ReFlex, a haptic wrist interface for motor learning and rehabilitation

Chapuis, D.; Grave, Remco Benthem de; Lambercy, Olivier; Gassert, Roger

doi:10.1109/haptic.2010.5444622

Cited by 14 publications

(12 citation statements)

References 25 publications

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“…The ReFlex is a one degree-of-freedom robotic manipulandum which was used in previous studies to assess wrist and finger proprioception (Chapuis et al, 2010;Rinderknecht et al, 2016). It can move an end-effector to well-controlled positions.…”

Section: Robotic Manipulandummentioning

confidence: 99%

Age-Dependent Asymmetry of Wrist Position Sense Is Not Influenced by Stochastic Tactile Stimulation

Georgarakis

Sonar

Rinderknecht

et al. 2020

Front. Hum. Neurosci.

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Stochastic stimulation has been shown to improve movement, balance, the sense of touch, and may also improve position sense. This stimulation can be non-invasive and may be a simple technology to enhance proprioception. In this study, we investigated whether sub-threshold stochastic tactile stimulation of mechanoreceptors reduces age-related errors in wrist position estimation. Fifteen young (24.5 ± 1.5 y) and 23 elderly (71.7±7.3 y) unimpaired, right-handed adults completed a wrist position gauge-matching experiment. In each trial, the participant's concealed wrist was moved to a target position between 10 and 30 • of wrist flexion or extension by a robotic manipulandum. The participant then estimated the wrist's position on a virtual gauge. During half of the trials, sub-threshold stochastic tactile stimulation was applied to the wrist muscle tendon areas. Stochastic stimulation did not significantly influence wrist position sense. In the elderly group, estimation errors decreased non-significantly when stimulation was applied compared to the trials without stimulation [mean constant error reduction µ(θ of con ) = 0.8 • in flexion and µ(θ oe con ) = 0.7 • in extension direction, p = 0.95]. This effect was less pronounced in the young group [ µ(θ y con ) = 0.2 • in flexion and in extension direction, p = 0.99]. These improvements did not yield a relevant effect size (Cohen's d < 0.1). Estimation errors increased with target angle magnitude in both movement directions. In young participants, estimation errors were non-symmetric, with estimations in flexion [µ(θ yf con ) = 1.8 • , σ (θ yf con ) = 7.0 • ] being significantly more accurate than in extension [µ(θ ye con ) = 8.3 • , σ (θ ye con ) = 9.3 • , p < 0.01]. This asymmetry was not present in the elderly group, where estimations in flexion [µ(θ of con ) = 7.5 • , σ (θ of con ) = 9.8 • ] were similar to extension [µ(θ oe con ) = 7.7 • , σ (θ oe con ) = 9.3 • ]. Hence, young and elderly participants performed equally in extension direction, whereas wrist position sense in flexion direction deteriorated with age (p < 0.01). Though unimpaired elderly adults did not benefit from stochastic stimulation, it cannot be deduced that individuals with more Georgarakis et al.Age-Dependent Wrist Position Sense Asymmetry severe impairments of their sensory system do not profit from this treatment. While the errors in estimating wrist position are symmetric in flexion and extension in elderly adults, young adults are more accurate when estimating wrist flexion, an effect that has not been described before.

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Section: Robotic Manipulandummentioning

confidence: 99%

Age-Dependent Asymmetry of Wrist Position Sense Is Not Influenced by Stochastic Tactile Stimulation

Georgarakis

Sonar

Rinderknecht

et al. 2020

Front. Hum. Neurosci.

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“…Each trial of the assessment aiming at estimating the difference threshold of the angular position at the right wrist joint consisted of the consecutive presentation of two different angles and the subsequent judgment by the subject which of the two presented movements was larger (two-interval 2AFC paradigm (Macmillan and Douglas Creelman, 2005)). The movements were applied to the passive wrist with a one degree-of-freedom robotic wrist interface (Chapuis et al, 2010). The movements always started from the resting position (hand aligned with forearm, 0 • ) and went into flexion direction (maximum 40 • ).…”

Section: Protocol Of the Proprioceptive Assessmentmentioning

confidence: 99%

Enhancing Simulations With Intra-Subject Variability for Improved Psychophysical Assessments

Rinderknecht

Lambercy

Gassert

2018

Preprint

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Psychometric properties of perceptual assessments, like reliability, depend on the stochastic properties of psychophysical sampling procedures resulting in method variability, as well as inter-and intra-subject variability. Method variability is commonly minimized by optimizing sampling procedures through computer simulations. Inter-subject variability is inherent in the population of interest and cannot be acted upon. In contrast, intra-subject variability introduced by confounds cannot be simply quantified from experimental data, as this data also includes method variability. Therefore, this aspect is generally neglected when developing assessments. Yet, comparing method variability and intra-subject variability could give insights on whether effort should be invested in optimizing the sampling procedure, or in addressing potential confounds instead. We propose a new approach to estimate and model intra-subject variability of psychometric functions by combining computer simulations and behavioral data, and to account for it when simulating experiments. The approach was illustrated in a real-world scenario of proprioceptive difference threshold assessments. The behavioral study revealed a test-retest reliability of 0.212. Computer simulations lacking intra-subject variability predicted a reliability of 0.768, whereas the new approach including an intra-subject variability model lead to a realistic estimate of reliability (0.207). Such a model also allows computing the theoretically maximally attainable reliability (0.552) assuming an ideal sampling procedure. Comparing the reliability estimates when exclusively accounting for method variability versus intra-subject variability reveals that intra-subject variability should be reduced by addressing confounds and that only optimizing the sampling procedure may be insufficient to achieve a high reliability. The new approach also allows accelerating the development of assessments by simulating the converging behavior of the reliability confidence interval with a large number of subjects and retests without requiring additional experiments. Having such a tool of predictive value is especially important for target populations where time is scarce, such as for assessments in clinical settings.

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“…On one hand, DC motors based robot have stability problems in force feedback control, while the brakes are passive components and can improve the system stability [7]. On the other hand, brakes can provide more resistance together with motors in rehabilitation training, since the requirement of resistance of the robot is larger than the assistance in active training [8].…”

Section: Mechanical Structurementioning

confidence: 99%

Implementation of active training for an upper-limb rehabilitation robot based on impedance control

Peng

Hou

Kasabov

et al. 2015

The 27th Chinese Control and Decision Conference (2015 CCDC)

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Many rehabilitation robots have been designed to alleviate the conflict between increasing number of poststroke patients and shortage of therapists. Active training is the main feature of advanced rehabilitation robots, which has been proved to be more effective than simple passive movement training. This paper presents the implementation of active training on a 2-DOF upper-limb rehabilitation robot, which can assist the shoulder and elbow joint rehabilitation training of post-stroke patients. The controller is built based on impedance control, which can provide a compliant human-robot reaction. The implementation of active training is combined with a virtual reality game, and the average error between the actual and target reaction force is 1.41 ± 0.79 N in the X axis, and 1.22 ± 0.91 N in the Y axis. 5453 978-1-4799-7016-2/15/$31.00 c 2015 IEEE

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ReFlex, a haptic wrist interface for motor learning and rehabilitation

Cited by 14 publications

References 25 publications

Age-Dependent Asymmetry of Wrist Position Sense Is Not Influenced by Stochastic Tactile Stimulation

Age-Dependent Asymmetry of Wrist Position Sense Is Not Influenced by Stochastic Tactile Stimulation

Enhancing Simulations With Intra-Subject Variability for Improved Psychophysical Assessments

Implementation of active training for an upper-limb rehabilitation robot based on impedance control

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