Smarter Wearables Healthier Life

The first wearable devices gave us "just the facts" and little else. Today, wearables and mobile devices are getting smarter. They gather data across multiple variables, integrate that data with information from other devices and leverage AI to provide new levels of analysis for a variety of conditions.

Our Smiles: Dental Care 

Tooth decay is the most common health condition in the world, according to research cited by the World Health Organization. Yet many people don’t have access to dental care or find going to the dentist too time-consuming. In the U.S., the number one reason people don’t visit the dentist is lack of money. In low income countries, there simply aren’t enough dentists – approximately one dentist for every 152,000 people.

The majority of oral health problems are preventable. A new class of apps and tools leverages your smartphone’s camera and machine learning to help identify cavities, tooth decay and receding gums, bringing dental care closer to people that may not have access to it.

“Using smartphones can provide us with world resources no matter where we are. So if I’m in a remote area and I get a toothache, I can send an image and find out what kind of treatment I may need. But also, to help you track your progress and track it over time, to watch any condition that might be worsening.”

Karen Panetta, IEEE Fellow, IEEE Robotics and Automation Society, IEEE Education Society, IEEE Computer Society, IEEE Oceanic Engineering Society, IEEE Product Safety Engineering Society, IEEE Signal Processing Society, IEEE Systems, Man and Cybernetics Society

Our Brains: Mental Well-Being 

Currently, most major mental health conditions have no cure, but they may be managed. Wearables and smartphones contain a number of sensors that can help examine and monitor symptoms. Location and GPS functions, for example, can be used to measure variables such as how far a person has traveled in a day, how far away from home they are or whether they’ve visited unpredictable locations. In some cases, travel to unpredictable locations may correlate to symptoms of schizophrenia, while a sedentary lifestyle may be associated with depression. Voice data can also be an indicator for mental distress. Heart rate variability, eye movement and electrodermal activity — changes in the skin caused by sweating — can also reveal a person’s mental state.

Data provided by the World Economic Forum

“Stressful periods vary throughout the day, and depending on the environment, the patient can experience sharp but acute stress periods. Data like this can be recorded by wearables and smart devices, which can then provide insights for the therapist.”

Ramalatha Marimuthu, IEEE Senior Member, IEEE Computer Society, IEEE Education Society, IEEE Society on Social Implications of Technology

Skin Deep: Cancer Detection 

Doctors and healthcare professionals have been exploring artificial intelligence techniques for cancer detection for at least 15 years. Machine learning and deep learning algorithms have successfully been used to screen for several types of cancer. The next step: skin cancer screening on your smartphone.

When detected early , the 5-year survival rate for melanoma is 99% Data provided by the

“A picture or a signal from the skin is well understood by AI and machine learning algorithms to comprehend whether there is cancer or not. People have applied VGGNet and ResNet and different types of deep learning algorithms and they have core accuracies in the order of 90 percent. This is a good precision to further deploy these types of technologies for commercialization. The hardware and the AI model, both are in development phase for this type of skin cancer detection.”

Sambit Bakshi, IEEE Senior Member

Life Pump: Heart Health 

Fitness trackers were among the earliest wearable devices. It’s no surprise that they have advanced. Fitness trackers now analyze multiple data points for a more complete picture of heart health, and in some cases can be used for disease detection.

“Heart rate data alone is kind-of useful, but it really becomes valuable when it’s aggregated with other data points, as well as when you can see trends. But then when you couple it with things like your sleep data … so maybe you’re not getting enough sleep, so that’s why your resting heart rate is going up … that’s interesting. And now, we have so many other data points such as 02, such as respiratory rate, your temperature – that you can do really sophisticated things.”

Carmen Fontana, IEEE Member, IEEE Computer Society

Our Metabolism: Diabetes 

Traditionally, diabetes patients have had to prick their fingers several times each day to measure glucose levels in blood. But diabetes management has been revolutionized by the use of graphene-based patches that measure glucose levels in sweat, and other wearables that are less intrusive. Some researchers have begun looking into the use of graphene tattoos to help. The innovations are meant to address a key challenge in diabetes wearables: making sure devices match the lifestyles of their users.

Data provided by the

“Eventually, such patients need to have a normal life. So the challenge is to design biocompatible materials that could be embedded in a non-invasive way on the human body, avoiding allergies and other kinds of complications. And at the same time keeping a good lifecycle. So these days we have observed some devices – stickers, tattoos and gadgets that can last embedded in the human body for weeks. And finally, they need to keep the measurement precision.”

Marcelo Zuffo, IEEE Member, IEEE Computer Society, IEEE Consumer Electronics Society, IEEE Broadcast Technology Society, IEEE Society on Social Implications of Technology

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