Background: Individuals with hypertrophic cardiomyopathy (HCM) may be asymptomatic or display activity-limiting symptoms. A common cause of symptoms is left ventricular outflow tract obstruction (LVOTO), which may impact the individuals' ability to undertake physical activity. This study sought to examine daily step count as a potential marker of exercise capacity, which may represent a proxy marker of disease severity in HCM.
Methods: A cross-sectional study of 63 HCM patients was conducted from March to November 2015. Participants wore an ActiGraph GT3X+ (Pensacola, Florida, USA) accelerometer for 7 days. Minutes per day of light, moderate and vigorous physical activity and step count were calculated, and those with LVOTO were compared to those without. Similarly, those with good functional capacity (New York Heart Association; NYHA class I) were compared to those with NYHA class II-IV.
Results: The majority of HCM patients were male (n=45, 71%) with mean age of 48.8±14.9years. Hypertrophic cardiomyopathy patients with history of LVOTO and those NYHA class II-IV took significantly fewer steps per day (LV obstruction: 5527±2370 versus 7027±2095, p=0.01 and NYHA: 5346±1898 versus 6801±2339, p=0.03). No differences were observed across the different intensities of physical activity.
Conclusions: Measurement of daily step count may be a useful and simple tool to determine exercise capacity and provide an indicator of disease severity in individuals with HCM.
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http://dx.doi.org/10.1016/j.hlc.2017.12.012 | DOI Listing |
Sci Rep
March 2025
College of Education, University of the Visayas, Cebu, 6000, Philippines.
As society ages, improving the health of the elderly through effective training programs has become a pressing issue. Virtual reality (VR) technology, with its immersive experience, is increasingly being utilized as a vital tool in rehabilitation training for the elderly. To further enhance training outcomes and improve health conditions among the elderly, this work proposes an integrated model that combines the Generative Adversarial Network (GAN), Variational Autoencoder (VAE), and Long Short-Term Memory (LSTM) network.
View Article and Find Full Text PDFJ Med Internet Res
March 2025
Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Background: The application of intelligent robots in therapy is becoming more and more important for people with dementia. More extensive research is still needed to evaluate its impact on behavioral and psychological dementia symptoms, as well as quality of life in different care settings.
Objective: The purpose of this research is to methodically assess how well intelligence robot interventions work for patients with dementia.
J Vis Exp
February 2025
Department of Artificial Intelligence, Faculty of Computer Science and Information Technology, Universiti Malaya;
This study aims to validate the accuracy of low-cost fitness smartwatches by comparing their data with gold-standard measurements for cardiovascular and physical activity parameters. The study enrolled 50 subjects, 26 undergoing validation testing for heart rate, blood oxygen saturation (SpO2), and sleep data against polysomnography (PSG). Additionally, 24 subjects participated in the 3-Minute Walk Test (3MWT) and Stairs Climbing (SC), with step counts validated against manual video calculations.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
March 2025
Gait abnormalities are common in the older population owing to aging- and disease-related changes in physical and neurological functions. Differentiating the causes of gait abnormalities is challenging because various abnormal gaits share a similar pattern in older patients. Herein, we propose a deep neural network (DNN) model to classify disease-specific gait patterns in older adults using commercialized instrumented insoles.
View Article and Find Full Text PDFInt J Biometeorol
March 2025
Department of Agricultural, Food and Nutritional Science, Faculty of Agricultural, Life and Environmental Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
Livestock production is increasingly at risk from rising temperatures under global warming. Despite this, how temperature increases impact the behavior of cattle on pasture is not fully understood. This research reports on patterns of beef cattle activity, including step counts and lying time, during the summer and fall grazing seasons of 2021, coincident with an unusual period of elevated temperatures and heat load within a northern temperate rangeland of Alberta, Canada.
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