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

Stroke Clinical Trial

Official title:

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

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04995367
• Other study ID #: CorporacionRCLCS0005
• Status: Completed
• Phase: N/A
• Start date: March 15, 2021
• Est. completion date: May 15, 2021

Study information

• Verified date: August 2021
• Source: Corporación de Rehabilitación Club de Leones Cruz del Sur
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

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

Description:

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 5
• Est. completion date: May 15, 2021
• Est. primary completion date: May 12, 2021
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 70 Years

Eligibility

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

Related Conditions & MeSH terms

• Stroke

Intervention

Device:
• 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.

Locations

Country	Name	City	State
Chile	Corporación de Rehabilitación Club de Leones Cruz del Sur	Punta Arenas	XII Región

Sponsors (2)

Lead Sponsor	Collaborator
Corporación de Rehabilitación Club de Leones Cruz del Sur	Colombian School of Engineering Julio Garavito

Country where clinical trial is conducted

Chile, 

References & Publications (9)

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. Review. — View Citation

Gomez-Vargas D, Ballen-Moreno F, Barria P, Aguilar R, Azorín 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). pii: 412. doi: 10.3390/brainsci11040412. — View Citation

He Y, Eguren D, Azorín 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. Review. — View Citation

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. — View Citation

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. Review. — View Citation

Ortiz M, Ferrero L, Iáñez E, Azorín 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. — View Citation

Ortiz M, Iáñez E, Contreras-Vidal JL, Azorín 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. — View Citation

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. Review. — View Citation

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. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Response time	The response time for each task will be automatically measured by a Visual Studio Code Software during the use of the Brain-Computer Interface.; This variable will consider the response time of a specific command, since the subject receives the stimulation until the software detects the EEG Signal. The measure unit is milliseconds	Baseline
Primary	EEG signals from primary motor cortex	continuous signals will be acquired from the primary motor cortex of lower limbs (FcZ, C2, Cz, C1, Cpz) according to the 10-20 International EEG System. Power spectral density in the frequency band of motor imagery (8-32Hz) will be obtained by OpenVibe Software and Matlab. The measure unit is Decibels per Hertz(dB/Hz).	Baseline
Secondary	Patient satisfaction with device: Quebec User Evaluation of Satisfaction with Assistive Technology	Measured with QUEST scale. The Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) is a 12-item outcome measure that assesses user satisfaction with two components, Device and Services. Scores of 1 indicate dissatisfaction and scores of 5 indicate high satisfaction	Baseline