Hand Position Error Research Articles

Transformation from arm joint coordinates to hand external coordinates explains non-uniform precision of hand position sense in horizontal workspace

People perceive hand position in horizontal workspace more precisely in radial than in azimuth directions and closer to the body than farther away. Current explanations for this position sense non-uniformity include spatial asymmetry in arm proprioceptive activities and/or cortex maps, experience-dependent learning, arm posture, and others. Here we investigated contributions to this non-uniformity of a posture-dependent transformation from arm joint angles, sensed by arm proprioceptors, to hand position. We measured precision of hand position sense in a bimanual hand mirror-position matching task at four horizontal targets forming a square in front of the body in 11 blindfolded individuals. We found lower hand precision in azimuth than in radial direction, higher azimuth precision at close targets, and higher radial precision at distant targets. We then theoretically analyzed the transformation of random angle errors at shoulder and elbow into hand position random errors in a horizontal plane and obtained similar distributions of hand position errors. The predicted and experimental hand-precision ellipse orientations, but not ellipse shapes or sizes, were highly correlated and were nearly orthogonal to arm stiffness ellipse orientations reported in the literature. We concluded that the joint-to-hand coordinate transformation is responsible for the non-uniform precision of hand position sense.

Feedback Control of Functional Electrical Stimulation for 2-D Arm Reaching Movements.

Functional electrical stimulation (FES) can be used as a neuroprosthesis in which muscles are stimulated by electrical pulses to compensate for the loss of voluntary movement control. Modulating the stimulation intensities to reliably generate movements is a challenging control problem. This paper introduces a feedback controller for a multi-muscle FES system to control hand movements in a 2-D (table-top) task space. This feedback controller is based on a recent human motor control model, which uses muscle synergies to simplify its calculations and improve the performance. This synergy-based controller employs direct relations between the muscle synergies and the produced hand force, therefore allowing for the real-time calculation of six muscle stimulation levels required to reach an arbitrary target. The experimental results show that this control scheme can perform arbitrary point-to-point reaching tasks in the 2-D task space in real time, with an average of ~2 cm final hand position error from the specified targets. The success of this prototype demonstrates the potential of the proposed method for the feedback control of functional tasks with FES.

Feedback control of functional electrical stimulation for arbitrary upper extremity movements.

Functional electrical stimulation (FES) is a type of neuroprosthesis in which muscles are stimulated by electrical pulses in order to compensate for the loss of voluntary movement control. Modulating the stimulation intensities to reliably generate movements is a challenging control problem. For the first time, this paper presents a feedback controller for FES to control arm movements in a 2D (table-top) task space. This feedback controller is based on a recent human motor control model, which uses muscle synergies to simplify the calculations and improve control performance. The experimental results show that this control scheme can produce arbitrary movements in the 2D task space, with less than 2 cm hand position error from the specified targets.

Supplemental vibrotactile feedback control of stabilization and reaching actions of the arm using limb state and position error encodings

BackgroundDeficits of kinesthesia (limb position and movement sensation) commonly limit sensorimotor function and its recovery after neuromotor injury. Sensory substitution technologies providing synthetic kinesthetic feedback might re-establish or enhance closed-loop control of goal-directed behaviors in people with impaired kinesthesia.MethodsAs a first step toward this goal, we evaluated the ability of unimpaired people to use vibrotactile sensory substitution to enhance stabilization and reaching tasks. Through two experiments, we compared the objective and subjective utility of two forms of supplemental feedback – limb state information or hand position error – to eliminate hand position drift, which develops naturally during stabilization tasks after removing visual feedback.ResultsExperiment 1 optimized the encoding of limb state feedback; the best form included hand position and velocity information, but was weighted much more heavily toward position feedback. Upon comparing optimal limb state feedback vs. hand position error feedback in Experiment 2, we found both encoding schemes capable of enhancing stabilization and reach performance in the absence of vision. However, error encoding yielded superior outcomes - objective and subjective - due to the additional task-relevant information it contains.ConclusionsThe results of this study have established the immediate utility and relative merits of two forms of vibrotactile kinesthetic feedback in enhancing stabilization and reaching actions performed with the arm and hand in neurotypical people. These findings can guide future development of vibrotactile sensory substitution technologies for improving sensorimotor function after neuromotor injury in survivors who retain motor capacity, but lack proprioceptive integrity in their more affected arm.

