Objective: To investigate the effect of exercise training on markers of the lipoprotein-lipid profile and inflammatory markers in post-menopausal overweight/obese women with a moderately elevated systolic blood pressure.
Methods: A total of 267 women [mean body mass index (BMI)=32.0+/-5.7kg/m(2) and mean age=57.3+/-6.6 years] underwent a 6-month exercise intervention program. Exercise training was performed 3-4 times per week at a targeted heart rate corresponding to 50% of the maximal oxygen consumption.
Results: Compared to baseline values, mean change in relative VO(2) max (the primary endpoint) was of 1.18+/-2.25mL/minkg (p<0.0001), mean weight loss was of 1.4+/-3.3kg (p<0.0001), mean reduction in waist circumference was of 2.4+/-6.9cm (p<0.0001) and systolic blood pressure did not change significantly (-1.2+/-13.0mmHg, NS). No changes were observed in markers of the lipoprotein-lipid profile. No changes were observed for plasma levels of C-reactive protein, interleukin-6, tumor-necrosis factor-alpha and adiponectin. Changes in VO(2) max were negatively associated with changes in body weight (r=-0.26, p<0.0001) and waist circumference (r=-0.16, p=0.01), but not with changes in cardiometabolic risk markers.
Conclusion: Although exercise training significantly increased cardiorespiratory fitness in these sedentary, but metabolically healthy obese/overweight women with a moderately elevated systolic blood pressure, no significant improvements were observed in their cardiometabolic risk profile.
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http://dx.doi.org/10.1016/j.atherosclerosis.2009.05.009 | DOI Listing |
Sensors (Basel)
December 2024
Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USA.
Flexible high-deflection strain gauges have been demonstrated to be cost-effective and accessible sensors for capturing human biomechanical deformations. However, the interpretation of these sensors is notably more complex compared to conventional strain gauges, particularly during dynamic motion. In addition to the non-linear viscoelastic behavior of the strain gauge material itself, the dynamic response of the sensors is even more difficult to capture due to spikes in the resistance during strain path changes.
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December 2024
Centro de Estudos Egas Moniz, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisbon, Portugal.
Virtual reality (VR) has been used in research and clinical practice in the management of Parkinson's disease (PD), potentially enhancing physiotherapy. Adverse events (AEs) associated with VR applications in PD have been poorly explored. We conducted a randomized controlled trial to compare two 12-week interventions using physiotherapy and immersive VR, and analyzed the frequency and type of AEs occurring in 30 people with PD.
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December 2024
Department of Engineering and Industrial Design, Magdeburg-Stendal University of Applied Sciences, 39110 Magdeburg, Germany.
Inappropriate, excessive, or overly strenuous training of sport horses can result in long-term injury, including the premature cessation of a horse's sporting career. As a countermeasure, this study demonstrates the easy implementation of a biomechanical load monitoring system consisting of five commercial, multi-purpose inertial sensor units non-invasively attached to the horse's distal limbs and trunk. From the data obtained, specific parameters for evaluating gait and limb loads are derived, providing the basis for objective exercise load management and successful injury prevention.
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December 2024
Faculty of Medicine, Department of Kinesiology, Université Laval, Quebec City, QC G1V OA6, Canada.
Foot strike patterns influence vertical loading rates during running. Running retraining interventions often include switching to a new foot strike pattern. Sudden changes in the foot strike pattern may be uncomfortable and may lead to higher step-to-step variability.
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December 2024
Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, Serbia.
This paper presents the development of a robotic system for the rehabilitation and quality of life improvement of children with cerebral palsy (CP). The system consists of four modules and is based on a virtual humanoid robot that is meant to motivate and encourage children in their rehabilitation programs. The efficiency of the developed system was tested on two children with CP.
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