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Motor Learning in a Customized Body-Machine Interface (BMI)

14 de noviembre de 2019 actualizado por: Ferdinando Mussa-Ivaldi, Shirley Ryan AbilityLab

Motor Learning in a Customized Body-Machine Interface for Persons With Paralysis

People with tetraplegia often retain some level of mobility of the upper body. The proposed study will test the hypothesis that it is possible to develop personalized interfaces, which utilize the residual mobility to enable paralyzed persons to control computers, wheelchairs and other assistive devices. If successful the project will result into the establishment of a new family of human-machine interfaces based on wearable sensors that adapt their functions to their users' abilities.

Descripción general del estudio

Estado

Desconocido

Descripción detallada

The goal of these studies is to enable persons paralyzed by spinal cord injury (SCI) to drive powered wheelchairs and interact with computers by acting through an interface that maximizes the effectiveness of their residual motor function. This is called a "body-machine interface" because it maps the motions of the upper-body (arms and shoulders) to the space of device control signals in an optimal way. In this way, paralyzed persons that cannot operate a joystick controller because of lack of hand mobility can effectively use their whole upper body as virtual joystick device. An important characteristic of the proposed approach is that it is based on the possibility to control a computer or a wheelchair by bodily movements through an interactive learning process, in which the interface adapts itself to the subject's mobility and the subject learns to act through the interface. This study aims at developing and testing the customization of this interface to a group of SCI participants with tetraplegia, resulting from high-level cervical injury. The proposed research is organized in three specific aims:

(Aim 1) To develop new functional capabilities in persons with spinal cord injury by customizing a body-machine interface to their individual upper body mobility. After fitting the interface to the residual movements of each subject, participants will practice computer games aimed at training two classes of control actions: operating a virtual joystick and operating a virtual keyboard. This study will test the ability of the subjects to perform skilled maneuvers with a simulated wheelchair.

(Aim 2.) To test the hypothesis that practicing the upper-body control of personalized interfaces results in significant physical and psychological benefits after spinal-cord injury. A study will evaluate and quantify the impact of the practicing functional upper-body motions on the mobility of the shoulder and arms by conventional clinical methods and by measuring the subjects' ability to generate coordinated upper body movements and to apply isometric forces. Other studies under this aim will evaluate the effects of operating the body-machine interface on musculoskeletal pain and on the mood and mental state of the participants.

(Aim 3) To train spinal-cord injury survivors to skillfully operate a powered wheelchair using their enhanced upper body motor skills and customized interface parameters. Finally, the last study will test the hypothesis that the skills learned through practice in the virtual environment are retained for the control of an actual powered wheelchair. After reaching stable performance in the simulated wheelchair, subjects will practice the control of the physical wheelchair in safe a testing environment.

(Aim 4.) To understand how extensive practice with a body machine interface affects the cortical representation of the trained limbs. A study will evaluate and quantify the impact of the practicing functional upper-body motions on corticospinal excitability as a correlate to sensorimotor skill learning. Participants will meet the inclusion criteria for both the main study and satisfy the additional optional criteria. Participant will practice upper-body movements using the body-machine interface. The study will evaluate the evolution of corticospinal excitability in related areas of the motor cortex during the training compared to the baseline and after a follow-up period.

If successful, this study will lead to effective operation of a highly customized interface that adapts to the residual motor capability of its users. Physical and psychological benefits are expected to derive from the sustained and coordinated activity associated with the use of this body-machine interface

Tipo de estudio

Intervencionista

Inscripción (Actual)

157

Fase

  • No aplica

Contactos y Ubicaciones

Esta sección proporciona los datos de contacto de quienes realizan el estudio e información sobre dónde se lleva a cabo este estudio.

Ubicaciones de estudio

    • Illinois
      • Chicago, Illinois, Estados Unidos, 60611
        • Shirley Ryan Abilitylab

Criterios de participación

Los investigadores buscan personas que se ajusten a una determinada descripción, denominada criterio de elegibilidad. Algunos ejemplos de estos criterios son el estado de salud general de una persona o tratamientos previos.

Criterio de elegibilidad

Edades elegibles para estudiar

18 años a 65 años (Adulto, Adulto Mayor)

Acepta Voluntarios Saludables

No

Géneros elegibles para el estudio

Todos

Descripción

Inclusion Criteria:

  • Age 18-65
  • Injuries at C3-C6 level, complete (ASIA A) or incomplete (ASIA B and C)
  • Able to follow simple commands
  • Able to speak or respond to questions

Exclusion Criteria:

  • Presence of tremors, spasm and other significant involuntary movements
  • Cognitive impairment
  • Deficit of visuo-spatial orientation
  • Concurrent pressure sores or urinary tract infection

(Optional) Additional Exclusion Criteria for evaluation of corticospinal excitability using Transcranial Magnetic Stimulation:

