Effect of human-robot interaction on muscular synergies on healthy people and post-stroke chronic patients

Scano, Alessandro; Chiavenna, Andrea; Caimmi, Marco; Malosio, Matteo; Tosatti, Lorenzo Molinari; Molteni, Franco

doi:10.1109/icorr.2017.8009302

Cited by 4 publications

(6 citation statements)

References 11 publications

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“…Such a synergy is a stabilizing synergy that prepares the shoulder to the elevation. It resembles clearly the second synergy that was found in Scano et al ( 2017 ). The second, third, and fourth synergies found in d’Avella et al ( 2006 ) are instead related, respectively, to elbow extension, shoulder flexion, and a complement to the previous two functions, respectively.…”

Section: Methodssupporting

confidence: 86%

“…The coupling was probably observed due to the fact that shoulder and elbow move with similar timing and the algorithm, applied to fewer muscles in the present study, coupled them naturally. S1 in Scano et al ( 2017 ) is thus correspondent to the second and third synergies found in d’Avella et al ( 2006 ). The fourth and fifth synergies found in d’Avella et al ( 2006 ) include muscles that were not included in the present study and of minor relevance in reaching production.…”

Section: Methodssupporting

confidence: 71%

“…Cluster 1 includes patients that show coactivation patterns that are similar to the ones of healthy subjects (d’Avella et al, 2006 ; Scano et al, 2017 ). Overall, Cluster 1 shows the highest mean scores both in RPS and FMA.…”

Section: Discussionmentioning

confidence: 99%

“…In a previous study on healthy people (Scano et al, 2017 . ), the pattern portrayed in Figure 3 was found.…”

Section: Methodsmentioning

confidence: 96%

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Muscle Synergies-Based Characterization and Clustering of Poststroke Patients in Reaching Movements

Scano

Chiavenna

Malosio

et al. 2017

Front. Bioeng. Biotechnol.

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BackgroundA deep characterization of neurological patients is a crucial step for a detailed knowledge of the pathology and maximal exploitation and customization of the rehabilitation therapy. The muscle synergies analysis was designed to investigate how muscles coactivate and how their eliciting commands change in time during movement production. Few studies investigated the value of muscle synergies for the characterization of neurological patients before rehabilitation therapies. In this article, the synergy analysis was used to characterize a group of chronic poststroke hemiplegic patients.MethodsTwenty-two poststroke patients performed a session composed of a sequence of 3D reaching movements. They were assessed through an instrumental assessment, by recording kinematics and electromyography to extract muscle synergies and their activation commands. Patients’ motor synergies were grouped by the means of cluster analysis. Consistency and characterization of each cluster was assessed and clinically profiled by comparison with standard motor assessments.ResultsMotor synergies were successfully extracted on all 22 patients. Five basic clusters were identified as a trade-off between clustering precision and synthesis power, representing: healthy-like activations, two shoulder compensatory strategies, two elbow predominance patterns. Each cluster was provided with a deep characterization and correlation with clinical scales, range of motion, and smoothness.ConclusionThe clustering of muscle synergies enabled a pretherapy characterization of patients. Such technique may affect several aspects of the therapy: prediction of outcomes, evaluation of the treatments, customization of doses, and therapies.

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Section: Methodssupporting

confidence: 86%

Section: Methodssupporting

confidence: 71%

Section: Discussionmentioning

confidence: 99%

“…In a previous study on healthy people (Scano et al, 2017 . ), the pattern portrayed in Figure 3 was found.…”

Section: Methodsmentioning

confidence: 96%

See 2 more Smart Citations

Muscle Synergies-Based Characterization and Clustering of Poststroke Patients in Reaching Movements

Scano

Chiavenna

Malosio

et al. 2017

Front. Bioeng. Biotechnol.

View full text Add to dashboard Cite

show abstract

“…Merging, on the other hand, consists in the expression of two or more synergies in a single pattern, and it is typical of very low-functioning patients. Scano et al ( 2017 ) found that a small population of stroke survivors could be correlated with a limited set of patterns that were partially related to their motor functionality. Lunardini et al ( 2017 ) conducted a muscle synergy analysis on the upper limb muscles of children with dystonia and age-matched healthy controls while they completed various writing tasks.…”

Section: Introductionmentioning

confidence: 99%

Robotic Assistance for Upper Limbs May Induce Slight Changes in Motor Modules Compared With Free Movements in Stroke Survivors: A Cluster-Based Muscle Synergy Analysis

Scano

Chiavenna

Malosio

et al. 2018

Front. Hum. Neurosci.

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Background: The efficacy of robot-assisted rehabilitation as a technique for achieving motor recovery is still being debated. The effects of robotic assistance are generally measured using standard clinical assessments. Few studies have investigated the value of human-centered instrumental analysis, taking the modular organization of the human neuromotor system into account in assessing how stroke survivors interact with robotic set-ups. In this paper, muscle synergy analysis was coupled with clustering procedures to elucidate the effect of human-robot interaction on the spatial and temporal features, and directional tuning of motor modules during robot-assisted movements.Methods: Twenty-two stroke survivors completed a session comprising a series of hand-to-mouth movements with and without robotic assistance. Patients were assessed instrumentally, recording kinematic, and electromyographic data to extract spatial muscle synergies and their temporal components. Patients' spatial synergies were grouped by means of a cluster analysis, matched pairwise across conditions (free and robot-assisted movement), and compared in terms of their spatial and temporal features, and directional tuning, to examine how robotic assistance altered their motor modules.Results: Motor synergies were successfully extracted for all 22 patients in both conditions. Seven clusters (spatial synergies) could describe the original datasets, in both free and robot-assisted movements. Interacting with the robot slightly altered the spatial synergies' features (to a variable extent), as well as their temporal components and directional tuning.Conclusions: Slight differences were identified in the characteristics of spatial synergies, temporal components and directional tuning of the motor modules of stroke survivors engaging in free and robot-assisted movements. Such effects are worth investigating in the framework of a modular description of the neuromusculoskeletal system to shed more light on human-robot interaction, and the effects of robotic assistance and rehabilitation.

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Machine Learning Applied to Neuroreabilitation: A Systematic Mapping

Fernandes

Santana

2020

JADI

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Machine learning and recommendation systems are tools used to improve the search indices of the most relevant items in large amounts of data that can be applied in the health area. To present a systematic mapping in the area of neurorehabilitation that uses machine learning. Analyze the references of the work carried out involving the theme on the application of machine learning in the area of neurorehabilitation. Search for studies enrolled in databases through logical operators for the selection of peer-reviewed journal articles. In addition, it was verified that the application of the systematic mapping in the elaboration of the bibliographic review allows to identify the main gaps for the development of new research, and to direct to the main publications related to the study. Therefore, it is necessary to promote this area of research to offer this public access to the techniques of neuro-rehabilitation as a form of treatment, acquisition of knowledge, motivation or even inclusion. In this way, it will be possible to obtain a greater maturity in the obtained results and, thus, to promote a systematization in the use of neuro-rehabilitation in the promotion of the well-being of these people.

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Effect of human-robot interaction on muscular synergies on healthy people and post-stroke chronic patients

Cited by 4 publications

References 11 publications

Muscle Synergies-Based Characterization and Clustering of Poststroke Patients in Reaching Movements

Muscle Synergies-Based Characterization and Clustering of Poststroke Patients in Reaching Movements

Robotic Assistance for Upper Limbs May Induce Slight Changes in Motor Modules Compared With Free Movements in Stroke Survivors: A Cluster-Based Muscle Synergy Analysis

Machine Learning Applied to Neuroreabilitation: A Systematic Mapping

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