Computer Scientists based at the University of Bath are experimenting with conductive seams to track all physical activity.

According to the scientists, these charged seams are powerful enough to detect even subtle movements that a smartwatch or a fitness app would miss.

Conductive seams in clothing yield data that can be analyzed to gain a better understanding of how the wearer moves.

“There are lots of potential applications for conductive yarn in any activity where you want to identify and improve the quality of a person’s movement,” explained Ph.D. student Olivia Ruston at Bath. “This could be very helpful in physiotherapy, rehabilitation, and sports performance.”

They are not the first team of scientists to create textile sensors for use in clothing, but it is the first project that focuses on using conductive seams.

This study has uncovered how the number of conductive seams and their placement on garments affects the yarn’s ability to record information.

“There’s great potential to exploit the wearing of clothing and tech – many people are experimenting with e-textiles,” Ruston said, “but we don’t have a coherent understanding between technologists and fashion designers, and we need to link these groups up so we can come up with the best ideas for embedding tech into clothing.”

Ruston’s team of scientists is working with a special kind of yarn. This yarn is built with a unique conductive core made from a hybrid material designed to sense pressure and stretch. This hybrid is made from a metal-polymer combination.

The yarn is woven into the seam of a garment and then activated, strictly at low voltages. The wearer’s body movements will bring about variations in the resistance of the yarn and tension within the seams.

The researchers used a microcontroller to relay the voltage signal from the seams and onto a computer.

Co-author Professor Mike Fraser explains that their work will influence the fashion industry: “Our work provides implications for sensing-driven clothing design.” Fraser is the head of computer science at the University of Bath. “As opportunities for novel clothing functionality emerge, we believe intelligent seam placement will play a key role in influencing design and manufacturing processes. Ultimately, this could influence what is considered fashionable.”

Weekly semaglutide injections have helped patients lose more than 15kgs. Might this be a magic bullet in the fight against obesity?

We need efficient ways to treat and prevent obesity, even as we fight COVID-19. 29% of women and 26% of men in the UK, according to NHS in data published in 2020 May, were presumed to be obese. These individuals had a body mass index higher than 30.

The situation has now gotten worse thanks to a widespread lockdown-related gain in weight. Obese patients are not only likely to die due to COVID-19; but even worse, University of Glasgow researchers’ recent estimates suggest that obesity might have overtaken smoking as a cause of ill health in Scotland and England.

A healthy balanced diet and suitable physical exercise could prevent weight gain. But this is not considered an effective treatment against obesity. Consuming a very low-calorie diet of not more than 1,000 kcal a day might result in losing about 10 to 15kgs within 12 weeks.

A more modest, cautious calorie restriction prescribed by several commercial slimming plans could cause an average annual weight loss of about 7kgs. However any weight lost through these methods can be regained. And you need another approach to keep the wright off.

To date, various drugs formulated to treat obesity are either inefficient in clinical practice or have harmful side effects like anal leakage or higher blood pressure. Bariatric surgery is the only reliable treatment for critical obesity at the moment, but long-term side effects and risks accompany it.

A series of peptide hormones regulate energy expenditure and appetite. These hormones are released in the intestine. Bariatric surgery works because it changes the gut response to food intake and how it communicates with the brain.

Specifically, glucagon-like peptide (GLP-1) is produced in the ileum in the last section of small intestines. GLP-1 responds to foods containing carbohydrates. Insulin synthesis is thereby promoted and secretion by the pancreas, but it affects the stomach by reducing the digestive system movements and secretion of acid.

The UK researchers published their findings on semaglutide in the New England Journal of Medicine led by John Wilding, in February. They found that a drug mimicking GLP-1 that was initially intended for diabetes treatment caused considerable weight loss in type 2 diabetes patients.

The researchers worked with 1,962 patients, of whom 75% were female. Of these, 13% were Asian, 6% black, and 75% white. Their average body mass index was 38. Patients were randomly divided into 2 equal groups. One group received semaglutide weekly injections, while the control group received placebo injections for 68 weeks. Both groups got lifestyle advice and diet.

The semaglutide group lost an average of 15.3kgs in contrast to 2.6 from the control group. The treatment effect difference in the two groups was 12.7kgs weight loss.

The treatment as successfully reduced blood pressure by 5.1mmHg, and the patients reported better physical functioning. The treatment’s major side effects included nausea, diarrhea, and occasional vomiting. And to those on active treatment, there were more frequent gastrointestinal disorders. Of more concern may be the accelerated danger of pancreatitis and gallbladder disease.

