Use of inertial sensors as devices for upper limb motor monitoring exercises for motor rehabilitation

2015 ◽  
Vol 5 (2) ◽  
pp. 91-102 ◽  
Author(s):  
Alexandre Balbinot ◽  
Jonas Crauss Rodrigues de Freitas ◽  
Daniel Santos Côrrea
Keyword(s):  
Upper Limb ◽  
Inertial Sensors ◽  
Motor 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.

scholarly journals Quality parameters for a multimodal EEG/EMG/kinematic brain-computer interface (BCI) aiming to suppress neurological tremor in upper limbs

F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 282 ◽  
Author(s):  
Giuliana Grimaldi ◽  
Mario Manto ◽  
Yassin Jdaoudi
Keyword(s):  
Upper Limb ◽  
Functional Disability ◽  
Inertial Sensors ◽  
Brain Computer Interface ◽  
Quality Parameters ◽  
Computer Interface ◽  
Upper Limbs ◽  
Original Algorithm ◽  
Daily Life Activities ◽  
New Treatment

Tremor is the most common movement disorder encountered during daily neurological practice. Tremor in the upper limbs causes functional disability and social inconvenience, impairing daily life activities. The response of tremor to pharmacotherapy is variable. Therefore, a combination of drugs is often required. Surgery is considered when the response to medications is not sufficient. However, about one third of patients are refractory to current treatments. New bioengineering therapies are emerging as possible alternatives. Our study was carried out in the framework of the European project “Tremor” (ICT-2007-224051). The main purpose of this challenging project was to develop and validate a new treatment for upper limb tremor based on the combination of functional electrical stimulation (FES; which has been shown to reduce upper limb tremor) with a brain-computer interface (BCI). A BCI-driven detection of voluntary movement is used to trigger FES in a closed-loop approach. Neurological tremor is detected using a matrix of EMG electrodes and inertial sensors embedded in a wearable textile. The identification of the intentionality of movement is a critical aspect to optimize this complex system. We propose a multimodal detection of the intentionality of movement by fusing signals from EEG, EMG and kinematic sensors (gyroscopes and accelerometry). Parameters of prediction of movement are extracted in order to provide global prediction plots and trigger FES properly. In particular, quality parameters (QPs) for the EEG signals, corticomuscular coherence and event-related desynchronization/synchronization (ERD/ERS) parameters are combined in an original algorithm which takes into account the refractoriness/responsiveness of tremor. A simulation study of the relationship between the threshold of ERD/ERS of artificial EEG traces and the QPs is also provided. Very interestingly, values of QPs were much greater than those obtained for the corticomuscular module alone.

scholarly journals Clinical Application of Virtual Reality for Upper Limb Motor Rehabilitation in Stroke: Review of Technologies and Clinical Evidence

2020 ◽  
Vol 9 (10) ◽  
pp. 3369
Author(s):  
Won-Seok Kim ◽  
Sungmin Cho ◽  
Jeonghun Ku ◽  
Yuhee Kim ◽  
Kiwon Lee ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Clinical Application ◽  
Upper Limb ◽  
Stroke Rehabilitation ◽  
Cochrane Library ◽  
Motor Rehabilitation ◽  
Novel Technologies ◽  
Ovid Medline ◽  
Meta Analyses ◽  
The Cochrane Library

Neurorehabilitation for stroke is important for upper limb motor recovery. Conventional rehabilitation such as occupational therapy has been used, but novel technologies are expected to open new opportunities for better recovery. Virtual reality (VR) is a technology with a set of informatics that provides interactive environments to patients. VR can enhance neuroplasticity and recovery after a stroke by providing more intensive, repetitive, and engaging training due to several advantages, including: (1) tasks with various difficulty levels for rehabilitation, (2) augmented real-time feedback, (3) more immersive and engaging experiences, (4) more standardized rehabilitation, and (5) safe simulation of real-world activities of daily living. In this comprehensive narrative review of the application of VR in motor rehabilitation after stroke, mainly for the upper limbs, we cover: (1) the technologies used in VR rehabilitation, including sensors; (2) the clinical application of and evidence for VR in stroke rehabilitation; and (3) considerations for VR application in stroke rehabilitation. Meta-analyses for upper limb VR rehabilitation after stroke were identified by an online search of Ovid-MEDLINE, Ovid-EMBASE, the Cochrane Library, and KoreaMed. We expect that this review will provide insights into successful clinical applications or trials of VR for motor rehabilitation after stroke.

