U-Limb: A multi-modal, multi-center database on arm motion control in healthy and post-stroke conditions

Abstract Background Shedding light on the neuroscientific mechanisms of human upper limb motor control, in both healthy and disease conditions (e.g., after a stroke), can help to devise effective tools for a quantitative evaluation of the impaired conditions, and to properly inform the rehabilitative process. Furthermore, the design and control of mechatronic devices can also benefit from such neuroscientific outcomes, with important implications for assistive and rehabilitation robotics and advanced human-machine interaction. To reach these goals, we believe that an exhaustive data collection on human behavior is a mandatory step. For this reason, we release U-Limb, a large, multi-modal, multi-center data collection on human upper limb movements, with the aim of fostering trans-disciplinary cross-fertilization. Contribution This collection of signals consists of data from 91 able-bodied and 65 post-stroke participants and is organized at 3 levels: (i) upper limb daily living activities, during which kinematic and physiological signals (electromyography, electro-encephalography, and electrocardiography) were recorded; (ii) force-kinematic behavior during precise manipulation tasks with a haptic device; and (iii) brain activity during hand control using functional magnetic resonance imaging.

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Unvealing the Principal Modes of Human Upper Limb Movements through Functional Analysis

Frontiers in Robotics and AI ◽

10.3389/frobt.2017.00037 ◽

2017 ◽

Vol 4 ◽

Cited By ~ 17

Author(s):

Giuseppe Averta ◽

Cosimo Della Santina ◽

Edoardo Battaglia ◽

Federica Felici ◽

Matteo Bianchi ◽

...

Keyword(s):

Functional Analysis ◽

Upper Limb ◽

Limb Movements ◽

Upper Limb Movements ◽

Human Upper Limb

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Human Upper Limb Experimental Analysis for Assistive Devices in Feeding Process

Advanced Engineering Forum ◽

10.4028/www.scientific.net/aef.42.122 ◽

2021 ◽

Vol 42 ◽

pp. 122-127

Author(s):

Cristian Copilusi ◽

Ionut Geonea ◽

Alexandru Margine ◽

Adrian Rosca

Keyword(s):

Upper Limb ◽

Experimental Analysis ◽

Command And Control ◽

Disabled Persons ◽

Assistive Devices ◽

Upper Arm ◽

Experimental Process ◽

Feeding Process ◽

And Control ◽

Human Upper Limb

This research addresses attention to human upper limb experimental analysis during feeding process aiding disabled persons. The research core is focused on the experimental process of obtaining the angular amplitudes and trajectories developed by the human upper arm during feeding process. The research originality consists on the obtained results which can be used in further researches for command and control of robotic assisting devices.

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A Multiparameter Approach to Evaluate Post-Stroke Patients: An Application on Robotic Rehabilitation

Applied Sciences ◽

10.3390/app8112248 ◽

2018 ◽

Vol 8 (11) ◽

pp. 2248 ◽

Cited By ~ 4

Author(s):

Antonella Belfatto ◽

Alessandro Scano ◽

Andrea Chiavenna ◽

Alfonso Mastropietro ◽

Simona Mrakic-Sposta ◽

...

Keyword(s):

Upper Limb ◽

Brain Activity ◽

Quantitative Description ◽

Motor Task ◽

Chronic Patients ◽

Clinical Scales ◽

Post Stroke ◽

Robotic Therapy ◽

Parameter Evaluation ◽

Before And After

Multidomain instrumental evaluation of post-stroke chronic patients, coupled with standard clinical assessments, has rarely been exploited in the literature. Such an approach may be valuable to provide comprehensive insight regarding patients’ status, as well as orienting the rehabilitation therapies. Therefore, we propose a multidomain analysis including clinically compliant methods as electroencephalography (EEG), electromyography (EMG), kinematics, and clinical scales. The framework of upper-limb robot-assisted rehabilitation is selected as a challenging and promising scenario to test the multi-parameter evaluation, with the aim to assess whether and in which domains modifications may take place. Instrumental recordings and clinical scales were administered before and after a month of intensive robotic therapy of the impaired upper limb, on five post-stroke chronic hemiparetic patients. After therapy, all patients showed clinical improvement and presented pre/post modifications in one or several of the other domains as well. All patients performed the motor task in a smoother way; two of them appeared to change their muscle synergies activation strategies, and most subjects showed variations in their brain activity, both in the ipsi- and contralateral hemispheres. Changes highlighted by the new multiparametric instrumental approach suggest a recovery trend in agreement with clinical scales. In addition, by jointly demonstrating lateralization of brain activations, changes in muscle recruitment and the execution of smoother trajectories, the new approach may help distinguish between true functional recovery and the adoption of suboptimal compensatory strategies. In the light of these premises, the multi-domain approach may allow a finer patient characterization, providing a deeper insight into the mechanisms underlying the relearning procedure and the level (neuro/muscular) at which it occurred, at a relatively low expenditure. The role of this quantitative description in defining a personalized treatment strategy is of great interest and should be addressed in future studies.

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