  • Any metal in head with the exception of dental work or any ferromagnetic metal elsewhere in the body. This applies to all metallic hardware such as cochlear implants, or an Internal Pulse Generator or medication pumps, implanted brain electrodes, and peacemaker.
  • Personal history of epilepsy (untreated with one or a few past episodes), or treated patients
  • Vascular, traumatic, tumoral, infectious, or metabolic lesion of the brain, even without history of seizure, and without anticonvulsant medication
  • Administration of drugs that potentially lower seizure threshold [62], without concomitant administration of anticonvulsant drugs which potentially protect against seizures occurrence
  • Change in dosage for neuro-active medications (Baclophen, Lyrica, Celebrex, Cymbalta, Gapapentin, Naposyn, Diclofenac, Diazapam, Tramadol, etc) within 2 weeks of any study visit.
  • Skull fractures, skull deficits or concussion within the last 6 months
  • unexplained recurring headaches
  • Sleep deprivation, alcoholism
  • Claustrophobia precluding MRI
  • Pregnancy

Plan de estudios

Esta sección proporciona detalles del plan de estudio, incluido cómo está diseñado el estudio y qué mide el estudio.

¿Cómo está diseñado el estudio?

Detalles de diseño

  • Propósito principal: Cuidados de apoyo
  • Asignación: No aleatorizado
  • Modelo Intervencionista: Asignación paralela
  • Enmascaramiento: Único

Armas e Intervenciones

Grupo de participantes/brazo
Intervención / Tratamiento
Experimental: SCI Static
SCI group that practices with a static body-machine map
The intervention compares two ways of customizing the body-machine interface which will be used for subjects for 40 sessions (spread over 8 months). In one case (SCI static), the body-machine interface is static. In the other case (SCI Machine Learning), there is a machine learning algorithm that adapts to the movements made by the subject.
Experimental: SCI Machine Learning
Spinal Cord Injury patients who practice with a body-machine map that is adapted using machine learning
The intervention compares two ways of customizing the body-machine interface which will be used for subjects for 40 sessions (spread over 8 months). In one case (SCI static), the body-machine interface is static. In the other case (SCI Machine Learning), there is a machine learning algorithm that adapts to the movements made by the subject.

¿Qué mide el estudio?

Medidas de resultado primarias

Medida de resultado
Medida Descripción
Periodo de tiempo
Change in Time to task completion from Baseline at 8 months
Periodo de tiempo: Baseline and 8 months
The subjects will perform computer games requiring different data entry tasks (characters, cursor control) and navigate either a virtual or a real obstacle course. This primary outcome measure is the time it takes subjects to complete each task.
Baseline and 8 months

Medidas de resultado secundarias

Medida de resultado
Medida Descripción
Periodo de tiempo
Change in Movement Smoothness from Baseline at 8 months
Periodo de tiempo: Baseline and 8 months
This outcome measure measures the change in movement smoothness when operating the virtual and real wheelchairs
Baseline and 8 months
Change in Strength
Periodo de tiempo: Baseline and 8 months
This outcome measure measures the changes in upper body strength after training
Baseline and 8 months
Change in Mental State
Periodo de tiempo: Baseline and 8 months
This outcome measures measures the change in mental state (as quantified by the State-Trait Anxiety Inventory) after training
Baseline and 8 months

Colaboradores e Investigadores

Aquí es donde encontrará personas y organizaciones involucradas en este estudio.

Investigadores

  • Investigador principal: Ferdinando A Mussa-Ivaldi, PhD, Northwestern University

Publicaciones y enlaces útiles

La persona responsable de ingresar información sobre el estudio proporciona voluntariamente estas publicaciones. Estos pueden ser sobre cualquier cosa relacionada con el estudio.

Fechas de registro del estudio

Estas fechas rastrean el progreso del registro del estudio y los envíos de resultados resumidos a ClinicalTrials.gov. Los registros del estudio y los resultados informados son revisados ​​por la Biblioteca Nacional de Medicina (NLM) para asegurarse de que cumplan con los estándares de control de calidad específicos antes de publicarlos en el sitio web público.

Fechas importantes del estudio

Inicio del estudio

1 de febrero de 2013

Finalización primaria (Anticipado)

1 de septiembre de 2022

Finalización del estudio (Anticipado)

1 de septiembre de 2022

Fechas de registro del estudio

Enviado por primera vez

16 de abril de 2012

Primero enviado que cumplió con los criterios de control de calidad

28 de mayo de 2012

Publicado por primera vez (Estimar)

31 de mayo de 2012

Actualizaciones de registros de estudio

Última actualización publicada (Actual)

15 de noviembre de 2019

Última actualización enviada que cumplió con los criterios de control de calidad

14 de noviembre de 2019

Última verificación

1 de noviembre de 2019

Más información

Esta información se obtuvo directamente del sitio web clinicaltrials.gov sin cambios. Si tiene alguna solicitud para cambiar, eliminar o actualizar los detalles de su estudio, comuníquese con register@clinicaltrials.gov. Tan pronto como se implemente un cambio en clinicaltrials.gov, también se actualizará automáticamente en nuestro sitio web. .

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