Biofeedback system for transfemoral amputees rehabilitation

Quiñones, Ivett; Vela, Emir A.; Perez, A. I.; Alessi, Aldo; Urrusti, José; Torres-Cepeda, Duly

doi:10.1109/pahce.2009.5158386

Cited by 3 publications

(3 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Although biofeedback is effective in both clinical and non-clinical settings, it is particularly beneficial during the early stages of rehabilitation [13]. Using biofeedback technologies is generally received well by trial participants and increases motivation to complete sustained rehabilitation [15,16], though there have been usability issues reported within the elderly population [13].…”

Section: Introductionmentioning

confidence: 99%

Visual Biofeedback Tool for Quantitative Pressure Monitoring in Lower-Limb Prosthetic Sockets

Turner¹,

Jain²,

Patel³

et al. 2021

Preprint

View full text Add to dashboard Cite

Obtaining a good socket fit is an iterative process dependent on the skill and experience of the prosthetist creating it, and requiring individualisation based on the size and shape. There is no standard measurement system used to aid prosthetic socket creation, despite the severe impacts on physical health and quality of life if one is ill-fitting. Pressure sensors embedded in a prosthetic socket were used to collect data at the socket-residuum interface. To choose an interpolation method, a 2D grid was used, with previously collected walking test pressure data, to simplify the sensor array with a border for extrapolation. Four multivariable interpolation methods were evaluated to create a colour map of the pressure data. Radial Basis Function interpolation was chosen as it produced a clear image with a graduated interpolation between data points and was used to create a colour map across the surface of a 3D prosthetic socket model. For the model to be accessible to clinical audiences, a desktop application was created using PyQt to view the model. The created application allowed for connection to the sensors via Bluetooth, with the pressure data updating the colour map on the 3D model in real-time. The created application shows the potential for a clinical product, however further development informed by feedback from rehabilitation clinicians and prosthesis users is required

show abstract

Section: Introductionmentioning

confidence: 99%

Visual Biofeedback Tool for Quantitative Pressure Monitoring in Lower-Limb Prosthetic Sockets

Turner¹,

Jain²,

Patel³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Although biofeedback is effective in both clinical and non-clinical settings, it is particularly beneficial during the early stages of rehabilitation [15]. Using biofeedback technologies is generally received well by trial participants and increases motivation to complete sustained rehabilitation [17,18], though there have been usability issues reported within the elderly population [15]. Visual feedback during rehabilitation has been shown to positively influence rehabilitation and can be used as outcome measures as well.…”

Section: Introductionmentioning

confidence: 99%

A Visual Feedback Tool for Quantitative Pressure Monitoring in Lower-Limb Prosthetic Sockets

et al. 2021

View full text Add to dashboard Cite

Obtaining a good socket fit is an iterative process dependent on the skill and experience of the prosthetist creating it and requires individualisation based on the size and shape. There is no standard measurement system used to aid prosthetic socket creation despite the severe impacts on physical health and quality of life if one is ill fitting. Pressure sensors embedded in a prosthetic socket were used to collect data at the socket–residuum interface. To choose an interpolation method, the sensor array was simplified to a 2D grid with a border for extrapolation and tested using previously collected walking test pressure data. Four multivariable interpolation methods were evaluated to create a colour map of the pressure data. Radial basis function interpolation was chosen, as it produced a clear image with a graduated interpolation between data points, and was used to create a colour map across the surface of a 3D prosthetic socket model. For the model to be accessible to clinical audiences, a desktop application was created using PyQt to view the model. The application allowed for connection to the sensors via Bluetooth, with the pressure data updating on the 3D model in real time. Clinician feedback on the application showed the potential for a clinical product; however, further development informed by feedback from rehabilitation clinicians and prosthesis users is required.

show abstract

“…Una de las técnicas más utilizadas en rehabilitación es el biofeedback electromiográfico, que detecta la actividad mioeléctrica mediante electrodos de superficie para generar información auditiva o visual útil al paciente para inhibir o aumentar determinada actividad muscular [23][24][25]. Otra forma de realizar biofeedback se hace a partir de la información de una plataforma sensible a la presión durante la bipedestación, para reentrenar la simetría en el apoyo y el equilibrio (estático y dinámico); también la posición articular obtenida con un electrogoniómetro puede ser utilizada para este fin [26].…”

Section: Introductionunclassified

Sistema de Biofeedback para Rehabilitación de Marcha Asistida por un Exoesqueleto

Mayor

Valencia-Jimenez

Hoyos

et al. 2019

RIB

View full text Add to dashboard Cite

Los robots proporcionan nuevas formas de terapia para pacientes con desórdenes neurológicos. Las terapias de marcha asistidas con exoesqueletos pueden incrementar la duración y la intensidad de los entrenamientos para los pacientes y reducir el esfuerzo físico del terapeuta. Sin embargo, el uso de estos dispositivos para el entrenamiento de la marcha limita la interacción física entre el terapeuta y el paciente, en comparación con la terapia manual. Una apropiada realimentación de las funciones corporales y biomecánicas en la interacción con el sistema robótico facilita la evaluación del desempeño del paciente, motivándolo en el reaprendizaje de la marcha con resultados superiores. Este artículo presenta el diseño de una interfaz de usuario para un exoesqueleto de miembros inferiores para asistencia en la marcha y en terapias de rehabilitación. Se consideraron aspectos técnicos y clínicos para proporcionar ventajas del exoesqueleto durante las terapias, estableciendo una herramienta de apoyo para la configuración, monitoreo y registro de los parámetros involucrados. Se propuso un esquema de realimentación sensorial para el paciente acerca de la actividad muscular, la presión ejercida en diferentes puntos de los pies y algunas variables biomecánicas. Finalmente, se valida la herramienta con sujetos sanos por medio de un test de usabilidad propuesto.

show abstract

Biofeedback system for transfemoral amputees rehabilitation

Cited by 3 publications

References 4 publications

Visual Biofeedback Tool for Quantitative Pressure Monitoring in Lower-Limb Prosthetic Sockets

Visual Biofeedback Tool for Quantitative Pressure Monitoring in Lower-Limb Prosthetic Sockets

A Visual Feedback Tool for Quantitative Pressure Monitoring in Lower-Limb Prosthetic Sockets

Sistema de Biofeedback para Rehabilitación de Marcha Asistida por un Exoesqueleto

Contact Info

Product

Resources

About