How Joseph Pilates went from circus performer to exercise expert. Pilates is one of the fastest growing exercises in America, but it all started in an unlikely place. Breakthroughs, discoveries, and DIY tips sent every weekday. Pilates is having a moment. According to a recent report from the Sports and Fitness Industry Association, Pilates participation has shot up from 9.2 million participants to 12.9 million since 2019, a jump of nearly 40% and the largest of any workout type across the United States.

There are nearly seven million people currently diagnosed with Alzheimer's in the US, and while there is no cure, experts are searching for ways to prevent it. That is because stories about far off lands and mythical creatures require readers to remember what happened early on in the book to understand the ending. 'Fiction may elicit more intense emotions and imagery in addition to new facts and ideas from reading non-fiction books,' said Dr. Zaldy Tan, a professor of neurology and medicine at Cedars-Sinai Medical Center. 'But more than the type of book, the key here is sustainability, Tan said, adding: 'I recommend people challenge their minds by reading something new to them.' Alzheimer's disease is the sixth leading cause of death in the US with 6.9 million people living with the disease which is expected to double by 2050 Neuroscientists have suggested that remaining physically active and engaging in other activities like knitting, playing chess and puzzles and gardening could also prevent cognitive decline. 'Leisure activities including reading have been associated with lower risk of developing dementia in older adults,' Tan told DailyMail.com.

Competition is ubiquitous in the natural world [1, 2] and in human society [3, 4, 5]. Despite its universality, competitive interaction has rarely been investigated in the field of Human Robot Interaction, which has mainly focused on cooperative interactions such as collaborative manipulation, mobility assistance, feeding, and so on [6, 7, 8, 9, 10]. In some ways it is not surprising that competitive interaction has been overlooked: of course everyone wants a robot that can assist them; who would want a robot that thwarts their intentions? Yet, we also accept that human-human competition can be healthy and productive, for example in structured contexts such as sports. In this paper we explore the idea that human-robot competition can provide similar benefits. We believe that physical exercise settings such as athletic practice, fitness training, and physical therapy are scenarios in which competitive HRI can benefit users.

In order to detect and correct physical exercises, a Grow-When-Required Network (GWR) with recurrent connections, episodic memory and a novel subnode mechanism is developed in order to learn spatiotemporal relationships of body movements and poses. Once an exercise is performed, the information of pose and movement per frame is stored in the GWR. For every frame, the current pose and motion pair is compared against a predicted output of the GWR, allowing for feedback not only on the pose but also on the velocity of the motion. In a practical scenario, a physical exercise is performed by an expert like a physiotherapist and then used as a reference for a humanoid robot like Pepper to give feedback on a patient's execution of the same exercise. This approach, however, comes with two challenges. First, the distance from the humanoid robot and the position of the user in the camera's view of the humanoid robot have to be considered by the GWR as well, requiring a robustness against the user's positioning in the field of view of the humanoid robot. Second, since both the pose and motion are dependent on the body measurements of the original performer, the expert's exercise cannot be easily used as a reference. This paper tackles the first challenge by designing an architecture that allows for tolerances in translation and rotations regarding the center of the field of view. For the second challenge, we allow the GWR to grow online on incremental data. For evaluation, we created a novel exercise dataset with virtual avatars called the Virtual-Squat dataset. Overall, we claim that our novel architecture based on the GWR can use a learned exercise reference for different body variations through continual online learning, while preventing catastrophic forgetting, enabling for an engaging long-term human-robot interaction with a humanoid robot.

Esports players might be viewed as individuals who sit around, eat junk food and guzzle down sugary drinks, but a new study finds these gamers are just the opposite. A team from Queensland University of Technology uncovered uncovered players are up to 21 percent more likely to have a healthier body weight than the average person. The survey also reveals that esport gamers smoke and drink less than the general public and are significantly more active as a result of certain video games. Although a majority are in tip top shape, the study did find that 4.03 percent of esports players are more likely to be morbidly obese than the general public. A team from Queensland University of Technology uncovered uncovered players are up to 21 percent more likely to have a healthier body weight than the average person.

