Adaptive assistive control of a soft elbow trainer with self-alignment using pneumatic bending joint

Wilkening, André; Stöppler, Henning; Ivlev, Oleg

doi:10.1109/icorr.2015.7281288

Cited by 14 publications

(10 citation statements)

References 17 publications

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“…Especially patient-cooperative rehabilitation robots, that are taken into account the patient's intention and behavior as well as maximize the patient's voluntary effort, are proposed to have a high potential to improve robot-assisted rehabilitation [4][5][6][7][8]. In the design of those rehabilitation robots, an essential aspect is the physical human-robot interface, which should provide a safe human-robot interaction (HRI) with high comfort for the user.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Physical Human-Robot Interaction Using Cost-Effective Pneumatic Padding

2016

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Abstract:The idea to use a cost-effective pneumatic padding for sensing of physical interaction between a user and wearable rehabilitation robots is not new, but until now there has not been any practical relevant realization. In this paper, we present a novel method to estimate physical human-robot interaction using a pneumatic padding based on artificial neural networks (ANNs). This estimation can serve as rough indicator of applied forces/torques by the user and can be applied for visual feedback about the user's participation or as additional information for interaction controllers. Unlike common mostly very expensive 6-axis force/torque sensors (FTS), the proposed sensor system can be easily integrated in the design of physical human-robot interfaces of rehabilitation robots and adapts itself to the shape of the individual patient's extremity by pressure changing in pneumatic chambers, in order to provide a safe physical interaction with high user's comfort. This paper describes a concept of using ANNs for estimation of interaction forces/torques based on pressure variations of eight customized air-pad chambers. The ANNs were trained one-time offline using signals of a high precision FTS which is also used as reference sensor for experimental validation. Experiments with three different subjects confirm the functionality of the concept and the estimation algorithm.

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Section: Introductionmentioning

confidence: 99%

Estimation of Physical Human-Robot Interaction Using Cost-Effective Pneumatic Padding

2016

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“…Such actuators may be effective for rehabilitation but not for a portable system. Pneumatic bending joint using skewed rotary elastic chamber (sREC) is used in a soft elbow trainer to assist patient for safe and effective rehabilitation [15]. It has a pneumatic elastic chamber which allows self-alignment to the polycentric movement of the human joint axis.…”

Section: Existing Elbow Exoskeletonsmentioning

confidence: 99%

A mechanism for elbow exoskeleton for customised training

Manna

Dubey

2017

2017 International Conference on Rehabilitation Robotics (ICORR)

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It is well proven that repetitive extensive training consisting of active and passive therapy is effective for patients suffering from neuromuscular deficits. The level of difficulty in rehabilitation should be increased with time to improve the neurological muscle functions. A portable elbow exoskeleton has been designed that will meet these requirements and potentially offers superior outcomes than human-assisted training. The proposed exoskeleton can provide both active and passive rehabilitation in a single structure without changing its configuration. The idea is to offer three levels of rehabilitation; namely active, passive and stiffness control in a single device using a single actuator. The mechanism also provides higher torque to weight ratio making it an energy efficient mechanism.

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“…It is well-recognized that inherent compliance of robot will help realize the safe human–robot interaction in rehabilitation. Combining traditional electromechanical drivers with elastic springs or directly using actuators with inherent compliance such as the pneumatic muscles is a potential way to ensure the compliance in human–robot environments (Hussain et al, 2013a ; Wilkening et al, 2015 ), while the compliance offers a promising means to improve a robot’s soft dynamics and inherent safety.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Compliance Control of a Soft Ankle Rehabilitation Robot Actuated by Pneumatic Muscles

Liu

Meng

et al. 2017

Front. Neurorobot.

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Traditional compliance control of a rehabilitation robot is implemented in task space by using impedance or admittance control algorithms. The soft robot actuated by pneumatic muscle actuators (PMAs) is becoming prominent for patients as it enables the compliance being adjusted in each active link, which, however, has not been reported in the literature. This paper proposes a new compliance control method of a soft ankle rehabilitation robot that is driven by four PMAs configured in parallel to enable three degrees of freedom movement of the ankle joint. A new hierarchical compliance control structure, including a low-level compliance adjustment controller in joint space and a high-level admittance controller in task space, is designed. An adaptive compliance control paradigm is further developed by taking into account patient’s active contribution and movement ability during a previous period of time, in order to provide robot assistance only when it is necessarily required. Experiments on healthy and impaired human subjects were conducted to verify the adaptive hierarchical compliance control scheme. The results show that the robot hierarchical compliance can be online adjusted according to the participant’s assessment. The robot reduces its assistance output when participants contribute more and vice versa, thus providing a potentially feasible solution to the patient-in-loop cooperative training strategy.

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Adaptive assistive control of a soft elbow trainer with self-alignment using pneumatic bending joint

Cited by 14 publications

References 17 publications

Estimation of Physical Human-Robot Interaction Using Cost-Effective Pneumatic Padding

Estimation of Physical Human-Robot Interaction Using Cost-Effective Pneumatic Padding

A mechanism for elbow exoskeleton for customised training

Hierarchical Compliance Control of a Soft Ankle Rehabilitation Robot Actuated by Pneumatic Muscles

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