scholarly journals The effect of therapeutic instrumental music performance method on upper extremity functions in adolescent cerebral palsy

Author(s):  
Bilinc Dogruoz Karatekin ◽  
Afitap Icagasioglu
2021 ◽  
Vol 8 ◽  
pp. 205566832110140
Author(s):  
Anuprita Kanitkar ◽  
Sanjay T Parmar ◽  
Tony J Szturm ◽  
Gayle Restall ◽  
Gina Rempel ◽  
...  

Introduction A computer game-based upper extremity (CUE) assessment tool is developed to quantify manual dexterity of children with Cerebral Palsy (CP). The purpose of this study was to determine test-retest reliability of the CUE performance measures (success rate, movement onset time, movement error, and movement variation) and convergent validity with the Peabody Developmental Motor Scale version 2 (PDMS-2) and the Quality of Upper Extremity Skills Test (QUEST). Methods Thirty-five children with CP aged four to ten years were tested on two occasions two weeks apart. Results CUE performance measures of five chosen object manipulation tasks exhibited high to moderate intra-class correlation coefficient (ICC) values. There was no significant difference in the CUE performance measures between test periods. With few exceptions, there was no significant correlation between the CUE performance measures and the PDMS-2 or the QUEST test scores. Conclusions The high to moderate ICC values and lack of systematic errors indicate that the CUE assessment tool has the ability to repeatedly record reliable performance measures of different object manipulation tasks. The lack of a correlation between the CUE and the PDMS-2 or QUEST scores indicates that performance measures of these assessment tools represent distinct attributes of manual dexterity.


2016 ◽  
Vol 20 (3) ◽  
pp. 173-178 ◽  
Author(s):  
Juul Vera Alewijnse ◽  
Ellen M. van Rooijen ◽  
Mick Kreulen ◽  
Mark JC Smeulders ◽  
Siok Swan Tan

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7884
Author(s):  
Celia Francisco-Martínez ◽  
Juan Prado-Olivarez ◽  
José A. Padilla-Medina ◽  
Javier Díaz-Carmona ◽  
Francisco J. Pérez-Pinal ◽  
...  

Quantifying the quality of upper limb movements is fundamental to the therapeutic process of patients with cerebral palsy (CP). Several clinical methods are currently available to assess the upper limb range of motion (ROM) in children with CP. This paper focuses on identifying and describing available techniques for the quantitative assessment of the upper limb active range of motion (AROM) and kinematics in children with CP. Following the screening and exclusion of articles that did not meet the selection criteria, we analyzed 14 studies involving objective upper extremity assessments of the AROM and kinematics using optoelectronic devices, wearable sensors, and low-cost Kinect sensors in children with CP aged 4–18 years. An increase in the motor function of the upper extremity and an improvement in most of the daily tasks reviewed were reported. In the population of this study, the potential of wearable sensors and the Kinect sensor natural user interface as complementary devices for the quantitative evaluation of the upper extremity was evident. The Kinect sensor is a clinical assessment tool with a unique markerless motion capture system. Few authors had described the kinematic models and algorithms used to estimate their kinematic analysis in detail. However, the kinematic models in these studies varied from 4 to 10 segments. In addition, few authors had followed the joint assessment recommendations proposed by the International Society of Biomechanics (ISB). This review showed that three-dimensional analysis systems were used primarily for monitoring and evaluating spatiotemporal variables and kinematic parameters of upper limb movements. The results indicated that optoelectronic devices were the most commonly used systems. The joint assessment recommendations proposed by the ISB should be used because they are approved standards for human kinematic assessments. This review was registered in the PROSPERO database (CRD42021257211).


2018 ◽  
Vol 7 (5) ◽  
pp. 327-334 ◽  
Author(s):  
Jen-Wen Hung ◽  
Yao-Jen Chang ◽  
Chiung-Xia Chou ◽  
Wen-Chi Wu ◽  
Stephen Howell ◽  
...  

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