scholarly journals Feasibility and Performance Validation of a Leap Motion Controller for Upper Limb Rehabilitation

Robotics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 130
Author(s):  
Marcus R. S. B. de Souza ◽  
Rogério S. Gonçalves ◽  
Giuseppe Carbone
Keyword(s):  
Upper Limb ◽  
Industrial Robot ◽  
Human Hand ◽  
Leap Motion ◽  
Tracking Accuracy ◽  
Motion Controller ◽  
Upper Limb Rehabilitation ◽  
Leap Motion Controller ◽  
Limb Rehabilitation ◽  
Accuracy And Repeatability

The leap motion controller is a commercial low-cost marker-less optical sensor that can track the motion of a human hand by recording various parameters. Upper limb rehabilitation therapy is the treatment of people having upper limb impairments, whose recovery is achieved through continuous motion exercises. However, the repetitive nature of these exercises can be interpreted as boring or discouraging while patient motivation plays a key role in their recovery. Thus, serious games have been widely used in therapies for motivating patients and making the therapeutic process more enjoyable. This paper explores the feasibility, accuracy, and repeatability of a leap motion controller (LMC) to be applied in combination with a serious game for upper limb rehabilitation. Experimental feasibility tests are carried out by using an industrial robot that replicates the upper limb motions and is tracked by using an LMC. The results suggest a satisfactory performance in terms of tracking accuracy although some limitations are identified and discussed in terms of measurable workspace.

scholarly journals Terapia baseada em realidade virtual usando o Leap Motion Controller para reabilitação do membro superior após acidente vascular cerebral

2017 ◽  
Vol 27 (2) ◽  
pp. 25935
Author(s):  
Nayron Medeiros Soares ◽  
Gabriela Magalhães Pereira ◽  
Renata Italiano da Nóbrega Figueiredo ◽  
Gleydson Silva Morais ◽  
Sandy Gonzaga De Melo
Keyword(s):  
Virtual Reality ◽  
Upper Limb ◽  
Active Role ◽  
Reality Therapy ◽  
Leap Motion ◽  
Motion Controller ◽  
Upper Limb Rehabilitation ◽  
Post Stroke ◽  
Leap Motion Controller ◽  
Hand Coordination

*** Virtual reality therapy using the Leap Motion Controller for post-stroke upper limb rehabilitation ***AIMS: To evaluate the applicability of a virtual reality-based motion sensor for post-stroke upper limb rehabilitation.CASES DESCRIPTION: Three post-stroke patients were subjected to virtual reality training for rehabilitation of their upper limbs using the Leap Motion Controller technology and the game Playground 3D® for 3 consecutive days. On the first and last days, the Box and Blocks test, the De Melo Eye-Hand Coordination Test, and transcranial magnetic stimulation were applied. On the last day, the patients were evaluated with the Experience Evaluation Form. After the proposed training, a lower motor threshold was observed in both cerebral hemispheres, as well as better performance in the tests that evaluated hand and eye-hand coordination skills. The proposed therapy was well received by the patients.CONCLUSIONS: No adverse effects were observed, and promising and precise results were obtained for the virtual reality-based training using the Leap Motion Controller and Playground 3D®. The training allowed patients to have an active role in the rehabilitation of stroke-induced upper limb sequelae.

scholarly journals Evaluation of the Leap Motion Controller during the performance of visually-guided upper limb movements

PLoS ONE ◽  
2018 ◽  
Vol 13 (3) ◽  
pp. e0193639 ◽  
Author(s):  
Ewa Niechwiej-Szwedo ◽  
David Gonzalez ◽  
Mina Nouredanesh ◽  
James Tung
Keyword(s):  
Upper Limb ◽  
Leap Motion ◽  
Visually Guided ◽  
Motion Controller ◽  
Limb Movements ◽  
Leap Motion Controller ◽  
Upper Limb Movements

A Motion Capture Realization Method for Assisting in Product Design via Parametric Surfaces

2019 ◽  
Author(s):  
Miri Weiss Cohen ◽  
Daniele Regazzoni
Keyword(s):  
Motion Capture ◽  
Feature Recognition ◽  
Relevant Information ◽  
Sensor Data ◽  
Human Hand ◽  
Leap Motion ◽  
Parametric Surfaces ◽  
Motion Controller ◽  
Leap Motion Controller ◽  
Design Characteristics

Abstract This work proposes a human computer interface system using a motion capture device, for assisting in CAD modeling and designing. The leap motion controller input data serves as an interactive tool which is transformed to surface representation of NURBS surfaces. Acquiring the sensor data is done by analyzing the images using a feature recognition module which in this work was updated and enhanced. Joints of hands and fingers are sufficed, and define recognized 3D image of a human hand. To use relevant information from the Leap Motion device, it is mandatory to interpret and map the input sensor data into 3D software coordinate system. This is done by implementing various transformations and a normalization procedures. Methods corresponding between these representation are developed in this work, to reduce noise thus providing accuracy. The DOF provided by the definition of the NURBS parametric surfaces and the Leap Motion Controller provide flexible design characteristics.