Shoulder position sense in volleyball players with infraspinatus atrophy secondary to suprascapular nerve neuropathy.

Isolated infraspinatus atrophy (IIA) is a common condition among overhead-activity athletes, which affects the hitting shoulder and is caused by suprascapular nerve injury. As the suprascapular nerve is a mixed nerve, such damage could lead to reduced afferent proprioceptive information and impaired shoulder sensorimotor control. This study aimed to evaluate the proprioception of the shoulder with IIA, through the assessment of shoulder position sense. The shoulder position sense was assessed in 24 professional volleyball players (12 players with IIA and 12 healthy players) with a blind dynamic shoulder repositioning test (all participants were blindfolded during the test). Three functional glenohumeral movements were tested as follows: abduction, forward flexion, and a combination of abduction and external rotation. In all three tested movements, the affected shoulder of players with isolated infraspinatus atrophy showed significantly higher hand position error than the healthy contralateral (P<10-3 , for all movements) and the healthy control group hitting shoulder (P<10-3 , for abduction and flexion; P=.02, for combined movement of abduction and external rotation). The study highlights a reduced sense of position of the hitting shoulder in professional volleyball players with IIA secondary to suprascapular nerve palsy. The higher hand position error of the pathologic shoulder suggests an impairment of the shoulder sensorimotor control system, which likely results from reduced afferent proprioceptive information. Deficient afferent proprioceptive information may result in poor accuracy in descending motor commands and impairment of the shoulder neuromuscular function, leading to reduced shoulder functional stability and increased risk of injury.

Similarities in the Neural Control of the Shoulder and Elbow Joints Belie Their Structural Differences

Movement of the hand in three dimensional space is primarily controlled by the orientation of the shoulder and elbow complexes. Due to discrepancies in proprioceptive acuity, overlap in motor cortex representation and grossly different anatomies between these joints, we hypothesized that there would be differences in the accuracy of aimed movements between the two joints. Fifteen healthy young adults were tested under four conditions – shoulder motion with the elbow constrained and unconstrained, and elbow motion with the shoulder constrained and unconstrained. End point target locations for each joint were set to coincide with joint excursions of 10, 20 or 30 degrees of either the shoulder or elbow joint. Targets were presented in a virtual reality environment. For the constrained condition, there were no significant differences in angular errors between the two joints, suggesting that the central nervous system represents linked segment models of the limb in planning and controlling movements. For the unconstrained condition, although angle errors were higher, hand position errors remained the same as those of the constrained trials. These results support the idea that the CNS utilizes abundant degrees of freedom to compensate for the potentially different contributions to end-point errors introduced by each joint.

Comparison of the errors in basic life support performance after training using the 2000 and 2005 ERC guidelines

The importance of immediate cardiopulmonary resuscitation (CPR) and defibrillation after cardiac arrest is established. The 2005 European Resuscitation Council (ERC) guidelines were altered to try to improve survival after cardiac arrest. This observational study compares the errors in basic life support (BLS) performance after training using the 2000 or 2005 guidelines. First-year healthcare students at the University of Birmingham, United Kingdom, were taught adult BLS in a standardised 8-h course: an historical group with previous ERC guidelines (Old), the other with 2005 ERC guidelines (New). 2537 (Old 1773; New 764) students were trained and assessed in BLS. There was no difference in overall error rate between Old and New (5.53% vs. 6.70% ( p > 0.05)) or adherence to the sequence of the respective BLS algorithm. The New group (“hands in centre of the chest”) had significantly more erroneous hand positions compared to the Old group (5.23% vs. 1.64%, p < 0.001). The 2005 ERC guidelines do not significantly improve correct BLS performance. Removal of hand placement measurement results in a significant increase in hand position errors. The clinical benefit of an increased number of compressions impaired by worsened hand positioning is unknown and requires further study.

