Sensitivity Analysis of Dynamics System in the Upper Limb Movement Control

Volume 2: Biomedical and Biotechnology ◽

10.1115/imece2012-86094 ◽

2012 ◽

Author(s):

Kai Chen ◽

Richard A. Foulds

Keyword(s):

Sensitivity Analysis ◽

Upper Limb ◽

Impedance Control ◽

Muscle Length ◽

Movement Control ◽

Arm Movement ◽

Human Movement ◽

Limb Movement ◽

Feedback Information ◽

Analysis Of Dynamics

The dependence of muscle force on muscle length gives rise to a “spring–like” behavior which has been shown to play an important role during human movement. Neville Hogan (Hogan, 1985) proposed a mathematical model in terms of impedance control of arm movement. Discussing this work, Dr. Hogan admits that it can not effectively model all aspects of the performance of the system. He said “Controlling the complete dynamic behavior of the limb may be beyond the capacity of the central nervous system. If the disturbance is sufficiently abrupt, then, because of the inevitable transmission delays, continuous intervention based on neural feedback information will not be a feasible method of modulating these quantities.”. However, the model proposed in this study, accomplished most the work which Hogan believed was not feasible. In order to validate the result of proposed model, this study perform sensitivity analysis between the results produced by the dynamics system and the results measured, the comparison showed the difference between these two results were less than 10%, which strongly support the idea that proposed dynamic model can accurately reflect dynamics system in the upper limb movement control.

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Acoustic information about upper limb movement in voicing

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2004163117 ◽

2020 ◽

Vol 117 (21) ◽

pp. 11364-11367 ◽

Cited By ~ 8

Author(s):

Wim Pouw ◽

Alexandra Paxton ◽

Steven J. Harrison ◽

James A. Dixon

Keyword(s):

Steady State ◽

Upper Limb ◽

Arm Movement ◽

Limb Movement ◽

Interpersonal Perception ◽

The Body ◽

Acoustic Information ◽

Human Voice ◽

Vocal System ◽

The Voice

We show that the human voice has complex acoustic qualities that are directly coupled to peripheral musculoskeletal tensioning of the body, such as subtle wrist movements. In this study, human vocalizers produced a steady-state vocalization while rhythmically moving the wrist or the arm at different tempos. Although listeners could only hear and not see the vocalizer, they were able to completely synchronize their own rhythmic wrist or arm movement with the movement of the vocalizer which they perceived in the voice acoustics. This study corroborates recent evidence suggesting that the human voice is constrained by bodily tensioning affecting the respiratory–vocal system. The current results show that the human voice contains a bodily imprint that is directly informative for the interpersonal perception of another’s dynamic physical states.

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The Mechanics of Perturbed Upper Limb Movement Control

Volume 2: Biomedical and Biotechnology Engineering ◽

10.1115/imece2010-37201 ◽

2010 ◽

Author(s):

Kai Chen ◽

Richard A. Foulds

Keyword(s):

Upper Limb ◽

Muscle Length ◽

Movement Control ◽

Elbow Flexion ◽

Influential Factors ◽

Least Square ◽

Movement Trajectory ◽

Time Duration ◽

Inverse Dynamic ◽

Control Signals

The dependence of muscle force on muscle length gives rise to a “spring - like” behavior which has been shown to play an important role during movement. This study extended this concept and incorporated the influential factors of the mechanical behavior of the neural, muscular and skeletal system on the control of elbow movement. A significant question in motor control is determining how information about movement is used to modify control signals to achieve desired performance. One theory proposed and supported by Feldman et. is the equilibrium point hypothesis (EPH). In it the central nervous system (CNS) reacts to movement as a shift of the limb’s equilibrium posture. The EPH drastically simplified the requisite computations for multi-joint movements and mechanical interactions with complex dynamic objects in the context. Because the neuromuscular system is spring-like, the instantaneous difference between the arm’s actual position and the equilibrium position specified by the neural activity can generate the requisite torques, avoiding the complex “inverse dynamic” of computing the torques at the joints. Moreover, this instantaneous difference serves as a potential source of movement control related to limb dynamics and associated movement-dependent torques when perturbations are added. In this paper, we have used an EPH model to examine changes to control signals for arm movements in the context of adding perturbations in format of forces or torques. The mechanical properties and reflex actions of muscles crossing the elbow joint were examined during a planned 1 radian voluntary elbow flexion movement. Brief unexpected torque/force pulses of identical magnitude and time duration (4.5 N flexion switching to 50 N extension within 120ms) were introduced at various points of a movement in randomly selected trials. Single perturbation was implemented in different trials during early, mid, stages of the movement by pre-programmed 6DOF robotic arm (MOOG FCS HapticMaster). Changes in movement trajectory induced by a torque/ force perturbation determined over the first 120 ms by a position prediction formulation, and then a modified and optimization K-B-I (stiffness-damping-inertia) model was fit to the responses for predicting both non-perturbed and perturbed movement of elbow. The stiffness and damping coefficients estimate during voluntary movements were compared to values recorded of different subjects during trials. A least square nonlinear optimization model was designed to help determine the optimized impedance a subject could generate, and the identified of adapted of K-B-I in perturbed upper limb movements confirmed our assumption.

