Decoding Imagined 3D Arm Movement Trajectories From EEG to Control Two Virtual Arms—A Pilot Study

Moving smoothly is generally considered as a higher-order goal of motor control and moving jerkily as a witness of clumsiness or pathology, yet many common and well-controlled movements (e.g., tracking movements) have irregular velocity profiles with widespread fluctuations. The origin and nature of these fluctuations have been associated with the operation of an intermittent process but in fact remain poorly understood. Here we studied velocity fluctuations during slow movements, using combined experimental and theoretical tools. We recorded arm movement trajectories in a group of healthy participants performing back-and-forth movements at different speeds, and we analyzed velocity profiles in terms of series of segments (portions of velocity between 2 minima). We found that most of the segments were smooth (i.e., corresponding to a biphasic acceleration) and had constant duration irrespective of movement speed and linearly increasing amplitude with movement speed. We accounted for these observations with an optimal feedback control model driven by a staircase goal position signal in the presence of sensory noise. Our study suggests that one and the same control process can explain the production of fast and slow movements, i.e., fast movements emerge from the immediate tracking of a global goal position and slow movements from the successive tracking of intermittently updated intermediate goal positions. NEW & NOTEWORTHY We show in experiments and modeling that slow movements could result from the brain tracking a sequence of via points regularly distributed in time and space. Accordingly, slow movements would differ from fast movement by the nature of the guidance and not by the nature of control. This result could help in understanding the origin and nature of slow and segmented movements frequently observed in brain disorders.

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Evaluating Arm Movement Imitation

American Journal of Undergraduate Research ◽

10.33697/ajur.2006.004 ◽

2006 ◽

Vol 4 (4) ◽

Cited By ~ 4

Author(s):

Alexandra Constantin ◽

Maja Matarić

Keyword(s):

Empirical Study ◽

Arm Movement ◽

Pairwise Similarity ◽

Rotational Angle ◽

Movement Trajectories ◽

Human Evaluation ◽

Movement Imitation

In this paper, we present a metric for assessing the quality of arm movement imitation. We develop a joint-rotational-angle-based segmentation and comparison algorithm that rates pairwise similarity of arm movement trajectories on a scale of 1-10. We describe an empirical study designed to validate the algorithm we developed, by comparing it to human evaluation of imitation. The results provide evidence that the evaluation of the automatic metric did not significantly differ from human evaluation.

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Effect of Task Practice Order on Motor Skill Learning in Adults With Parkinson Disease: A Pilot Study

Physical Therapy ◽

10.2522/ptj.20060228 ◽

2007 ◽

Vol 87 (9) ◽

pp. 1120-1131 ◽

Cited By ~ 30

Author(s):

Chien-Ho (Janice) Lin ◽

Katherine J Sullivan ◽

Allan D Wu ◽

Shailesh Kantak ◽

Carolee J Winstein

Keyword(s):

Pilot Study ◽

Motor Learning ◽

Parkinson Disease ◽

Task Switching ◽

Arm Movement ◽

Random Order ◽

Study Data ◽

Skill Learning ◽

Control Group ◽

Task Practice

Background and Purpose: Random practice of motor tasks has been shown to enhance motor learning. The purpose of this study was to investigate the effects of task practice order (random, blocked) on motor learning in adults with Parkinson disease (PD).Subjects: Twenty adults with mild PD and 20 age-matched adults (controls) participated in the study.Methods: Participants in both groups (PD and control) practiced 3 movement tasks with either a blocked or a random practice order. This 2 participant group × 2 practice order design resulted in 4 experimental groups. The Trail Making Test was administered to all participants to determine task-switching capability. Motor performance on the arm movement tasks was quantified on the basis of the root-mean-square error difference between the goal movement task and each participant's response.Results: The task-switching capability of the control group was superior to that of the PD group. For acquisition, in general, participants in the control group performed with significantly less error than participants in the PD group. For retention, participants in the control group who practiced with a random order performed more accurately than participants in the control group who practiced with a blocked order. However, for the PD group, the findings were reversed; participants who practiced with a blocked order performed more accurately than participants who practiced with a random order. These findings resulted in a group × practice order interaction.Discussion and Conclusion: These pilot study data suggest that, contrary to the findings for age-matched control learners, for learners with mild PD, a blocked practice order may be better than a random practice order for motor learning.

