MATHEUS SILVA D'ALENCAR
Projetos de Pesquisa
Unidades Organizacionais
LIM/54 - Laboratório de Bacteriologia, Hospital das Clínicas, Faculdade de Medicina
18 resultados
Resultados de Busca
Agora exibindo 1 - 10 de 18
conferenceObject A Short-period of Physical Activity Using Exergames was able to Promote Improvements in Endurance of People Living with Parkinson's Disease(2018) BARBOSA, Pamela Yuki; FALCONI, Amarilis; KAWAI, Katia; ALMEIDA, Aline Carvalho de; OKAMOTO, Erika; GUELFI, Erica Neves; D'ALENCAR, Matheus; PIEMONTE, Maria ElisaconferenceObject Manual and Verbal guidance during the balance training based in virtual reality is essential for therapeutic results in people with Parkinson's disease: a randomized clinical trial(2017) PIEMONTE, M. E. Pimentel; FALCONI, A.; D'ALENCAR, M.; OKAMOTO, E.- Goalkeeper Game: A New Assessment Tool for Prediction of Gait Performance Under Complex Condition in People With Parkinson's Disease(2020) STERN, Rafael B.; D'ALENCAR, Matheus Silva; USCAPI, Yanina L.; GUBITOSO, Marco D.; ROQUE, Antonio C.; HELENE, Andre F.; PIEMONTE, Maria Elisa PimentelBackground: People with Parkinson's disease (PD) display poorer gait performance when walking under complex conditions than under simple conditions. Screening tests that evaluate gait performance changes under complex walking conditions may be valuable tools for early intervention, especially if allowing for massive data collection. Objectives: To investigate the use of the Goalkeeper Game (GG) to predict impairment in gait performance under complex conditions in people with Parkinson's disease (PPD) and compare its predictive power with the one of the Montreal Cognitive Assessment (MoCA) test. Methods: 74 PPD (HY stages: 23 in stage 1; 31 in stage 2; 20 in stage 3), without dementia (MoCA cut-off 21), tested in ON period with dopaminergic medication were submitted to single individual cognitive/motor evaluation sessions. MoCA and GG were used to assess cognition, and the dynamic gait index (DGI) test was used to assess gait performance under complex condition. GG test resulted in 9 measures extracted via a statistical model. The predictive power of the GG measures and the MoCA score with respect to gait performance, as assessed by DGI, were compared. Results: The predictive models based on GG obtained a better score of prediction (65%) then MoCA (56%) for DGI scores (at a 50% specificity). Conclusion: GG is a novel tool for noninvasive screening that showed a superior predictive power in assessing gait performance under complex condition in people with PD than the well-established MoCa test.
conferenceObject Stability of Parkinson's Disease Subtypes Based on Cluster Analysis in a Large Cohort(2018) D'ALENCAR, Matheus; PENA, Norberto; MIRANDA, Jose Vivas; PIEMONTE, Maria Elisa- A non-expensive bidimensional kinematic balance assessment can detect early postural instability in people with Parkinson's disease(2023) SANTOS, Gabriel Venas; D'ALENCAR, Matheus Silva; HELENE, Andre Frazao; ROQUE, Antonio C.; MIRANDA, Jose Garcia Vivas; PIEMONTE, Maria Elisa PimentelBackgroundPostural instability is a debilitating cardinal symptom of Parkinson's disease (PD). Its onset marks a pivotal milestone in PD when balance impairment results in disability in many activities of daily living. Early detection of postural instability by non-expensive tools that can be widely used in clinical practice is a key factor in the prevention of falls in widespread population and their negative consequences.ObjectiveThis study aimed to investigate the effectiveness of a two-dimensional balance assessment to identify the decline in postural control associated with PD progression.MethodsThis study recruited 55 people with PD, of which 37 were men. Eleven participants were in stage I, twenty-three in stage II, and twenty-one in stage III. According to the Hoehn and Yahr (H&Y) rating scale, three clinical balance tests (Timed Up and Go test, Balance Evaluation Systems Test, and Push and Release test) were carried out in addition to a static stance test recorded by a two-dimensional movement analysis software. Based on kinematic variables generated by the software, a Postural Instability Index (PII) was created, allowing a comparison between its results and those obtained by clinical tests.ResultsThere were differences between sociodemographic variables directly related to PD evolution. Although all tests were correlated with H&Y stages, only the PII was able to differentiate the first three stages of disease evolution (H&Y I and II: p = 0.03; H&Y I and III: p = 0.00001; H&Y II and III: p = 0.02). Other clinical tests were able to differentiate only people in the moderate PD stage (H&Y III).ConclusionBased on the PII index, it was possible to differentiate the postural control decline among the first three stages of PD evolution. This study offers a promising possibility of a low-cost, early identification of subtle changes in postural control in people with PD in clinical practice.
conferenceObject The severity of motor symptoms and depression are the higher predictor for the decrease in daily living activities independence in people with Parkinson's disease(2018) DIAS, C. Dionizio; OKAMOTO, E.; MIRANDA, C.; D'ALENCAR, M.; PIEMONTE, M. E.conferenceObject Balance training in virtual reality promotes superior generalization of gains in postural control to functionality in comparison conventional training - a randomized clinical trial(2017) OLIVEIRA, T. de Paula; MIRANDA, C. Souza; D'ALENCAR, M. Silva; LOURENCO, M.; FRISO, B. Anielle; CANESSO, E. Cervi; YUN, B.; MARQUES, A. Pasqual; PIEMONTE, M. E. PimentalconferenceObject Association between deficiencies in implicit learning and dual-task gait performance and balance control in patients with Parkinson's disease(2017) PIEMONTE, Maria Elisa; D'ALENCAR, Matheus; MONTE, Bruno; HELENE, Andre; GALVES, JeffersonconferenceObject How Can You Achieve a Reliable Qualitative Gait Evaluation Using Only a GoPro (c) Camera?(2018) D'ALENCAR, Matheus; PENA, Norberto; MIRANDA, Jose Vivas; PIEMONTE, Maria ElisaconferenceObject The independence in daily living activities is the best predictor for quality of life in people with Parkinson's disease(2018) DIONIZIO, C.; OKAMOTO, E.; MIRANDA, C.; D'ALENCAR, M.; PIEMONTE, M. E.