Dynamic upper limb proprioception in multidirectional shoulder instability.

The ability of subjects with multidirectional shoulder instability to use proprioception to complete a series of upper limb repositioning tasks was investigated. Twelve subjects with multidirectional instability and 12 control subjects were blindfolded and instructed to use proprioception to reproduce a self-selected target position as accurately as possible. Subjects completed 10 repetitions for each limb using three distinct upper limb movements: overhead reaching, scapular plane pointing, and humeral external rotation with abduction. A three-dimensional video motion analysis system tracked limb position and determined spatial hand position error. Subjects with multidirectional shoulder instability showed significantly greater hand position error than control subjects. No hand position error differences were found between the symptomatic and the asymptomatic limbs of subjects in the instability group. Inter-repetition error for subjects in both groups improved significantly during the first three movement cycles. These results suggest that after movement initiation, dynamic proprioception was a factor in improving hand position accuracy in both groups, but to a lesser degree in subjects with multidirectional instability. Consequently, subjects with multidirectional instability may have a reduced capacity to use proprioception to refine and control the motor output of the upper limb.

Coordinate transformation learning of hand position feedback controller with time delay

The speed, accuracy, and adaptability of human movement depends on the brain performing an inverse kinematics transformation—i.e., a transformation from visual to joint angle coordinates—based on learning from experience. In human visually guided motion control, it is important to learn a feedback controller for the hand position error. This paper proposes two novel models that learn coordinate transformations of the human visual feedback controller with time delay. The proposed models redress drawbacks in current models because they do not rely on complex signal switching, which does not seem neurophysiologically plausible.

A human system learning model for solving the inverse kinematics problem by direct inverse modeling

AbstractThe problem of computing a human arm posture that will take the hand to a desired hand position given by vision is called an inverse kinematics problem. To solve this problem, the human nervous system has a system for solving the inverse kinematics problem computing the proper joint angles from the desired hand position.Although the direct inverse modeling method is popular for the acquisition of an inverse kinematics model, a sufficient inverse model cannot be obtained for such systems with many‐to‐one input‐output correspondence as a human arm system.This paper, proposes a new model of a human inverse kinematics solver which uses the learned inverse model of the linearized model of the human arm. This inverse model transforms the hand position error to the update vector of the joint angles. The solver inverse kinematics problems by using the hand position error feedback. The performance of the solver is shown using numerical simulations.

Resolved Motion Adaptive Control for Mechanical Manipulators

This paper presents the development of a resolved motion adaptive control which adopts the ideas of “resolved motion rate control” [8] and “resolved motion acceleration control” [10] to control a manipulator in Cartesian coordinates for various loading conditions. The proposed adaptive control is performed at the hand level and is based on the linearized perturbation system along a desired hand trajectory. The controlled system is characterized by feedforward and feedback components which can be computed separately and simultaneously. The feedforward component resolves the specified positions, velocities, and accelerations of the hand into a set of values of joint positions, velocities, and accelerations from which the nominal joint torques are computed using the Newton-Euler equations of motion to compensate all the interaction forces among the various joints. The feedback component consisting of recursive least square identification scheme and an optimal adaptive self-tuning controller for the linearized system computes the perturbation torques which reduce the manipulator hand position and velocity errors along the nominal hand trajectory. The feasibility of implementing the proposed adaptive control using present day low-cost microprocessors is explored.

The Use of 8mm Loop Films To Teach the Identification of Clarinet Fingering, Embouchure, and Hand Position Errors

The Use of 8mm Loop Films To Teach the Identification of Clarinet Fingering, Embouchure, and Hand Position Errors