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Gesture Production and Text Structure

Perceptual and Motor Skills ◽

10.2466/pms.101.2.435-439 ◽

2005 ◽

Vol 101 (2) ◽

pp. 435-439 ◽

Cited By ~ 5

Author(s):

Sergio Chieffi ◽

Mariateresa Ricci

Keyword(s):

Pilot Study ◽

Arm Movement ◽

Text Structure ◽

Low Level ◽

High Level ◽

Verbal Production ◽

Verbal Meaning ◽

The Relationship ◽

Present Pilot Study ◽

Gesture Production

In the present pilot study, we examined the relationship between gesture and verbal production. Subjects were asked to read a story and then to narrate what they remembered. We analyzed verbal production according to Kintsch's procedure and obtained a list of hierarchically organized propositions that represented the meaning of subject's narration. Propositions were subdivided into High- and Low-level propositions. Further, we analyzed gesture production by identifying hand or arm movement that accompanied subject's narration. Each gesture was associated with the word simultaneously produced, and then with the proposition to which the word belonged. Analysis showed subjects were more likely to produce gestures in association with High- rather than with Low-level propositions. High-level propositions may elicit the production of gestures which, in turn, mark the importance of verbal meaning conveyed simultaneously.

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Constraints on human arm movement trajectories.

Canadian Journal of Psychology/Revue Canadienne de Psychologie ◽

10.1037/h0084157 ◽

1987 ◽

Vol 41 (3) ◽

pp. 365-378 ◽

Cited By ~ 476

Author(s):

R.G. Marteniuk ◽

C.L. Mackenzie ◽

M. Jeannerod ◽

S. Athenes ◽

C. Dugas

Keyword(s):

Arm Movement ◽

Movement Trajectories ◽

Human Arm

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Prediction of arm movement trajectories from ECoG-recordings in humans

Journal of Neuroscience Methods ◽

10.1016/j.jneumeth.2007.10.001 ◽

2008 ◽

Vol 167 (1) ◽

pp. 105-114 ◽

Cited By ~ 214

Author(s):

Tobias Pistohl ◽

Tonio Ball ◽

Andreas Schulze-Bonhage ◽

Ad Aertsen ◽

Carsten Mehring

Keyword(s):

Arm Movement ◽

Movement Trajectories

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Reaching to Grasp With a Multi-Jointed Arm. I. Computational Model

Journal of Neurophysiology ◽

10.1152/jn.00030.2002 ◽

2002 ◽

Vol 88 (5) ◽

pp. 2355-2367 ◽

Cited By ~ 46

Author(s):

Elizabeth B. Torres ◽

David Zipser

Keyword(s):

Error Correction ◽

Constraint Satisfaction ◽

Degrees Of Freedom ◽

Computational Models ◽

Reference Frames ◽

Dimensional Space ◽

Arm Movement ◽

Human Movement ◽

Path Selection ◽

Movement Trajectories

The generation of goal-directed movements requires the solution of many difficult computational problems. Among these are transformations from extrinsic to intrinsic reference frames, specifying solution paths, removing under-specification due to excess degrees of freedom and path multiplicity, constraint satisfaction, and error correction. There are no current motor-control computational models that address these issues in the context of realistic arm movement with redundant degrees of freedom. In this paper, we conjecture there is a geometric stage between sensory input and physical execution. The geometric stage determines movement trajectories independently of forces. It uses a gradient technique that relies on the metric of the space of postures to resolve endpoint path selection, posture-change specification, error correction, and multiple constraint satisfaction on-line without preplanning. The model is instantiated in an arm with seven degrees of freedom that moves in three-dimensional space. Simulated orientation-matching movements are compared with actual human movement data to assess the validity of several of the model's behavioral predictions.

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ON THE BÊTA-ELLIPTIC MODEL FOR THE CONTROL OF THE HUMAN ARM MOVEMENT

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001407005272 ◽

2007 ◽

Vol 21 (01) ◽

pp. 5-19 ◽

Cited By ~ 15

Author(s):

HALA BEZINE ◽

MEHDI KEFI ◽

ADEL M. ALIMI

Keyword(s):

Degrees Of Freedom ◽

Arm Movement ◽

Motor Program ◽

Movement Trajectories ◽

Hand Model ◽

Elliptic Theory ◽

Human Arm ◽

Elliptic Model ◽

Cursive Script ◽

Natural Movement

This article describes a kinematic theory, called the Bêta-elliptic model, for generating handwriting movements. The model consists of a sequential controller producing a curvilinear velocity approximated by Bêta profiles. This earlier interacts with a trajectory generator to provide elliptic strokes. As an application to our model, we consider a redundant seven degrees of freedom manipulator having a kinematic structure similar to that of a human arm. We treat to demonstrate how the Bêta-elliptic theory enables a simple motor program to generate complex curvilinear movements that have many of the properties that humans exhibit when they produce cursive script. Bêta-elliptic properties enable a simple control strategy to generate complex handwritten script if the hand model contains redundant degrees of freedom. Here, we restrict our analysis to a total of seven degrees of freedom from the shoulder to the wrist. The proposed controller launches transient commands to independent hand synergies at times when the hand begins to move. The Bêta-elliptic model transforms these synergy commands into smooth curvilinear velocity fitted by Bêta profiles among temporally overlapping synergetic units of trajectory approximated by elliptic strokes. In experiments, and at first sight, good phenomenological agreement with natural movement trajectories is found.

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