Assessment-driven arm therapy at home using an IMU-based virtual reality system

Wittmann, Frieder; Lambercy, Olivier; Gonzenbach, Roman; Raai, Mark A. van; Höver, Raphael; Held, Jeremia P. O.; Starkey, Malcolm; Curt, Armin; Luft, Andreas R.; Gassert, Roger

doi:10.1109/icorr.2015.7281284

Cited by 53 publications

(44 citation statements)

References 23 publications

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“…El ambiente de juego tenía tres niveles de dificultad (Figura 5), y la diferencia entre estos se respaldó en la cantidad de movimientos necesarios para superar cada nivel, por lo que el juego logra ser atractivo para el jugador cuando resulta difícil de jugar [31], siendo esta una característica importante, teniendo en cuenta que los niveles de dificultad conllevan a un factor de alta motivación en el individuo durante una terapia [32]. niveles de complejidad de la pista.…”

Section: Resultsunclassified

Tecnología lúdica para la rehabilitación de miembro superior en jóvenes

Gutierrez

Papamija²,

Rojas³

et al. 2018

Vis. Electron.

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El proyecto de investigación consistió en el diseño de una tecnología lúdica utilizada como instrumento de rehabilitación en una actividad de juego, enfocada al restablecimiento de la función motriz del miembro superior, el cual está involucrado en la realización de actividades de la vida diaria (actividades como: aseo personal, sostener objetos, apoyarse, entre otras). El juego propuesto considera a la persona en su conjunto de sistemas físicos, intelectuales y psicosociales. El prototipo fue caracterizado con pruebas realizadas a 50 jóvenes de edades entre 16 y 22 años, aparentemente sanos, quienes decidieron participar de manera voluntaria de la actividad de juego. El juguete constó de: un brazalete electrónico (control remoto) y un carro de juguete que tenía la función de moverse simultáneamente con los movimientos que efectuaba el jugador con su extremidad superior. El juguete se moviliza en medio de una pista dividida por tres niveles de dificultad. Se constató que la actividad lúdica propuesta cumplió con los requerimientos de una actividad en el marco de la rehabilitación, puesto que se tiene en cuenta la estabilidad y realización de movimientos desde la articulación proximal del hombro, siguiendo por codo y muñeca, además se pueden obtener beneficios adyacentes, a nivel cognitivo, debido a que el jugador debe entender e identificar el espacio en el que se desarrolla el juego, de tal manera que el jugador plantea una estrategia de juego basado en secuencias lógicas, acciones y consecuencias, y en ciertas actitudes sociales, evidenciadas en la apreciación que genera el juego en el participante, evaluado a través de una encuesta en factores como: dversión, atención, presión, sentido de competencia y esfuerzo.

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Section: Resultsunclassified

Tecnología lúdica para la rehabilitación de miembro superior en jóvenes

Gutierrez

Papamija²,

Rojas³

et al. 2018

Vis. Electron.

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“…Such an adaptation strategy has the potential to facilitate reinforcement learning (Naros et al, 2016b) by progressively challenging the patient (Naros and Gharabaghi, 2015). Recent studies explored automated adaptation of training difficulty in stroke rehabilitation of less severely affected patients (Metzger et al, 2014; Wittmann et al, 2015). More specifically, both robot-assisted rehabilitation of proprioceptive hand function (Metzger et al, 2014) and inertial sensor-based virtual reality feedback of the arm (Wittmann et al, 2015) benefit from assessment-driven adjustments of exercise difficulty.…”

Section: Introductionmentioning

confidence: 99%

“…Recent studies explored automated adaptation of training difficulty in stroke rehabilitation of less severely affected patients (Metzger et al, 2014; Wittmann et al, 2015). More specifically, both robot-assisted rehabilitation of proprioceptive hand function (Metzger et al, 2014) and inertial sensor-based virtual reality feedback of the arm (Wittmann et al, 2015) benefit from assessment-driven adjustments of exercise difficulty. Furthermore, a direct comparison between adaptive BRI training and non-adaptive training (Naros et al, 2016b) or sham adaptation (Bauer et al, 2016a) in healthy patients revealed the impact of reinforcement-based adaptation for the improvement of performance.…”

