2017
DOI: 10.1080/17483107.2016.1278467
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The impact of robot-mediated adaptive I-TRAVLE training on impaired upper limb function in chronic stroke and multiple sclerosis

Abstract: Robot-mediated training resulted in improved movement coordination in both groups, as well as clinical improvement in pwMS. Absence of functional improvements in stroke patients may relate to severe upper limb dysfunction at baseline. Implications for Rehabilitation Robot-mediated training improved strength, active range of motion and upper limb capacity in pwMS. Robot-mediated therapy allows for adapted training difficulty.

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Cited by 31 publications
(67 citation statements)
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“…An important finding regards a quite promising and actual development trend: tracking for feedback and training arm (shoulder, elbow, forearm) and hand, together, produced “greater improvement” than such endeavors done separately for the respective anatomic regions (Merians et al, 2009 ). The methods to achieve that require the use of, including haptic-based, virtual reality (VR) facilities (Huang et al, 2012 ; Guo et al, 2013 ; Lin et al, 2013b ; Wei et al, 2013 ; Dowling et al, 2014 ; Song et al, 2014 ; Thielbar et al, 2014 ; Kim and Rosen, 2015 ; Shull and Damian, 2015 ; Grimm et al, 2016 ; Mazzoleni et al, 2017 ; Maris et al, 2018 ). This matches with the conceptual addition of, for instance, Brain Machine Interface (BMI) and/or neuromuscular electrical stimulation (NMES)/FES or transcranial Direct Current Stimulation (tDCS), respectively repetitive transcranial magnetic stimulation (rTMS), facilities usage, too.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…An important finding regards a quite promising and actual development trend: tracking for feedback and training arm (shoulder, elbow, forearm) and hand, together, produced “greater improvement” than such endeavors done separately for the respective anatomic regions (Merians et al, 2009 ). The methods to achieve that require the use of, including haptic-based, virtual reality (VR) facilities (Huang et al, 2012 ; Guo et al, 2013 ; Lin et al, 2013b ; Wei et al, 2013 ; Dowling et al, 2014 ; Song et al, 2014 ; Thielbar et al, 2014 ; Kim and Rosen, 2015 ; Shull and Damian, 2015 ; Grimm et al, 2016 ; Mazzoleni et al, 2017 ; Maris et al, 2018 ). This matches with the conceptual addition of, for instance, Brain Machine Interface (BMI) and/or neuromuscular electrical stimulation (NMES)/FES or transcranial Direct Current Stimulation (tDCS), respectively repetitive transcranial magnetic stimulation (rTMS), facilities usage, too.…”
Section: Discussionmentioning
confidence: 99%
“…Accordingly, such devices enable actuated controlled passive movements using VR or haptic capabilities (“wearables … untethered, ungrounded body worn devices that interact with skin directly or through clothing and can be used in natural environments outside a laboratory,” for “sensory replacement”/“augmentation” or training Shull and Damian, 2015 ). More interesting, for some of them, the haptic and VR facilities are coupled (Song and Guo, 2011 ; Huang et al, 2012 ; Song et al, 2013 , 2014 ; Wei et al, 2013 ; Thielbar et al, 2014 ; Dowling et al, 2014 ; Grimm et al, 2016 ; Guo et al, 2016 ; Mazzoleni et al, 2017 ; Maris et al, 2018 ).…”
Section: Discussionmentioning
confidence: 99%
“…Also, the superiority of digital health metrics for predicting rehabilitation outcomes might be explained by none of the conventional assessments being able to provide metrics specifically capturing impaired grip force coordination as done by the VPIT. When comparing the VPIT to other technology-aided assessments, it becomes apparent that most of them focus more on the evaluation of arm movements with less focus on the hand [21,22,23,25,26,27], which seems to be especially important for relating impairments to their functional impact. Overall, the VPIT emerges as a unique tool able to provide digital health metrics, which complement the clinically available information about impaired body functions.…”
Section: Digital Health Metrics Outperformed Conventional Scales For mentioning
confidence: 99%
“…Similarly, digital health metrics of sensorimotor impairments allow answering certain limitations of con-ventional scales by providing objective and fine-grained information without ceiling effects [20]. Such kinematic and kinetic metrics have found first pioneering applications in pwMS, allowing to better disentangle the mechanisms underlying sensorimotor impairments [21,22,23,24,25,26,27,28]. So far, neither of these techniques has been applied for a personalized prediction of rehabilitation outcomes in pwMS.…”
Section: Introductionmentioning
confidence: 99%
“…Exercise training can improve functional activities of the upper limb and perhaps decrease the rate and extent of disability in PwMS [12][13][14][15][16][17][18]. Facility-based upper limb training programs, whether in a healthcare setting or laboratory, have yielded bene cial outcomes for PwMS [13][14][15][16]. However, lack of access to these programs, especially if one lives in a remote area where there are fewer options or where there are healthcare/medical facilities but no MS experts, may render it di cult to engage in traditional healthcare facility upper limb exercise training programs.…”
Section: Several Studies Have Described a High Percentage Of Upper LImentioning
confidence: 99%