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Artigo em Inglês | MEDLINE | ID: mdl-25570891

RESUMO

Neurological disorders such as cerebral palsy commonly result in abnormal muscle hyperactivity that negatively effects functional use of the affected limbs. Individuals with cerebral palsy often present with a mix of spasticity and dystonia, and it can be difficult to distinguish between the effects of these types of abnormal tone. Different types of abnormal tone respond differently to treatments such as deep brain stimulation and baclofen. Conventional clinical evaluation techniques provide minimal information for distinguishing abnormal tone characteristics and changes from treatment. Devices that quantify abnormal tone characteristics can help distinguish between the effects of different types of abnormal muscle tone, and help to quantify treatment effects. This paper discusses the development and initial evaluation of MyoSense(TM), a clinician worn device for the quantification and differentiation of abnormal muscle tone. MyoSense evaluates the orientation, speed, and force during clinician manipulation of the affected limbs with a protocol that is similar to conventional practice for evaluating abnormal tone. Evaluation of the MyoSense device, using a mechanical apparatus to simulate abnormal muscle tone, showed good resolution of abnormal tone characteristics. Using a procedure directly modeled after conventional clinical evaluation of abnormal tone, MyoSense data showed good correlation with simulated profiles, 0.8 for spasticity and 0.93 for hypertonia. Evaluation of average change across different limb manipulation speeds, to mitigate acceleration and mechanical effects, resulted in MyoSense data correlations to simulated profiles of 0.99 for spasticity, spasticity with a catch, and dystonia. Overall these results show promise for future clinical evaluation of the MyoSense device.


Assuntos
Monitorização Ambulatorial/métodos , Espasticidade Muscular/fisiopatologia , Tono Muscular/fisiologia , Aceleração , Acelerometria/métodos , Paralisia Cerebral/diagnóstico , Paralisia Cerebral/fisiopatologia , Simulação por Computador , Estimulação Encefálica Profunda , Desenho de Equipamento , Dedos/fisiologia , Mãos/fisiologia , Humanos , Processamento de Sinais Assistido por Computador
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