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1.
Acta Neurol Scand ; 146(3): 304-317, 2022 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-35788914

RESUMO

BACKGROUND: Telemonitoring, a branch of telemedicine, involves the use of technological tools to remotely detect clinical data and evaluate patients. Telemonitoring of patients with Parkinson's disease (PD) should be performed using reliable and discriminant motor measures. Furthermore, the method of data collection and transmission, and the type of subjects suitable for telemonitoring must be well defined. OBJECTIVE: To analyze differences in patients with PD and healthy controls (HC) with the wearable inertial device SensHands-SensFeet (SH-SF), adopting a standardized acquisition mode, to verify if motor measures provided by SH-SF have a high discriminating capacity and high intraclass correlation coefficient (ICC). METHODS: Altogether, 64 patients with mild-to-moderate PD and 50 HC performed 14 standardized motor activities for assessing bradykinesia, postural and resting tremors, and gait parameters. SH-SF inertial devices were used to acquire movements and calculate objective motor measures of movement (total: 75). For each motor task, five or more biomechanical parameters were measured twice. The results were compared between patients with PD and HC. RESULTS: Fifty-eight objective motor measures significantly differed between patients with PD and HC; among these, 32 demonstrated relevant discrimination power (Cohen's d > 0.8). The test-retest reliability was excellent in patients with PD (median ICC = 0.85 right limbs, 0.91 left limbs) and HC (median ICC = 0.78 right limbs, 0.82 left limbs). CONCLUSION: In a supervised environment, the SH-SF device provides motor measures with good results in terms of reliability and discriminant ability. The reliability of SH-SF measurements should be evaluated in an unsupervised home setting in future studies.


Assuntos
Doença de Parkinson , Dispositivos Eletrônicos Vestíveis , , Marcha , Humanos , Doença de Parkinson/diagnóstico , Reprodutibilidade dos Testes
2.
Physiol Meas ; 40(6): 065005, 2019 07 01.
Artigo em Inglês | MEDLINE | ID: mdl-31018181

RESUMO

OBJECTIVE: Hypomimia is a common and early symptom of Parkinson's disease (PD), which reduces the ability of PD patients to manifest emotions. Currently, it is visually evaluated by the neurologist during neurological examinations for PD diagnosis, as described in task 3.2 of the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Since such an evaluation is semi-quantitative and affected by inter-variability, this paper aims to measure the physiological parameters related to eye blink and facial expressions extracted from a vertical electro-oculogram (VEOG) and facial surface electromyography (fsEMG) to differentiate PD patients from healthy control subjects (HCs). APPROACH: The spontaneous eye blink rate-minute (sEBR), its maximum amplitude (BMP), and facial cutaneous muscle activity were measured in 24 PD patients and 24 HCs while the subjects looked at a visual-tester composed of three main parts: static vision, dynamic vision and reading silently. Specificity and sensitivity for each parameter were calculated. MAIN RESULTS: The VEOG and the fsEMG allowed the identification of some parameters related to eye blink and facial expressions (i.e. sEBR, BMP, frontal and peribuccal muscular activities), being able to distinguish between PD patients and HCs with high sensitivity and specificity. SIGNIFICANCE: The demonstration that the combination of parameters related to eye blink and facial expressions can discriminate (with high accuracy) between PD patients versus HCs, thus resulting in a useful tool to support the neurologist in objective assessment of hypomimia for improving PD diagnosis.


Assuntos
Piscadela/fisiologia , Eletromiografia , Eletroculografia , Expressão Facial , Doença de Parkinson/diagnóstico , Doença de Parkinson/fisiopatologia , Idoso , Área Sob a Curva , Estudos de Casos e Controles , Eletrodos , Feminino , Humanos , Masculino , Curva ROC , Processamento de Sinais Assistido por Computador
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