Hand neuro-rehabilitation system using Nitinol spring actuators

Navarro, José María Sabater; Garcia, Nicolas M.; Ramos, Daniel Reveles; Camayo, E.; Albán, Óscar Andrés Vivas

doi:10.1016/j.robot.2014.09.015

Cited by 7 publications

(6 citation statements)

References 1 publication

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“…In our study we have focused on the rehabilitation of the distal part of the upper-limb, particularly the finger flexion/extension. Based on the structure and the actuation systems the exoskeletons are found mainly in two categories: a major portion of them are cable actuated [6], [7], [8], [9], [10], [11], and a minority of them are driven by rigid structures or linkages [12], [13], [14], [15]. Recently pneumatic actuators [16] are also being used to build soft exoskeletons.…”

Section: Imentioning

confidence: 99%

“…The individual finger modules are also actuated in different ways as per the need of the therapeutic exercise. Hand exoskeletons such as [6], [14], [15] actuates all the joints of a finger module, while the finger modules of [8], [7], [16] are underactuated. The compromise between making actuating all the fingers and actually all the joints of a finger module has to be made, as incorporating both them (e.g.…”

Section: Imentioning

confidence: 99%

“…From the design point of view, a underactuated design helps in making a device fully portable, lightweight, and easily deployable for use in hospital or home. The minimization of the design complexity is based on the idea that grasping needs can be met with lesser number of degrees of freedom (DOF) [49] and it is often considered enough to use one DOF per phalanx for neurorehabilitation [50]. Unlike cable driven mechanisms, direct drive is less complicated as the effects of cable routing, friction and backlash are avoided [51].…”

Section: Dmentioning

confidence: 99%

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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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Section: Imentioning

confidence: 99%

Section: Imentioning

confidence: 99%

Section: Dmentioning

confidence: 99%

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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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“…In Figure 13, the robot along with the actuator module is shown. The assistive tool with the actuator module has a mass about 300 g. This proves that the proposed device is much lighter and more compact in comparison to those devices that actuate all the fingers (Cempini et al, 2013;Chiri et al, 2012;Ito et al, 2011;Sabater-Navarro et al, 2015;Tadano et al, 2010;Zhang et al, 2014). This capability makes it an appropriate tool for daily activities.…”

Section: Prototyping and Experimental Setupmentioning

confidence: 88%

ASR glove: A wearable glove for hand assistance and rehabilitation using shape memory alloys

Hadi

Alipour

Kazeminasab

et al. 2017

Journal of Intelligent Material Systems and Structures

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To date, various hand exoskeleton devices have been proposed. Most of them, however, contain linkage mechanisms which are relatively weighty. This research presents a novel lightweight hand exoskeleton robot, which is called Advanced Service Robots laboratory (ASR) glove. The glove is shape memory alloy tendon-based actuated which can be utilized for both rehabilitation exercises and assistance for people with hand disability. To realize the proposed glove, after the conceptual design of the proposed robot, the kinematics and force analysis of the system are elaborated analytically and also verified using an experimental prototype of the proposed device. The study shows that the proposed system can flex and extend fingers in their range of motion and grasp objects efficiently. The resulted tool is capable to exert extremely high force levels to grasp objects in various hand configurations. Also, using a 0.25-mm shape memory alloy wire, an angular movement of 80°, 90°, and 70° can be generated at the distal interphalangeal, metacarpophalangeal, and proximal interphalangeal joints of a finger, respectively. In addition, the total grasping force more than 40 N can be produced at the tip of the fingers.

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“…The cabling mechanism made the system lighter but bulky. Sabater-Navarro et al (2015) designed a system that moves each finger but it did not move each phalanx individually. A system was developed by Gezgin et al (2016) which moves all of the fingers together.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy sliding mode control of a wearable rehabilitation robot for wrist and finger

Moshaii

Moghaddam

Niestanak

2019

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Purpose The purpose of this paper is to introduce a new design for a finger and wrist rehabilitation robot. Furthermore, a fuzzy sliding mode controller has been designed to control the system. Design/methodology/approach Following an introduction regarding the hand rehabilitation, this paper discusses the conceptual and detailed design of a novel wrist and finger rehabilitation robot. The robot provides the possibility of rehabilitating each phalanx individually which is very important in the finger rehabilitation process. Moreover, due to the model uncertainties, disturbances and chattering in the system, a fuzzy sliding mode controller design method is proposed for the robot. Findings With the novel design for moving the DOFs of the system, the rehabilitation for the wrist and all phalanges of fingers is done with only two actuators which are combined in one device. These features make the system a good choice for home rehabilitation. To control the robot, a fuzzy sliding mode controller has been designed for the system. The fuzzy controller does not affect the coefficient of the sliding mode controller and uses the overall error of the system to make a control signal. Thus, the dependence of the controller to the model decreases and the system is more robust. The stability of the system is proved by the Lyapunov theorem. Originality/value The paper provides a novel design of a hand rehabilitation robot and a controller which is used to compensate the effects of the uncertain parameters and chattering phenomenon.

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Hand neuro-rehabilitation system using Nitinol spring actuators

Cited by 7 publications

References 1 publication

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

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

ASR glove: A wearable glove for hand assistance and rehabilitation using shape memory alloys

Fuzzy sliding mode control of a wearable rehabilitation robot for wrist and finger

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