Modeling the assessment of the upper limb motor function impairment in children with cerebral palsy using sEMG and IMU sensors

Raouafi, Sana; Raison, Maxime; Sofiane, A

doi:10.1101/748202

Cited by 3 publications

(5 citation statements)

References 18 publications

(20 reference statements)

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“…In our recent study, the eight EMG features were the top ranked features among each category of sEMG features. Moreover, adding mean IMU-ACC provided the best classification accuracy in distinguishing TD, children with CP preand post-Robot-AT during the circle task [28]. The results support our hypothesis that Robot-AT would increase ULMFI values in children with CP and that levels of muscle activation would be closer to those of TD children (Figure 1 (b)) and Figure 2).…”

Section: Discussionsupporting

confidence: 80%

“…From our previous study [28], the best accuracy to differentiate between TD children and children with CP pre-and post-Robot-AT was obtained during the circle task. Each child had to draw a circle with a 4-cm radius using REAplan.…”

Section: Feature Selectionmentioning

confidence: 95%

“…Furthermore, two TD children were excluded due to missing data from two UL kinematic data during evaluation with REAplan. [28].…”

Section: Participants and Experimental Protocolmentioning

confidence: 99%

“…Among all extracted features, eight EMG and one IMU-ACC features provided enough information to distinguish between healthy children and children with CP pre-robot-AT and post-robot-AT [28]. Each EMG and IMU-ACC feature can be arranged as an 8-element vector for all channels.…”

Section: Calculation Of Similarity Indicesmentioning

confidence: 99%

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Robot-Assisted Therapy Influence on Kinematic and EMG Activity in the Upper Limb for Children with Cerebral Palsy

Raouafi¹,

Raison²,

Achiche³

2020

Preprint

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Aim: To develop an index for quantitative assessment of the upper limb motor function in children with cerebral palsy before and after robot-assisted therapy. Method: An upper limb motor function index was developed using kinematic, surface electromyography and three-axis inertial measurements unit data collected from 15 children with cerebral palsy (CP) and 15 typically developed children. Children with CP underwent 18 robot-assisted therapy sessions with the REAplan device. All children were evaluated, using kinematic data from the REAplan, electromyography and three-axis inertial measurements unit readings from its accelerometer. A principal component analysis was conducted to produce an evaluation index, which is able to detect the deviation from the upper limb motor function of typically developing children group. Children with CP were evaluated twice before and after the intervention with Box and Blocks test and Finger-To-Nose test. The discriminative and concurrent validity of the upper limb motor function index were investigated. Results: The upper limb motor function index was higher in children with CP post therapy (p<0.001). Finger-To-Nose test values improved after robot-assisted therapy (p<0.03). A weak but positive correlation was observed between upper limb motor function index and clinical tests (r=0.012, p=0.95 and r=0.13, p= 0.54 for Box and Blocks test and Finger-To-Nose test respectively). Interpretation: The upper limb motor function index successfully differentiated between the typically developing children and children with CP and was effective in assessing the improvement of the upper limb motor function after robot-assisted therapy. The upper limb motor function index could be extended to assess and monitor rehabilitation therapies of other populations, such as those with stroke and Parkinson’s disease.

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Section: Discussionsupporting

confidence: 80%

Section: Feature Selectionmentioning

confidence: 95%

“…Furthermore, two TD children were excluded due to missing data from two UL kinematic data during evaluation with REAplan. [28].…”

Section: Participants and Experimental Protocolmentioning

confidence: 99%

Section: Calculation Of Similarity Indicesmentioning

confidence: 99%

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Robot-Assisted Therapy Influence on Kinematic and EMG Activity in the Upper Limb for Children with Cerebral Palsy

Raouafi¹,

Raison²,

Achiche³

2020

Preprint

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“…On the other hand, it is important to highlight that the sEMG is a very well-known and commonly used technique in the diagnosis and in monitoring the evolution of patients suffering from different motor impairments. In fact, sEMG has become an important technique for both analyzing the movements and assessing the motor function impairment of children with motor disabilities, as it provides crucial information regarding muscle coordination ( Schmidt-Rohlfing et al, 2006 ; Wei et al, 2019 ; Bauer, Mall & Jung , 2018 ; Raouafi, Raison & Sofiane, 2019 ). Owing to sEMG, information regarding muscle activation, myoelectric manifestation of muscle fatigue, and recruitment of motor units can be obtained ( Garcia & Vieira, 2011 ).…”

Section: Introductionmentioning

confidence: 99%

A 3D-printed passive exoskeleton for upper limb assistance in children with motor disorders: proof of concept through an electromyography-based assessment

