RESUMO
BACKGROUND: Blood flow restriction (BFR) resistance training has demonstrated efficacy in promoting strength gains beneficial for rehabilitation. Yet, the distinct functional advantages of BFR strength training using high-load and low-load protocols remain unclear. This study explored the behavioral and neurophysiological mechanisms that explain the differing effects after volume-matched high-load and low-load BFR training. METHODS: Twenty-eight healthy participants were randomly assigned to the high-load blood flow restriction (BFR-HL, n = 14) and low-load blood flow restriction (BFR-LL, n = 14) groups. They underwent 3 weeks of BFR training for isometric wrist extension at intensities of 25% or 75% of maximal voluntary contraction (MVC) with matched training volume. Pre- and post-tests included MVC and trapezoidal force-tracking tests (0-75%-0% MVC) with multi-channel surface electromyography (EMG) from the extensor digitorum. RESULTS: The BFR-HL group exhibited a greater strength gain than that of the BFR-LL group after training (BFR_HL: 26.96 ± 16.33% vs. BFR_LL: 11.16 ± 15.34%)(p = 0.020). However, only the BFR-LL group showed improvement in force steadiness for tracking performance in the post-test (p = 0.004), indicated by a smaller normalized change in force fluctuations compared to the BFR-HL group (p = 0.048). After training, the BFR-HL group activated motor units (MUs) with higher recruitment thresholds (p < 0.001) and longer inter-spike intervals (p = 0.002), contrary to the BFR-LL group, who activated MUs with lower recruitment thresholds (p < 0.001) and shorter inter-spike intervals (p < 0.001) during force-tracking. The discharge variability (p < 0.003) and common drive index (p < 0.002) of MUs were consistently reduced with training for the two groups. CONCLUSIONS: BFR-HL training led to greater strength gains, while BFR-LL training better improved force precision control due to activation of MUs with lower recruitment thresholds and higher discharge rates.
Assuntos
Eletromiografia , Treinamento Resistido , Punho , Humanos , Masculino , Treinamento Resistido/métodos , Feminino , Punho/fisiologia , Adulto Jovem , Adulto , Contração Isométrica/fisiologia , Músculo Esquelético/fisiologia , Músculo Esquelético/irrigação sanguínea , Força Muscular/fisiologia , Terapia de Restrição de Fluxo Sanguíneo/métodosRESUMO
Applied behavior analysis (ABA) has become a popular behavioral therapy in the special education needs (SEN) community. ABA is used to manage SEN students' behaviors by solving problems in socially important settings, and puts emphasis on having precise measurements on physical and observable events. In this work, we present how Internet of Things (IoT) technologies can be applied to enhance ABA therapy in normal SEN classroom settings. We measured (1) learning performance data, (2) learners' physiological data, and (3) learning environment sensors' data. Upon preliminary analysis, we have found that learners' physiological data is highly diverse, while learner performance seems to be related to learners' electrodermal activity. Our preliminary findings suggest the possibility of enhancing ABA for SEN with IoT technologies.
Assuntos
Análise do Comportamento Aplicada , Internet das Coisas , Educação Inclusiva , Humanos , AprendizagemRESUMO
BACKGROUND: The real-world relationships between the demographic and clinical characteristics of asthma patients, their prehospitalization management and the frequency of hospitalization due to asthma exacerbation is poorly established. OBJECTIVE: To determine the risk factors of recurrent asthma exacerbations requiring hospitalizations and evaluate the standard of baseline asthma care. METHODS: A territory-wide, multicentre retrospective study in Hong Kong was performed. Medical records of patients aged ≥18 years admitted to 11 acute general hospitals from January 1 to December 31, 2016 for asthma exacerbations were reviewed. RESULTS: There were 2280 patients with 3154 admissions (36.7% male, median age 66.0 [interquartile range: 48.0-81.0] years, 519 had ≥2 admissions). Among them, 1830 (80.3%) had at least one asthma-associated comorbidity, 1060 (46.5%) and 885 (38.9%) of patients had Accident and Emergency Department (AED) attendance and hospitalization in the preceding year, respectively. Patients with advancing age (incidence rate ratio [IRR]: 1.003 for every year increment), a history of AED visits or hospitalization (IRR: 1.018 and 1.070 for every additional episode, respectively) for asthma exacerbation in the preceding year, the presence of neuropsychiatric (IRR: 1.142) and gastrointestinal (IRR: 1.154) comorbidities were risk factors for an increasing number of admissions for asthma exacerbation. For patients with ≥2 admissions, 17.1% were not prescribed inhaled corticosteroid and only 44.6% had spirometry checked before the index admission. Asthma phenotyping was often incomplete, as assessment of atopy (total serum immunoglobulin E level and senitization to aeroallergens) was only performed in 30 (5.8%) patients with ≥2 admissions. CONCLUSIONS AND CLINICAL RELEVANCE: Improving asthma care, especially in elderly patients with a prior history of urgent healthcare utilization and comorbidities, may help reduce healthcare burden. Suboptimal management before the index admission was common in patients hospitalized for asthma exacerbations. Early identification of patients at risk and enhancement of baseline asthma management may help to prevent recurrent asthma exacerbation and subsequent hospitalization.