not reduce the occurrences of preparatory muscle activation in the human arm.