scholarly journals Use of the Leap Motion Controller® System in the Rehabilitation of the Upper Limb in Stroke. A Systematic Review

2022 ◽  
Vol 31 (1) ◽  
pp. 106174
Author(s):  
Ángela Aguilera-Rubio ◽  
Isabel M. Alguacil-Diego ◽  
Ana Mallo-López ◽  
Alicia Cuesta-Gómez
Keyword(s):  
Systematic Review ◽  
Upper Limb ◽  
Leap Motion ◽  
Motion Controller ◽  
Leap Motion Controller

RehabHand: Oriented-tasks serious games for upper limb rehabilitation by using leap motion controller and target population in spinal cord injury

2021 ◽  
pp. 1-9
Author(s):  
Ana de los Reyes-Guzmán ◽  
Vicente Lozano-Berrio ◽  
María Alvarez-Rodríguez ◽  
Elisa López-Dolado ◽  
Silvia Ceruelo-Abajo ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Neurological Diseases ◽  
Low Cost ◽  
Target Population ◽  
Hand Movements ◽  
Leap Motion ◽  
Motion Controller ◽  
Upper Limb Rehabilitation ◽  
Leap Motion Controller ◽  
Cord Injury

BACKGROUND: There is a growing interest in the use of technology in the field of neurorehabilitation in order to quantify and generate knowledge about sensorimotor disorders after neurological diseases, understanding that the technology has a high potential for its use as therapeutic tools. Taking into account that the rehabilitative process of motor disorders should extend beyond the inpatient condition, it’s necessary to involve low-cost technology, in order to have technological solutions that can approach the outpatient period at home. OBJECTIVE: to present the virtual applications-based RehabHand prototype for the rehabilitation of manipulative skills of the upper limbs in patients with neurological conditions and to determine the target population with respect to spinal cord injured patients. METHODS: Seven virtual reality applications have been designed and developed with a therapeutic sense, manipulated by means of Leap Motion Controller. The target population was determined from a sample of 40 people, healthy and patients, analyzing hand movements and gestures. RESULTS: The hand movements and gestures were estimated with a fitting rate between the range 0.607–0.953, determining the target population by cervical levels and upper extremity motor score. CONCLUSIONS: Leap Motion is suitable for a determined sample of cervical patients with a rehabilitation purpose.

Upper-limb Rehabilitation Robot Based on Motor Imagery EEG

ROBOT ◽  
2011 ◽  
Vol 33 (3) ◽  
pp. 307-313 ◽  
Author(s):  
Baoguo XU ◽  
Si PENG ◽  
Aiguo SONG
Keyword(s):  
Motor Imagery ◽  
Upper Limb ◽  
Rehabilitation Robot ◽  
Upper Limb Rehabilitation ◽  
Limb Rehabilitation

Upper-limb Rehabilitation Robot Motion Control Based on Dynamic Interpolation

ROBOT ◽  
2012 ◽  
Vol 34 (5) ◽  
pp. 539 ◽  
Author(s):  
Lizheng PAN ◽  
Aiguo SONG ◽  
Guozheng XU ◽  
Huijun LI ◽  
Baoguo XU
Keyword(s):  
Motion Control ◽  
Upper Limb ◽  
Robot Motion ◽  
Rehabilitation Robot ◽  
Upper Limb Rehabilitation ◽  
Limb Rehabilitation

scholarly journals Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2146
Author(s):  
Manuel Andrés Vélez-Guerrero ◽  
Mauro Callejas-Cuervo ◽  
Stefano Mazzoleni
Keyword(s):  
Artificial Intelligence ◽  
Upper Limb ◽  
Main Trend ◽  
Motor Rehabilitation ◽  
Rehabilitation Process ◽  
Upper Limb Rehabilitation ◽  
Multiple Sensors ◽  
Meta Analyses ◽  
Limb Rehabilitation ◽  
And Control

Processing and control systems based on artificial intelligence (AI) have progressively improved mobile robotic exoskeletons used in upper-limb motor rehabilitation. This systematic review presents the advances and trends of those technologies. A literature search was performed in Scopus, IEEE Xplore, Web of Science, and PubMed using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology with three main inclusion criteria: (a) motor or neuromotor rehabilitation for upper limbs, (b) mobile robotic exoskeletons, and (c) AI. The period under investigation spanned from 2016 to 2020, resulting in 30 articles that met the criteria. The literature showed the use of artificial neural networks (40%), adaptive algorithms (20%), and other mixed AI techniques (40%). Additionally, it was found that in only 16% of the articles, developments focused on neuromotor rehabilitation. The main trend in the research is the development of wearable robotic exoskeletons (53%) and the fusion of data collected from multiple sensors that enrich the training of intelligent algorithms. There is a latent need to develop more reliable systems through clinical validation and improvement of technical characteristics, such as weight/dimensions of devices, in order to have positive impacts on the rehabilitation process and improve the interactions among patients, teams of health professionals, and technology.

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