Kaia Health, a digital therapeutics startup which uses computer vision technology for real-time posture tracking via the smartphone camera to deliver human-hands-free physiotherapy, has closed a $26 million Series B funding round. The funding was led by Optum Ventures, Idinvest and capital300 with participation from existing investors Balderton Capital and Heartcore Capital, in addition to Symphony Ventures -- the latter in an "investment partnership" with world famous golfer, Rory McIlroy, who knows a thing or two about chronic pain. Back in January 2019, when Kaia announced a $10M Series A, its business ratio was split 80:20 Europe to US. Now, says co-founder and CEO Konstantin Mehl -- speaking to TechCrunch by Zoom chat from New York where he's recently relocated -- it's flipped the other way. Part of the new funding will thus go on building out its commercial team in the US -- now its main market.

Kaia Health, a self-styled digital therapeutics" startup, has pulled in $10 million in Series A funding for an app-based approach to chronic pain management. The idea is to offer an alternative to painkillers, using mobile technology to deliver what the founder describes as multimodal, "mind body therapy" for musculoskeletal (MSK) disorders -- comprised of guided physical exercises, psychological techniques and on tap medical education. "Once you fall into this category of you're a chronic pain patient, and not just you have acute pain for two or three days, then this is the best therapy to do," says co-founder and CEO Konstantin Mehl. "But at the moment because this therapy is so expensive only 2% of the patients who should get access to it actually get access to it and the other 98% of patients are treated with treatments against acute pain, like painkillers and surgery… This is why there's this crazy cost explosion when you look at the costs in the healthcare systems." The 2015-founded startup has developed a personal trainer app that uses computer vision technology so it can act as a fully autonomous exercise coach. The app works by visually monitoring the user as they perform exercises (via their smartphone's camera), enabling it to keep track of repetitions and also provide vocal feedback -- to correct posture and motion. The idea is to offer a more accessible and less expensive alternative to the one-on-one in person physiotherapy which a person suffering chronic pain from a MSK disorder might otherwise use to manage their pain -- such as by visiting a dedicated pain center for weeks of guided treatment. However as Mehl notes that can be prohibitively expensive and also entail long wait times to get seen. Kaia's first focus has been on back pain which Mehl knows plenty about -- having suffered himself for two years. His struggles to find effective and affordable pain management were the inspiration for setting up the company, he tells us. The goal he's shooting for with Kaia is to democratize access to proven multimodal therapies and reduce reliance on pharmaceuticals -- pointing to rising use of opioid-based painkillers, including in the U.S., where reliance on the drug has been driven by over-prescription leading to an epidemic of addiction and rising numbers of overdose deaths. "Most treatments against chronic back pain are just crazy expensive and crazy ineffective.

Schools are on the front lines in coping with attention deficit hyperactivity disorder (ADHD). More school-age kids are getting diagnosed with it each year (more than one in 10, according to the most recent National Survey of Children's Health) and the classroom is where kids often have their biggest problems with impulse control and an inability to sit still and focus. Some kids take medicine to control these symptoms, but many do not. And so principals and teachers are tremendously interested in non-medical therapies they can use at school to help children. Fortunately, it's an exciting time in ADHD research, thanks to developments in neuroscience, and psychologists hope they will find new tools for schools.

Applications of robotic and wearable sensors based systems for human assistance or health monitoring have been gaining popularity in recent years. Among its diverse applications, therapeutic robotic systems have been utilized in the muscular physiotherapies for movement training, wrist and arm treatment for injuries and overexertions, and other therapies. Applications of wearable sensors for human assistance or health monitoring have been also gaining popularity in recent years. Wireless wearable sensor systems enable proactive personal health management and the ubiquitous monitoring of vital signs to keep an active watch on immediate health conditions. In this paper, we develop a system that consists of multiple wearable sensors, software agents and robots, where a robot has the intelligence to process its own observed data, the collected wearable sensor data, and to aggregate the information into a single compiled report. Our system is also able to detect severe abnormalities with the well-being of the monitored individual as detected by the sensors and to create immediate alerts. Our preliminary experimental results show that our system is accurate in detecting and monitoring basic human conditions. We posit that the approach of non-invasive monitoring, when combined with an alert system, will make this a desirable personalized well-being monitoring system in future health care.