Sánchez

Blanco

Río

et al. 2023

PeerJ

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The rehabilitation of children with motor disorders is mainly focused on physical interventions. Numerous studies have demonstrated the benefits of upper function using robotic exoskeletons. However, there is still a gap between research and clinical practice, owing to the cost and complexity of these devices. This study presents a proof of concept of a 3D-printed exoskeleton for the upper limb, following a design that replicates the main characteristics of other effective exoskeletons described in the literature. 3D printing enables rapid prototyping, low cost, and easy adjustment to the patient anthropometry. The 3D-printed exoskeleton, called POWERUP, assists the user’s movement by reducing the effect of gravity, thereby allowing them to perform upper limb exercises. To validate the design, this study performed an electromyography-based assessment of the assistive performance of POWERUP, focusing on the muscular response of both the biceps and triceps during elbow flexion–extension movements in 11 healthy children. The Muscle Activity Distribution (MAD) is the proposed metric for the assessment. The results show that (1) the exoskeleton correctly assists elbow flexion, and (2) the proposed metric easily identifies the exoskeleton configuration: statistically significant differences (p-value = 2.26 ⋅ 10−7 < 0.001) and a large effect size (Cohen’s d = 3.78 > 0.8) in the mean MAD value were identified for both the biceps and triceps when comparing the transparent mode (no assistance provided) with the assistive mode (anti-gravity effect). Therefore, this metric was proposed as a method for assessing the assistive performance of exoskeletons. Further research is required to determine its usefulness for both the evaluation of selective motor control (SMC) and the impact of robot-assisted therapies.

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Advances in Cerebral Palsy Treatment

Nahar,

Jain,

Paul

2024

ENG

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Background: Cerebral palsy is a complex neurodevelopmental disorder with various etiological factors and treatment options. This narrative review aimed to summarize the causes of cerebral palsy, identify areas needing additional research in treatment approaches, and highlight areas requiring further investigation. In order to provide a thorough overview of management techniques to lessen the effects of the illness and its consequences, this review has drawn data from a number of studies. Introduction: Prematurity increases the risk of brain damage during the developing stage and accounts for a sizable fraction of cerebral palsy cases. In a sizable portion of cases, maternal diabetes and hypertension are listed as the main causes. Damage to the brain tissue results from hypoxic-ischemic injuries sustained during pregnancy that upset the equilibrium of oxidants and antioxidants. To alter the oxidative stress pathway and ease related issues, pharmacological treatments, such as therapeutic hypothermia, free radical inhibition therapy, and mitochondrial therapy, have been proposed. Therapeutic strategies, such as physiotherapy, occupational therapy, speech therapy, and surgical interventions, have added quality to the lives of the children. Some of the most recent developments in this area include the development of biomarkers for muscle activity detection, machine learning to predict the types of cerebral palsy and abnormal movements, disease prediction with eye images, wireless inertia measuring unit for spasticity detection, computer-based video analysis of typical and atypical infants, identification of intellectual disabilities with algorithms, and deep learning methods for predicting cerebral palsy. Methods: This narrative review is based on a careful analysis of numerous researches conducted on cerebral palsy, which have served as the basis for statistical distribution. It reviews the causes of cerebral palsy, available treatments, and ongoing research with the goal of providing physicians and researchers in the field with useful information. The objectives, study questions, inclusion criteria, and search approach have all been outlined in a thorough protocol. To find pertinent research published up to September 2021, a literature search was carried out using electronic databases, including Google Scholar, PubMed, Cochrane Library, Scopus, and Web of Science. A combination of pertinent keywords, such as "cerebral palsy," "management," "technology," "wearable technology," "prematurity," and "artificial intelligence," has been used in the search approach. Results: Recent advances in the field include the discovery of biomarkers for the detection of muscle activity, machine learning algorithms to predict the types of cerebral palsy and abnormal movements, disease prediction using eye images, wireless inertia measuring units for the detection of spasticity, computer-based video analysis for the detection of atypical infants, and algorithms to identify intellectual disabilities. Additionally, employing technologies, like virtual reality systems, electrical stimulators, activity trackers, machine learning, and deep learning approaches, has shown promise in evaluating, diagnosing, and predicting treatment outcomes linked to gait, upper limb, and lower limb function. Conclusion: Future research should examine the clinical application of nanomedicine, stem cell therapy, and cutting-edge therapeutic strategies to prevent hypoxic-ischemic damage in the developing brain. Additionally, research is required to effectively assist children with severe speech difficulties using alternate communication modalities and cutting-edge computational tools. The outcomes for people with cerebral palsy can be improved by combining interdisciplinary efforts with cutting-edge technological interventions.

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Modeling the assessment of the upper limb motor function impairment in children with cerebral palsy using sEMG and IMU sensors

Cited by 3 publications

References 18 publications

Robot-Assisted Therapy Influence on Kinematic and EMG Activity in the Upper Limb for Children with Cerebral Palsy

Robot-Assisted Therapy Influence on Kinematic and EMG Activity in the Upper Limb for Children with Cerebral Palsy

A 3D-printed passive exoskeleton for upper limb assistance in children with motor disorders: proof of concept through an electromyography-based assessment

Advances in Cerebral Palsy Treatment

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