Section: Introductionmentioning

confidence: 99%

Closed-Loop Task Difficulty Adaptation during Virtual Reality Reach-to-Grasp Training Assisted with an Exoskeleton for Stroke Rehabilitation

2016

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Stroke patients with severe motor deficits of the upper extremity may practice rehabilitation exercises with the assistance of a multi-joint exoskeleton. Although this technology enables intensive task-oriented training, it may also lead to slacking when the assistance is too supportive. Preserving the engagement of the patients while providing “assistance-as-needed” during the exercises, therefore remains an ongoing challenge. We applied a commercially available seven degree-of-freedom arm exoskeleton to provide passive gravity compensation during task-oriented training in a virtual environment. During this 4-week pilot study, five severely affected chronic stroke patients performed reach-to-grasp exercises resembling activities of daily living. The subjects received virtual reality feedback from their three-dimensional movements. The level of difficulty for the exercise was adjusted by a performance-dependent real-time adaptation algorithm. The goal of this algorithm was the automated improvement of the range of motion. In the course of 20 training and feedback sessions, this unsupervised adaptive training concept led to a progressive increase of the virtual training space (p < 0.001) in accordance with the subjects' abilities. This learning curve was paralleled by a concurrent improvement of real world kinematic parameters, i.e., range of motion (p = 0.008), accuracy of movement (p = 0.01), and movement velocity (p < 0.001). Notably, these kinematic gains were paralleled by motor improvements such as increased elbow movement (p = 0.001), grip force (p < 0.001), and upper extremity Fugl-Meyer-Assessment score from 14.3 ± 5 to 16.9 ± 6.1 (p = 0.026). Combining gravity-compensating assistance with adaptive closed-loop feedback in virtual reality provides customized rehabilitation environments for severely affected stroke patients. This approach may facilitate motor learning by progressively challenging the subject in accordance with the individual capacity for functional restoration. It might be necessary to apply concurrent restorative interventions to translate these improvements into relevant functional gains of severely motor impaired patients in activities of daily living.

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“…The full-body motion capture technology has applications in various domains, including virtual reality [1], athletic training [2], biomedical engineering [3] and rehabilitation [4,5]. The demand for rehabilitation services and the resulting demand for systems capable of body movement monitoring continue to grow due to the increasing population of ageing people.…”

Section: Introductionmentioning

confidence: 99%

Inertial Motion Capture Costume Design Study

Szczęsna

Skurowski

Lach

et al. 2017

Sensors

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The paper describes a scalable, wearable multi-sensor system for motion capture based on inertial measurement units (IMUs). Such a unit is composed of accelerometer, gyroscope and magnetometer. The final quality of an obtained motion arises from all the individual parts of the described system. The proposed system is a sequence of the following stages: sensor data acquisition, sensor orientation estimation, system calibration, pose estimation and data visualisation. The construction of the system’s architecture with the dataflow programming paradigm makes it easy to add, remove and replace the data processing steps. The modular architecture of the system allows an effortless introduction of a new sensor orientation estimation algorithms. The original contribution of the paper is the design study of the individual components used in the motion capture system. The two key steps of the system design are explored in this paper: the evaluation of sensors and algorithms for the orientation estimation. The three chosen algorithms have been implemented and investigated as part of the experiment. Due to the fact that the selection of the sensor has a significant impact on the final result, the sensor evaluation process is also explained and tested. The experimental results confirmed that the choice of sensor and orientation estimation algorithm affect the quality of the final results.

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Assessment-driven arm therapy at home using an IMU-based virtual reality system

Cited by 53 publications

References 23 publications

Tecnología lúdica para la rehabilitación de miembro superior en jóvenes

Tecnología lúdica para la rehabilitación de miembro superior en jóvenes

Closed-Loop Task Difficulty Adaptation during Virtual Reality Reach-to-Grasp Training Assisted with an Exoskeleton for Stroke Rehabilitation

Inertial Motion Capture Costume Design Study

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