The American Heart Association emphasizes the importance of assessing levels of physical activity, both in the clinic and within the workplace. They also highlight the need for physicians to objectively assess cardiorespiratory fitness (CRF), as current methods (patient questionnaires) are open to patient bias.Accurate and objective CRF assessments that are based on exercise tolerance are often expensive and require professional facilities and specialist staff to carry out.The new study led by Harvard University researchers suggests that a simple, free test based on push-up capacity could be a useful way to assess CRF.The study, which is the first of its kind, was carried out under the hypothesis that “higher fitness levels would be associated with lower rates of incident CVD.”The researchers used data from fitness tests from over 1,000 firemen in the US state of Indiana. Over a period of ten years, medical records were observed to measure the amount of cardiovascular disease diagnoses.Each participant undertook baseline and periodic physical exams that included push-up capacity and maximal or submaximal exercise tolerance tests between the years 2000 and 2007, with surveillance lasting until 2010.With an average age of 39.6 (the actual ages ranging from 21 to 66), the cohort also had an average body-mass index (BMI) of 28.7. Despite being occupationally active, the cohort’s BMI score of 28.7 put them in the overweight range.Out of 1,104 men, 37 experienced health problems related to CVD, including heart failure, sudden cardiac death, or receiving coronary artery disease diagnoses. The study claims “significant negative associations were found between increasing push-up capacity and CVD events.”Professor Jeremy Pearson stated “this study shows that fitter firefighters have less chance of suffering a heart attack or stroke in the next decade.”Whilst the results may not be revolutionary, the study highlights that ‘push-up tests’ could be a simple, universal, cost-effective way of predicting CVD, potentially with more accuracy than a treadmill based test.Senior author of the study and a specialist in cardiovascular disease Stefanos Kales said that “push-up capacity is positively correlated with aerobic capacity and physical fitness,” and that “these types of objective functional markers are generally good predictors of mortality”.It is important to note that this study dealt with only one group of people, and the study’s results may not be reflected in different groups of people. Other cohorts, such as women or people who are less active, would need to be tested to definitively prove this test’s findings. Source:Yang J., et al. Association Between Push-up Exercise Capacity and Future Cardiovascular Events Among Active Adult Men. JAMA Network Open. 15 February 2019. The narrowing of our arteries with fatty substances, which can eventually lead to heart attacks and strokes, starts early, often in our 20s and 30s. Keeping fit, no matter your age, is an important way to reduce your risk.”Professor Jeremy Pearson, Associate Medical Director, BHF By Lois Zoppi, BAFeb 18 2019Reviewed by Kate Anderton, B.Sc. (Editor)A new study has found a link between the number of push-ups a person is able to do and the risk of cardiovascular disease. The findings show that middle-aged men who are able to complete 10 push-ups could reduce their risk of heart attack and stroke by as much as 97 percent.g-stockstudio | ShutterstockCardiovascular disease (CVD) is the leading cause of death worldwide. It is well documented that smoking, hypertension, diabetes, and lack of physical activity are some of the main risk factors for developing CVD.
Source:https://www.helsinki.fi/en/news/health-news/artificial-intelligence-identifies-key-patterns-from-video-footage-of-infant-movements Reviewed by James Ives, M.Psych. (Editor)Mar 27 2019Subtle characteristics in the spontaneous movement of very young babies may reveal clinically important aspects of their neurodevelopment. Visual assessment of typical movement patterns (General movements, GM) by a clinical expert is known to be effective in early identification of e.g. cerebral palsy (CP).”A three month old infant shows frequently occurring stereotypical, dancing-like movements throughout the body and limbs. A noted absence of them is highly predictive of later emergence of CP,” says Sampsa Vanhatalo, professor of clinical neurophysiology, University of Helsinki.A very early identification and subsequent therapeutic intervention would be highly beneficial for alleviating the neurodevelopmental impact of CP. Currently, a child is diagnosed with CP at much later age, typically between 6 months and 2 years of age. GM analysis holds promise in early detection of CP, however, it needs special expertise that is currently obtained through international teaching courses, which effectively limits the number of doctors or therapists with the relevant skills. In addition, GM analysis in its present form is based on visual assessment, which is always subjective.”There is an urgent need for objective and automated methods. They would allow employing movement analyses at much wider scale, and make it accessible to basically most, if not all, children in the world,” says Vanhatalo.THE STICK MAN REVEALS THE ESSENTIALSResearchers at University of Helsinki and University of Pisa set out to explore the possibility that a conventional video recording of an infant lying in bed could be transformed to a quantified analysis of infant movements. They collaborated with people from an AI company based in Tampere, Neuro Event Labs, who were able to create a method for an accurate extraction of children’s movements (using a technique known as pose estimation), allowing for the construction of a simplified “stick man” (or skeleton) video.Next, the researchers gave the stick figure videos to doctors with GM expertise to see whether diagnostically crucial information was preserved in those videos.Using the stick figure videos alone, the doctors were able to assign diagnostic groups in 95% of cases, proving that the clinically essential information had been preserved.The study shows that an automated algorithm may extract clinically important movement patterns from normal video recordings. These stick figure extractions can be directly used for quantitative analyses.Related StoriesArtificial intelligence set to revolutionize the field of proteomicsAI coach feasible and useful for behavioral counseling of teens in weight-loss programMachine learning identifies bugs that spread Chagas diseaseTo demonstrate such potential, the researchers provided a proof of concept analysis where simple measures of stick figure movements showed clear differences between groups of infants with either normal or abnormal movements.Use of stick figure videos also enables world-wide sharing among research communities without privacy concerns. This has been a significant bottleneck in setting up multinational research activities within this domain.”This will finally enable a genuinely Big Data kind of development for better quantitative movement analyses in infants,” Vanhatalo states.”Since this study, we have collected larger datasets, including 3D video recordings, and we are currently developing an AI-based method for infantile motor maturity assessment. The rationale is straightforward: there is a developmental issue with the child, if the computational assessment of the motor maturity does not match with the child’s true age.”MOVEMENT ANALYSIS TELLS ABOUT NEURODEVELOPMENT AND EFFECTIVENESS OF THERAPEUTIC INTERVENTIONSIn addition to early CP detection, automated movement analyses have many potential applications in the assessment of infant neurological development.”We could create one kind of functional growth chart,” says Vanhatalo.Movement analyses could also be used in diverse ways to improve therapeutic decisions. Such methods could provide quantitative means to objectively measure efficacy of different therapeutic strategies; one of the global hot topics in restorative medicine.Automated movement analyses could also allow out-of-hospital screening of children to identify those that need further care, or to provide assurance of normality in cases with concern about child’s development.”Use of machine learning and artificial intelligence allows for the extraction of substantial amounts of clinically useful information from a simple home-grade video recording. The ultimate aim is to find methods that will make it possible to provide high and even quality infant healthcare everywhere in the world,” Vanhatalo summarizes.