Rehabilitation and Health Care Robotics

Loos, H. F. Machiel Van der; Reinkensmeyer, David J.; Guglielmelli, Eugenio

doi:10.1007/978-3-319-32552-1_64

Cited by 68 publications

(25 citation statements)

References 189 publications

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“…A robotic exoskeleton is an active orthosis device to help patients with mobility and manipulation related disabilities and should be deployable in daily life activities [70]. More specifically, an upper limb exoskeleton is a wearable robot aimed to improve mobility and manipulation of the upper extremities, while a lower limb exoskeleton is a powered multi-joint orthosis that is able to move leg joints without external support.…”

Section: Robotic Exoskeletonsmentioning

confidence: 99%

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Mohebbi

2020

Curr Robot Rep

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Purpose of Review Research in assistive and rehabilitation robotics is a growing, promising, and challenging field emerged due to various social and medical needs such as aging populations, neuromuscular, and musculoskeletal disorders. Such robots can be used in various day-today scenarios or to support motor functionality, training, and rehabilitation. This paper reflects on the human-robot interaction perspective in rehabilitation and assistive robotics and reports on current issues and developments in the field. Recent Findings The survey on the literature reveals that new efforts are put on utilizing machine learning approaches alongside novel developments in sensing technology to adapt the systems with user routines in terms of activities for assistive systems and exercises for rehabilitation devices to fit each user's need and maximize their effectiveness. Summary A review of recent research and development efforts on human-robot interaction in assistive and rehabilitation robotics is presented in this paper. First, different subdomains in assistive and rehabilitation robotic research are identified, and accordingly, a survey on the background and trends of such developments is provided.

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Section: Robotic Exoskeletonsmentioning

confidence: 99%

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Mohebbi

2020

Curr Robot Rep

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“…There is progressively greater evidence that rehabilitation robots are most efficacious when employing a cooperative control strategy versus passive support (Israel et al, 2006;Ziherl et al, 2010;Balasubramanian et al, 2012;Casadio and Sanguineti, 2012;Van der Loos et al, 2016). And it is generally preferred that a rehabilitation robot offer assistance in a way that reflects the level of impairment (Novak and Riener, 2015), which can vary across the workspace: movements in some directions are more proficient than others.…”

Section: Applicationmentioning

confidence: 99%

Clustering of Directions Improves Goodness of Fit in Kinematic Data Collected in the Transverse Plane During Robot-Assisted Rehabilitation of Stroke Patients

Hartigan

Peduzzi

et al. 2018

Front. Robot. AI

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The kinematic character of hand trajectory in reaching tasks varies by movement direction. Often, direction is not included as a factor in the analysis of data collected during multidirectional reach tasks; consequently, this directionally insensitive model (DI) may be prone to type-II error due to unexplained variance. On the other hand, directionally specific models (DS) that account separately for each movement direction, may reduce statistical power by increasing the amount of data groupings. We propose a clustered-bysimilarity (CS) in which movement directions with similar kinematic features are grouped together, maximizing model fit by decreasing unexplained variance while also decreasing uninformative sub-groupings. We tested model quality in measuring change over time in 10 kinematic features extracted from 72 chronic stroke patients participating in the VA-ROBOTICS trial, performing a targeted reaching task over 16 movement directions (8 targets, back-and forth from center) in the horizontal plane. Across 49 participants surviving a quality control sieve, 4.3 ± 1.1 (min: 3; max: 7) clusters were found among the 16 movement directions; clusters varied between participants. Among 49 participants, and averaged across 10 features, the better-fitting model for predicting change in features was found to be CS assessed by the Akaike Information criterion (61.6 ± 7.3%), versus DS (31.0 ± 7.8%) and DI (7.1 ± 7.1%). Confirmatory analysis via Extra Sum of Squares F-test showed the DS and CS models out-performed the DI model in head-to-head (pairwise) comparison in >85% of all specimens. Thus, we find overwhelming evidence that it is necessary to adjust for direction in the models of multi-directional movements, and that clustering kinematic data by feature similarly may yield the optimal configuration for this co-variate.

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“…In this regard, a variety of robot-based devices has been investigated to support clinicians in neurorehabilitation [6,7]. Consequently, there are several studies available that aim to categorize the contribution of this type of system from global or specific perspectives.…”

Section: Introductionmentioning

confidence: 99%

Robotics in Health Care: Perspectives of Robot-Aided Interventions in Clinical Practice for Rehabilitation of Upper Limbs

et al. 2019

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Robot-aided systems to support the physical rehabilitation of individuals with neurological impairment is one of the fields that has been widely developed in the last few decades. However, the adoption of these systems in clinical practice remains limited. In order to better understanding the causes of this limitation, a systematic review of robot-based systems focused on upper extremity rehabilitation is presented in this paper. A systematic search and review of related articles in the literature were conducted. The chosen works were analyzed according to the type of device, the data analysis capability, the therapy method, the human–robot interaction, the safety strategies, and the focus of treatment. As a conclusion, self-adaptation for personalizing the treatments, safeguarding and enhancing of patient–robot interaction towards training essential factors of movement generation into the same paradigm, or the use of lifelike environments in fully-immersive virtual reality for increasing the assimilation of motor gains could be relevant factors to develop more accepted robot-aided systems in clinical practice.

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Rehabilitation and Health Care Robotics

Cited by 68 publications

References 189 publications

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Clustering of Directions Improves Goodness of Fit in Kinematic Data Collected in the Transverse Plane During Robot-Assisted Rehabilitation of Stroke Patients

Robotics in Health Care: Perspectives of Robot-Aided Interventions in Clinical Practice for Rehabilitation of Upper Limbs

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