Constraining Upper Limb Synergies of Hemiparetic Patients Using a Robotic Exoskeleton in the Perspective of Neuro-Rehabilitation

Crocher, Vincent; Sahbani, Anis; Robertson, Johanna; Roby-Brami, Agnès; Morel, Guillaume

doi:10.1109/tnsre.2012.2190522

Cited by 47 publications

(42 citation statements)

References 54 publications

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“…Haptic interfaces for sport training and rehabilitation robots aim at emulating this behavior. Even if the “passive mode” used in first stage, where the arm is moved by the robot, is similar to an assistance scheme, the “active mode” in which robot is only correcting patient movements “just-as-needed” is similar to an education scheme [41], [42], [63], [64].…”

Section: Resultsmentioning

confidence: 99%

A Framework to Describe, Analyze and Generate Interactive Motor Behaviors

2012

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While motor interaction between a robot and a human, or between humans, has important implications for society as well as promising applications, little research has been devoted to its investigation. In particular, it is important to understand the different ways two agents can interact and generate suitable interactive behaviors. Towards this end, this paper introduces a framework for the description and implementation of interactive behaviors of two agents performing a joint motor task. A taxonomy of interactive behaviors is introduced, which can classify tasks and cost functions that represent the way each agent interacts. The role of an agent interacting during a motor task can be directly explained from the cost function this agent is minimizing and the task constraints. The novel framework is used to interpret and classify previous works on human-robot motor interaction. Its implementation power is demonstrated by simulating representative interactions of two humans. It also enables us to interpret and explain the role distribution and switching between roles when performing joint motor tasks.

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Section: Resultsmentioning

confidence: 99%

A Framework to Describe, Analyze and Generate Interactive Motor Behaviors

2012

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“…One of the main challenges in assist-as-needed approach is to find the ideal joint angle trajectory for the required limb movement, as it forces the user to follow a desired trajectory [22]. This also reduces free interaction between the human and the device, rather than promoting it, which is beneficial for an effective motor recovery [24]. Moreover, to figure out the minimal assistance level in real time, the assist-as-needed controllers need to solve optimization problems which increase the computational and hardware complexity compromising the agility of the system design.…”

Section: Imentioning

confidence: 99%

Hand-Exoskeleton Assisted Progressive Neurorehabilitation Using Impedance Adaptation Based Challenge Level Adjustment Method

Chowdhury

Nishad

Meena

et al. 2019

IEEE Trans. Haptics

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This paper presents an underactuated design of a robotic hand exoskeleton, and a challenge based neurorehabilitation strategy. The exoskeleton is designed to reproduce natural human fingertip paths during extension and grasping, keeping minimal kinematic complexity. It facilitates an impedance adaptation based trigged assistance control strategy by switching between active non-assist and passive assistance modes. In the active non-assist mode, the exoskeleton motion follows the applied fingertip forces based on an impedance model. If the applied fingertip forces are inadequate, the passive assistance mode is triggered. The impedance parameters are updated at regular intervals based on the user performance, to implement a challenge based rehabilitation strategy. A six-week long hand therapy, conducted on four chronic stroke patients, resulted in significant (p-value<0.05) increase in force generation capacity and decrease (p-value<0.05) in the required assistance. Also, there was a significant (p-value<0.05) increase in the system impedance parameters which adequately challenged the patients. The change in the Action-Research-Arm-Test (ARAT) scores from baseline was also found to be significant (p-value<0.05) and beyond the minimal clinically important difference (MCID) limit. Thus the results prove that the proposed control strategy with has the potential to be a clinically effective solution for personalized rehabilitation of poststroke hand functionality.

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“…The contralateral and ipsilateral targets are reported to be more useful for assessing abnormal synergies. Crocher et al [87] on the other hand use explicit model based on linear relationship between joint velocities. Principal Component Analysis (PCA) is used to determine the constraint in redundancy of pointing task, that is the unused subspace with the least variance and quantify the difference between subject’s natural constraint, applied constraint by therapist and robot’s imposed constraint.…”

Section: Kinematic Parameters Evaluating Movement Qualitymentioning

confidence: 99%

Assessment of movement quality in robot- assisted upper limb rehabilitation after stroke: a review

Nordin

Xie

Wünsche

2014

J NeuroEngineering Rehabil

230

198

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Electronic supplementary materialStudies of stroke patients undergoing robot-assisted rehabilitation have revealed various kinematic parameters describing movement quality of the upper limb. However, due to the different level of stroke impairment and different assessment criteria and interventions, the evaluation of the effectiveness of rehabilitation program is undermined. This paper presents a systematic review of kinematic assessments of movement quality of the upper limb and identifies the suitable parameters describing impairments in stroke patients. A total of 41 different clinical and pilot studies on different phases of stroke recovery utilizing kinematic parameters are evaluated. Kinematic parameters describing movement accuracy are mostly reported for chronic patients with statistically significant outcomes and correlate strongly with clinical assessments. Meanwhile, parameters describing feed-forward sensorimotor control are the most frequently reported in studies on sub-acute patients with significant outcomes albeit without correlation to any clinical assessments. However, lack of measures in coordinated movement and proximal component of upper limb enunciate the difficulties to distinguish the exploitation of joint redundancies exhibited by stroke patients in completing the movement. A further study on overall measures of coordinated movement is recommended.Electronic supplementary materialThe online version of this article (doi:10.1186/1743-0003-11-137) contains supplementary material, which is available to authorized users.

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Constraining Upper Limb Synergies of Hemiparetic Patients Using a Robotic Exoskeleton in the Perspective of Neuro-Rehabilitation

Cited by 47 publications

References 54 publications

A Framework to Describe, Analyze and Generate Interactive Motor Behaviors

A Framework to Describe, Analyze and Generate Interactive Motor Behaviors

Hand-Exoskeleton Assisted Progressive Neurorehabilitation Using Impedance Adaptation Based Challenge Level Adjustment Method

Assessment of movement quality in robot- assisted upper limb rehabilitation after stroke: a review

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