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Social Resonance: Acoustic Information about Upper Limb Movement in Voicing

10.31234/osf.io/ny39e ◽

2019 ◽

Author(s):

Wim Pouw ◽

Alexandra Paxton ◽

Steven A. Harrison ◽

James A. Dixon

Keyword(s):

Upper Limb ◽

Motion Tracking ◽

Vocal Tract ◽

Arm Movement ◽

Limb Movement ◽

Speech Prosody ◽

Acoustic Information ◽

Within Subjects ◽

Arm Motion ◽

The Voice

We show that upper limb movement affects voice acoustics in a way that allows listeners to synchronize to those movements. In this pre-registered motion-tracking study (within-subjects, N = 30), participants listened to vocalizers producing a steady-state phonation while moving the upper limb with a wrist versus an arm motion at different tempos. Listeners were asked to synchronize their own wrist or arm movement with what they perceived in the voice acoustics to be the movement of the vocalizer. Previous research has shown that higher physical impetus gestures can directly affect lower vocal tract activity, leading to peaks in the fundamental frequency (F0; perceived as pitch) and intensity. Here we show that listeners can attune to acoustic information so as to synchronize both in frequency and in phasing with the vocalizer, even with very subtle movements. We interpret the current results in support of a possible ecological psychological approach to speech prosody.

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Acoustic specification of upper limb movement in voicing: Exploratory data report and pre-registration

10.31234/osf.io/5rcdu ◽

2019 ◽

Author(s):

Wim Pouw ◽

Alexandra Paxton ◽

Steven A. Harrison ◽

James A. Dixon

Keyword(s):

Upper Limb ◽

Visual Information ◽

Research Question ◽

Arm Movement ◽

Limb Movement ◽

Complex Information ◽

Exploratory Data ◽

Bodily States ◽

Study Participants ◽

Larger Sample

Hand gestures communicate complex information to listeners through the visual information created by movement. In a recent study, however, we found that there are also direct biomechanical effects of high-impetus upper limb movement on voice acoustics. Here we explored whether listeners could detect information about movement in voice acoustics of another person. In this exploratory study, participants listened to a recording of a vocalizer who was simultaneously producing low- (wrist movement) or high- (arm movement) impetus movements at three different tempos. Listeners were asked to synchronize their own movement (wrist or arm movement) with that of the vocalizer. Listeners coupled with the frequency of the vocalizer arm (but not wrist) movements, and showed phase-coupling with vocalizer arm (but not wrist) movements. However, we found that this synchronization occurred regardless of whether the listener was moving their wrist or arm. This study shows that, in principle, there is acoustic specification of arm movements in voicing, but not wrist movements. These results, if replicated, provide novel insight into the possible interpersonal functions of gesture acoustics, which may lie in communicating bodily states. The second part of the paper is a pre-registration for the confirmatory study that will assess the research question in a larger sample with more diverse and naturalistic stimuli.

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Movement Control Phases of Upper Body Coordination in Visually Guided Reach Movements

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/154193120905301215 ◽

2009 ◽

Vol 53 (12) ◽

pp. 834-838

Author(s):

Shin-Yuan Yu ◽

Bernard J. Martin

Keyword(s):

Motor Behavior ◽

Peak Velocity ◽

Movement Time ◽

Movement Control ◽

Human Movement ◽

Upper Body ◽

Movement Speed ◽

Joint Movement ◽

Feedback Information ◽

Time To Peak

Coordination of human movement includes temporal and spatial aspects. Under the assumption that the implicit movement sequence of body segments may be associated with visual feedback information, the activation timing, time to peak velocity of the hand and sequencing of joint movements were investigated in this study. The results show that variations in movement time with target azimuth and distance fit a quadratic regression model. In addition, the time to peak velocity reveals a movement scaling property in the context of self-imposed movement speed. Finally, the sequencing of joint movement also varies with target azimuth and distance. These motor behavior properties and movement characteristics can be used to model human reach movement in a dynamic manner and to estimate task durations.