As these high-quality trials show, semaglutide causes remarkable weight loss compared to other drugs tested so far. What happens after the treatment ends is uncertain. Preventing the weight from piling back on is a great challenge, and the lesson learned from bariatric surgery is that patients should avoid sugar-sweetened beverages and unhealthy snacking. Smaller portions of calorie-dense foods help.

The research findings need to be confirmed with a more ethnically diverse population with a higher proportion of males. From a practical standpoint, the drug injection’s weekly requirement is more likely to curb a more significant rollout of the treatment. Oral preparations of the drug are still under trials.

While semaglutide appears promising as an obesity treatment, it is not exactly a magic bullet. We should continue to promote a healthy lifestyle as well as discourage unhealthy eating habits that lead to obesity.

Most cases of disability and early death have their root cause in a poor diet. This is a global phenomenon. This means that improving diet can prevent most premature deaths.

According to recent research, Covid-19 patients who have dietary problems experience poorer outcomes.

A balanced diet does more than just help keep diabetes, cancer, and heart disease at bay, it also helps you fight off Covid-19.

Diet therapy helps people to prevent disease, as well as manage and treat illnesses. This includes acute and chronic diseases.

MNT (Medical Nutrition Therapy)

Treatment with Nutrition and Diet

Medical Nutrition Therapy means treating injuries, illnesses, and health conditions with diet and nutrition. MNT is an effective treatment for a range of conditions; from depression to HIV and kidney disease.

Even though researchers have proved that MTN works to treat chronic illnesses, MNT services are not widely accessible. Many patients cannot access it; either because it is too expensive or simply not available for them.

One study that focused on nutrition support for diabetes type 2 patients under Medicare found that not more than 4% benefited from MNT in the first year of their diagnosis.

Applying Digital Health Technology in the Service of MNT

Digital Health Technology has the potential to make MNT accessible to more people than ever before. Besides expanding availability, Digital Health Technology can provide the service in a more precise and individualized way.

We can now use both active and passive data collection to track, monitor, and analyze personal health by, for example, monitoring heart rates with smartwatches or logging in a 5-mile walk using a mobile app.

At least a fifth of America uses either a health app or a smart device to monitor their health. Users can choose from more than 300,000 apps on the market for health tracking.

The latest technologies like big data and machine learning can analyze data in real-time and present an opportunity to transform nutrition management.

With individual data such as meal patterns and symptoms, medics can apply machine learning and big data analysis to come up with evidence-based Medical Nutrition Therapy recommendations fast.

This will enable us to gain a deeper understanding of how diet influences improved disease treatment, management, and prevention.

Using mobile phones to make the technology accessible to more patients will allow them to benefit from MNT and access continual medical support wherever they are.

These technologies are compatible with machine learning and big data. They can make Medical Nutrition Therapy better and more accessible than ever.

Mobile phones can help patients take charge of their care, to access 24/7 medical support no matter where they are.

A single digital health service can integrate all these tools and services to make MNT more accessible financially by allowing them to access the therapy without having to pay for an in-person consultation.

Over time, the technology can minimize the ravages of disease, save lives, and reduce health services expenditure to the tune of billions of dollars.

Individualized MNT Advice

By building a single platform that continuously analyzes data across different locations and demographics, we can understand the role of diet in causing disease and altering the impact of the disease on the human body.

Vulnerable population groups like older people and the chronically ill also stand to benefit from such a platform.

With greater resources dedicated to data analysis, it will be possible to identify risk factors for chronic illnesses a lot earlier and to prescribe dietary interventions early enough to prevent and sometimes even reverse diseases.

Because people’s nutritional needs and preferences evolve with time, people need a platform that can grow and adapt to their changing needs over time, too. AI and machine learning will enable the platform to gradually develop a better understanding of user’s nutritional needs.

This kind of platform will use algorithms to spot and track patterns that reflect individual traits in behavior, biology, as well as physiology. These insights will help the tools to decide on the best diet for individual users, designed for their conditions, genetics, and even lifestyle.

Machine learning, as well as analysis of big data, can help users to understand the diet needs of individuals and to make more precise dietary prescriptions.

The technology can make clinical care better by recognizing the way drugs, nutrition, and disease interact and coming up with more precise MNT prescriptions.

We are on the cusp of a new technological era of more personalized nutritional services than ever.