Publications by authors named "H Agopyan"

Introduction: Recently, interest in quantifying upper limb function in cerebral palsy has grown. However, the lack of reference tasks and protocols, have hindered the development of quantified movement analysis in clinical practice. This study aimed to evaluate existing instrumented assessments of upper limb function in cerebral palsy, with a focus on their clinical applicability, to identify reasons for the lack of adoption and provide recommendations for improving clinical relevance and utility.

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Background: Infants at high-risk of unilateral Cerebral Palsy (UCP) may have asymmetry in upper extremity movement and function, which should be identified as soon as possible for management.

Aims: To explore the feasibility of using two AX3 Axivity monitors in wrist-worn bracelets to quantify movements, and to identify whether accelerometry parameters are consistent with hand function.

Methods And Procedures: 6 infants at high risk of UCP (aged 3 to -12 months) were included in a Single-Case Experimental Design to explore the impact of an 8-week bimanual stimulation home program.

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Visual feedback is used in different research areas, including clinical science and neuroscience. In this study, we investigated the influence of the visualization of a real-time personalized avatar on gait parameters, focusing on knee flexion during the swing phase. We also studied the impact of the modification of avatar's knee amplitude on kinematic of the knee of healthy subjects.

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The use of Serious Games (SG) in the health domain is expanding. In the field of neurodegenerative disorders (ND) such as Alzheimer's disease, SG are currently employed both to support and improve the assessment of different functional and cognitive abilities, and to provide alternative solutions for patients' treatment, stimulation, and rehabilitation. As the field is quite young, recommendations on the use of SG in people with ND are still rare.

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The purpose of this investigation was to analyze the validity of an iPhone application (Runmatic) for measuring running mechanics. To do this, 96 steps from 12 different runs at speeds ranging from 2.77-5.

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