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Iterative learning-based path control for robot-assisted upper-limb rehabilitation

Neural Computing and Applications ◽

10.1007/s00521-021-06037-z ◽

2021 ◽

Author(s):

Kamran Maqsood ◽

Jing Luo ◽

Chenguang Yang ◽

Qingyuan Ren ◽

Yanan Li

Keyword(s):

Upper Limb ◽

Impedance Control ◽

Human Movement ◽

Interaction Force ◽

Movement Speed ◽

Reference Trajectory ◽

Robot Assisted ◽

Upper Limb Rehabilitation ◽

Limb Rehabilitation ◽

Trajectory Learning

AbstractIn robot-assisted rehabilitation, the performance of robotic assistance is dependent on the human user’s dynamics, which are subject to uncertainties. In order to enhance the rehabilitation performance and in particular to provide a constant level of assistance, we separate the task space into two subspaces where a combined scheme of adaptive impedance control and trajectory learning is developed. Human movement speed can vary from person to person and it cannot be predefined for the robot. Therefore, in the direction of human movement, an iterative trajectory learning approach is developed to update the robot reference according to human movement and to achieve the desired interaction force between the robot and the human user. In the direction normal to the task trajectory, human’s unintentional force may deteriorate the trajectory tracking performance. Therefore, an impedance adaptation method is utilized to compensate for unknown human force and prevent the human user drifting away from the updated robot reference trajectory. The proposed scheme was tested in experiments that emulated three upper-limb rehabilitation modes: zero interaction force, assistive and resistive. Experimental results showed that the desired assistance level could be achieved, despite uncertain human dynamics.

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A Cortico-Spinal Model of Reaching and Proprioception under Multiple Task Constraints

Journal of Cognitive Neuroscience ◽

10.1162/089892998562852 ◽

1998 ◽

Vol 10 (4) ◽

pp. 425-444 ◽

Cited By ~ 33

Author(s):

Paul Cisek ◽

Stephen Grossberg ◽

Daniel Bullock

Keyword(s):

Movement Control ◽

Arm Movement ◽

Movement Speed ◽

Dynamic Feedback ◽

Range Of Movement ◽

Tonic Vibration Reflex ◽

Task Constraints ◽

Feedback Information ◽

Wide Range ◽

The Brain

A model of cortico-spinal trajectory generation for voluntary reaching movements is developed to functionally interpret a broad range of behavioral, physiological, and anatomical data. The model simulates how arm movements achieve their remarkable efficiency and accuracy in response to widely varying positional, speed, and force constraints. A key issue in arm movement control is how the brain copes with such a wide range of movement contexts. The model suggests how the brain may set automatic and volitional gating mechanisms to vary the balance of static and dynamic feedback information to guide the movement command and to compensate for external forces. For example, with increasing movement speed, the system shifts from a feedback position controller to a feedforward trajectory generator with superimposed dynamics compensation. Simulations of the model illustrate how it reproduces the effects of elastic loads on fast movements, endpoint errors in Coriolis fields, and several effects of muscle tendon vibration, including tonic and antagonist vibration reflexes, position and movement illusions, effects of obstructing the tonic vibration reflex, and reaching undershoots caused by antagonist vibration.

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Study of Rapid Goal-Directed Force of Upper Limb Movement

Journal of Mathematical Sciences ◽

10.1007/s10958-021-05282-w ◽

2021 ◽

Author(s):

A. G. Yakushev ◽

T. Yu. Bokov

Keyword(s):

Upper Limb ◽

Limb Movement

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Learning to Control Arm Stiffness Under Static Conditions

Journal of Neurophysiology ◽

10.1152/jn.00596.2004 ◽

2004 ◽

Vol 92 (6) ◽

pp. 3344-3350 ◽

Cited By ~ 73

Author(s):

Mohammad Darainy ◽

Nicole Malfait ◽

Paul L. Gribble ◽

Farzad Towhidkhah ◽

David J. Ostry

Keyword(s):

Impedance Control ◽

Arm Movement ◽

Realistic Model ◽

Impedance Change ◽

Robotic Device ◽

Lateral Direction ◽

Maximum Stiffness ◽

Asymmetric Pattern ◽

Static Conditions ◽

Endpoint Stiffness

We used a robotic device to test the idea that impedance control involves a process of learning or adaptation that is acquired over time and permits the voluntary control of the pattern of stiffness at the hand. The tests were conducted in statics. Subjects were trained over the course of 3 successive days to resist the effects of one of three different kinds of mechanical loads: single axis loads acting in the lateral direction, single axis loads acting in the forward/backward direction, and isotropic loads that perturbed the limb in eight directions about a circle. We found that subjects in contact with single axis loads voluntarily modified their hand stiffness orientation such that changes to the direction of maximum stiffness mirrored the direction of applied load. In the case of isotropic loads, a uniform increase in endpoint stiffness was observed. Using a physiologically realistic model of two-joint arm movement, the experimentally determined pattern of impedance change could be replicated by assuming that coactivation of elbow and double joint muscles was independent of coactivation of muscles at the shoulder. Moreover, using this pattern of coactivation control we were able to replicate an asymmetric pattern of rotation of the stiffness ellipse that was observed empirically. These findings are consistent with the idea that arm stiffness is controlled through the use of at least two independent co-contraction commands.

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