BCI-Based Control for Ankle Exoskeleton T-FLEX: Comparison of Visual and Haptic Feedback With Stroke Survivors

NCT ID: NCT04995367

Last Updated: 2021-08-06

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

5 participants

Study Classification

INTERVENTIONAL

Study Start Date

2021-03-15

Study Completion Date

2021-05-15

Brief Summary

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This protocol will developed an assessment of the T-FLEX device controlled by Brain-Computer Interface in patients with Stroke.

Detailed Description

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Brain-Computer Interface (BCI) remains an emerging tool that seeks to improve the patient interaction with the therapeutic mechanisms and to generate neuroplasticity progressively through neuromotor abilities. Motor Imagery (MI) analysis is the most used paradigm based on the motor cortex's electrical activity to detect movement intention. It has been shown that motor imagery mental practice with movement-associated feedback may offer an effective strategy to facilitate motor recovery in brain injury patients. This protocol will study a BCI system associated with visual and haptic feedback to facilitate MI generation and, to control a T-FLEX ankle exoskeleton. In this study, a group of five post-stroke patients will test four different strategies using T-FLEX: Passive movement, Active movement, Motor Imagination with Visual stimulation and Motor Imagination with Visual-Haptic stimuli. The quantitative characterization of BCI performance will be made by using statistical analysis of electroencephalographic data. Finally, the patient's satisfaction will be evaluated by a questionnaire.

Conditions

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Stroke

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

TREATMENT

Blinding Strategy

NONE

Study Groups

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Implementation of a BCI system integrated to the T-FLEX lower-limb exoskeleton in post-stroke

The participants will carry out tests for the evaluation of the functionality of the BCI system integrated to the T-FLEX device. The test consists of 1 session that includes four conditional experiments. Real Movement, Continuous Stationary Therapy, Motor Imagery Detection with Visual Stimulation, and Motor Imagery Detection with Tactile Stimulation.

Group Type EXPERIMENTAL

Implementation of a BCI system integrated to the T-FLEX lower-limb exoskeleton in post-stroke patients.

Intervention Type DEVICE

The participants will carry out 4 tasks with a BCI system integrated to the T-FLEX device. The task consists of 1 session that includes 4 conditional experiments: Active ankle movement, passive ankle movement, Motor Imagery Detection with Visual cue, and Motor Imagery Detection with Tactile Stimulation and visual cue.

Interventions

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Implementation of a BCI system integrated to the T-FLEX lower-limb exoskeleton in post-stroke patients.

The participants will carry out 4 tasks with a BCI system integrated to the T-FLEX device. The task consists of 1 session that includes 4 conditional experiments: Active ankle movement, passive ankle movement, Motor Imagery Detection with Visual cue, and Motor Imagery Detection with Tactile Stimulation and visual cue.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* Unilateral lower extremity paresis
* Hemorrhagic or ischemic stroke
* A minimum of six months after the acute infarction/onset of the disease
* Full passive range of motion in lower extremity or at least at neutral position
* Be able to stand freely
* Be able to walk with or without aid for at least 20 meters in less than 2 minutes

Exclusion Criteria

* Peripheral nervous system pathology
* Epilepsy
* Weight over 100 kg
* No cognitive ability to follow the study instructions
* Pregnancy
* Use of implanted devices
* Instable lower extremity joints or fixed contracture
Minimum Eligible Age

18 Years

Maximum Eligible Age

70 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Colombian School of Engineering Julio Garavito

OTHER

Sponsor Role collaborator

Corporación de Rehabilitación Club de Leones Cruz del Sur

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Asterio H Andrade, PhD

Role: STUDY_CHAIR

Rehabilitation Center Club de Leones Cruz del Sur

Locations

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Corporación de Rehabilitación Club de Leones Cruz del Sur

Punta Arenas, Region of Magallanes, Chile

Site Status

Countries

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Chile

References

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Verma R, Arya KN, Sharma P, Garg RK. Understanding gait control in post-stroke: implications for management. J Bodyw Mov Ther. 2012 Jan;16(1):14-21. doi: 10.1016/j.jbmt.2010.12.005. Epub 2010 Dec 30.

Reference Type BACKGROUND
PMID: 22196422 (View on PubMed)

Needham DM, Truong AD, Fan E. Technology to enhance physical rehabilitation of critically ill patients. Crit Care Med. 2009 Oct;37(10 Suppl):S436-41. doi: 10.1097/CCM.0b013e3181b6fa29.

Reference Type BACKGROUND
PMID: 20046132 (View on PubMed)

Chen G, Chan CK, Guo Z, Yu H. A review of lower extremity assistive robotic exoskeletons in rehabilitation therapy. Crit Rev Biomed Eng. 2013;41(4-5):343-63. doi: 10.1615/critrevbiomedeng.2014010453.

Reference Type BACKGROUND
PMID: 24941413 (View on PubMed)

Gomez-Vargas D, Ballen-Moreno F, Barria P, Aguilar R, Azorin JM, Munera M, Cifuentes CA. The Actuation System of the Ankle Exoskeleton T-FLEX: First Use Experimental Validation in People with Stroke. Brain Sci. 2021 Mar 24;11(4):412. doi: 10.3390/brainsci11040412.

Reference Type BACKGROUND
PMID: 33805216 (View on PubMed)

He Y, Eguren D, Azorin JM, Grossman RG, Luu TP, Contreras-Vidal JL. Brain-machine interfaces for controlling lower-limb powered robotic systems. J Neural Eng. 2018 Apr;15(2):021004. doi: 10.1088/1741-2552/aaa8c0.

Reference Type BACKGROUND
PMID: 29345632 (View on PubMed)

Ortiz M, Ianez E, Contreras-Vidal JL, Azorin JM. Analysis of the EEG Rhythms Based on the Empirical Mode Decomposition During Motor Imagery When Using a Lower-Limb Exoskeleton. A Case Study. Front Neurorobot. 2020 Aug 27;14:48. doi: 10.3389/fnbot.2020.00048. eCollection 2020.

Reference Type BACKGROUND
PMID: 32973481 (View on PubMed)

Ma T, Li H, Deng L, Yang H, Lv X, Li P, Li F, Zhang R, Liu T, Yao D, Xu P. The hybrid BCI system for movement control by combining motor imagery and moving onset visual evoked potential. J Neural Eng. 2017 Apr;14(2):026015. doi: 10.1088/1741-2552/aa5d5f. Epub 2017 Feb 1.

Reference Type BACKGROUND
PMID: 28145274 (View on PubMed)

Thomas E, Dyson M, Clerc M. An analysis of performance evaluation for motor-imagery based BCI. J Neural Eng. 2013 Jun;10(3):031001. doi: 10.1088/1741-2560/10/3/031001. Epub 2013 May 3.

Reference Type BACKGROUND
PMID: 23639955 (View on PubMed)

Ortiz M, Ferrero L, Ianez E, Azorin JM, Contreras-Vidal JL. Sensory Integration in Human Movement: A New Brain-Machine Interface Based on Gamma Band and Attention Level for Controlling a Lower-Limb Exoskeleton. Front Bioeng Biotechnol. 2020 Sep 3;8:735. doi: 10.3389/fbioe.2020.00735. eCollection 2020.

Reference Type BACKGROUND
PMID: 33014987 (View on PubMed)

Other Identifiers

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CorporacionRCLCS0005

Identifier Type: -

Identifier Source: org_study_id

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