scholarly journals Efficacy and Brain Imaging Correlates of an Immersive Motor Imagery BCI-Driven VR System for Upper Limb Motor Rehabilitation: A Clinical Case Report

2019 ◽  
Vol 13 ◽  
Author(s):  
Athanasios Vourvopoulos ◽  
Carolina Jorge ◽  
Rodolfo Abreu ◽  
Patrícia Figueiredo ◽  
Jean-Claude Fernandes ◽  
...  
Keyword(s):  
Case Report ◽  
Brain Imaging ◽  
Motor Imagery ◽  
Upper Limb ◽  
Clinical Case ◽  
Motor Rehabilitation

scholarly journals Towards a Wearable Wheelchair Monitor: Classification of Push Style Based on Inertial Sensors at Multiple Upper Limb Locations

2018 ◽  
Author(s):  
Roxana Ramirez Herrera ◽  
Behzad Momahed Heravi ◽  
Giulia Barbareschi ◽  
Tom Carlson ◽  
Catherine Holloway
Keyword(s):  
Upper Limb ◽  
Inertial Sensors

scholarly journals Studying Upper-Limb Kinematics Using Inertial Sensors Embedded in Mobile Phones

2015 ◽  
Vol 2 (1) ◽  
pp. e4 ◽  
Author(s):  
Cristina Roldan-Jimenez ◽  
Antonio Cuesta-Vargas ◽  
Paul Bennett
Keyword(s):  
Mobile Phones ◽  
Upper Limb ◽  
Inertial Sensors ◽  
Limb Kinematics

A Multisession Evaluation of a Collaborative Virtual Environment for Arm Rehabilitation

2020 ◽  
Vol 27 (3) ◽  
pp. 274-286
Author(s):  
Maja Goršič ◽  
Imre Cikajlo ◽  
Nika Goljar ◽  
Domen Novak
Keyword(s):  
Exercise Intensity ◽  
Inertial Sensors ◽  
Exercise Duration ◽  
Motor Rehabilitation ◽  
Upper Limb Rehabilitation ◽  
Arm Rehabilitation ◽  
Subacute Stroke ◽  
High Motivation ◽  
Limb Rehabilitation ◽  
Collaborative Sessions

In recent years, several multi-user virtual environments (VEs) have been developed to promote motivation and exercise intensity in motor rehabilitation. While competitive VEs have been extensively evaluated, collaborative and competitive rehabilitation VEs have seen relatively little study. Therefore, this article presents an evaluation of a VE for post-stroke arm rehabilitation that mimics everyday kitchen tasks and can be used either solo or collaboratively. Twenty subacute stroke survivors exercised with the VE for four sessions, with the first and third sessions involving solo exercise and the other two involving collaborative exercise. Exercise intensity was measured using inertial sensors while motivation was measured with questionnaires. Results showed high motivation and exercise intensity over all four sessions, and 11 of 20 participants preferred collaborative over solo exercise while only 4 preferred solo exercise. However, there were no differences in motivation, exercise duration, or exercise intensity between solo and collaborative sessions. Thus, we cannot currently claim that collaborative exercises are beneficial for upper limb rehabilitation. Future studies should evaluate other collaborative VE designs in different settings (e.g., at home) and with different participant pairs (e.g., patient-unimpaired) to find effective ways to utilize collaborative exercises in motor rehabilitation.

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