AI Show Promise For Assistive Technologies

Artificial intelligence scanning a person’s thoughts and translating them into text might seem like the stuff of dystopian fiction, but the results of one study at the University of Texas are showing promise for different types of assistive technology.

About the Study

In the study, which was published in Nature Neuroscience, researchers at the University of Texas in Austin were able to record and decode study participants’ brain activity with a non-invasive decoder. The researchers then used an artificial intelligence algorithm similar to the one that underlies Chat GPT to translate that activity into text. 

The Need for Humans Will Remain

Artificial intelligence is already revolutionizing health care, and changes are happening fast. Understandably, the disruption is causing questions and even concern. But the truth is, although the way medicine is practiced will necessarily change, the need for human practitioners isn’t going anywhere. 

What is the IoMT?

The Internet of Things continues to transform various industries. The medical field, in particular, is in the midst of a revolution in how patients receive their care and how medical providers offer their services. The rollout of Internet of Medical Things devices, including in hospitals and as convenient, wearable products, provides data resolution never before possible, and these changes are serving as powerful tools, particularly as telehealth continues to expand. Here are some of the reasons why the IoMT is poised to change how patients receive medical care and manage their medical needs.

Why Go Virtual?

Immersive technologies provide novel, cost effective solutions in healthcare, and applications are only expected to grow. Forbes Magazine reports that healthcare applications involving AR, VR, and MR are on track to reach nearly $10 billion dollars by 2027.

That’s a growth of 3.5 times over the current value of $2.7 billion. Given the many advantages, and the few predictable disadvantages, it wouldn’t be surprising to see even more explosive growth in the future.
 

Used in Medical Devices

Generative artificial intelligence (AI) refers to a subset of machine learning techniques that involve training models to generate new data that is similar to existing data. In the context of medical devices, generative AI models can be used to generate new images or designs for medical devices, simulate the performance of medical devices under different conditions, or generate new medical imaging scans with added or removed features.

Why Is It Taking Off?

Computer hardware has made incredible advances over the decades. However, by itself, hardware is inert; software is needed to make use of these powerful devices. Early computers required wiring components together to program, but the field quickly moved toward machine language and text-based approaches, which are still the dominant paradigms today. Over the years, efforts have been made to offer an alternative to writing traditional code. Today, no-code platforms are gaining a significant amount of interest. Here are some of the ways the no-code paradigm is affecting how people create with computers.

For Medical Devices

Assurance cases can reduce the time to market for products requiring regulatory oversight, for example, medical devices, while building a strong case for a product’s safety and effectiveness.

Assurance cases are a method for communicating the safety, effectiveness, and performance of a product by demonstrating how the submitted evidence supports the manufacturer’s claim.

Advantages Over Stand Alone Medical Devices

Mobile health technology is a booming field both at the consumer and professional levels. There are currently more than 100,000 personal health tracking apps available for smartphone users. These apps range from simple step trackers to diet analysis apps, sports performance tracking, and more. Professional uses for the smartphone are growing just as fast, from telemedicine to remote patient monitoring, to even replacing certain standalone medical devices.

Replacing? Yes. The smartphone has numerous advantages over standalone medical devices. Some are obvious. Others, however, are only starting to come into their own.

The Power Of Digital Twins and Digital Threads

“Digital Twins” and “Digital Threads” are recent terms, but the concepts they represent should be familiar. A digital twin is a virtual representation of a physical product, much like a simulation or digital mockup (DMU). A digital thread, on the other hand, is a product lifecycle management tool.

The difference is that digital twins and digital threads address the additional needs created by interconnected devices and applications.

Changing How Medicine Is Practiced

Technology has influenced medicine in a major way. New types of artificial intelligence aid in diagnosing and treating conditions, and the rise of telehealth makes medical care more accessible and convenient. One less appreciated field, however, is having a major impact on how medicine is practiced today: Robotics. Here are some of the ways medical robots are improving how medicine is practiced today and how this field is expected to evolve over time.

Role of AI

Perhaps the biggest revolution in computing in recent years has been the move to the cloud. No longer are individuals and organizations tied to their specific hardware: With cloud computing, it’s easy to scale up or down with just a few clicks and, typically, at a low cost. However, many are unaware of just how intertwined artificial intelligence is with the cloud’s rise and its use both today and in the future. Here are some of the ways artificial intelligence makes the cloud an intelligent cloud.

For Consumers: IoT Devices and Software

In May of 2021, President Joe Biden signed the Presidential Executive Order on Improving the Nation’s Cybersecurity (14028) as part of a greater effort to enhance software supply chain security. As part of the order, the National Institute of Science and Technology was tasked with issuing guidance for labeling consumer internet of things devices and software.

A Top Priority

Technological developments in recent decades have been a driving force in improvements in medicine. Today’s medical devices give doctors and others in the field far greater ability to see details that would previously have been missed, and the dropping cost of medical technology makes these devices more accessible. However, these advantages come with some downsides. In particular, poor security can put patient data at risk, and certain types of malware can render devices inaccurate or even unusable. Cybersecurity now must be a top priority for practices of all sizes.

Will it Impact How Medicine is Practiced?

The medical field is notoriously reluctant to adopt new technologies, as the high stakes of changing how medicine is practiced means new technologies have to be thoroughly vetted before being implemented. However, the promise of blockchain technologies means a growing number of medical entities are taking a close look at using it as a foundational technology across a range of areas, and this momentum is only expected to accelerate in the coming years. Here are some of the reasons why blockchain technology is poised to have a major impact on how medicine is practiced worldwide.

Revolutionizing IoT

The term “LTE” is certainly familiar to anyone following mobile connectivity over the years. For those operating in the embedded space, however, a technology called LTE-M is revolutionizing how Internet of Things and other connected devices can operate across a wide range of industries. Here are a few facts about this burgeoning technology and its present and future impact on the embedded environment.

Accelerating AI

Despite how complex modern computers seem, their basic architecture hasn’t changed much since they started implementing what’s known as Von Neumann architecture. The real “brains” of computers lie in the CPU and the RAM, the latter of which stores program code and data. While modern RAM is amply fast for a wide range of tasks, the connection between the RAM and CPU can function as a bottleneck for certain tasks; in particular, many artificial intelligence implementations are restrained by how quickly the processor can access data stored in RAM. Recent developments, however, aim to mitigate this limitation, potentially leading to far more capable AI implementations and allowing developers to craft new means of harnessing the potential of AI.

How They Interact

Artificial intelligence, and machine learning in particular, is transforming various fields in a profound manner. Although the medical field has a reputation for being slow to adopt various technologies, AI and ML are currently changing how medical devices are being designed, potentially leading to better outcomes for patients. The FDA is taking an active role, helping to provide guidance for medical device designers and manufacturers. However, the fundamental nature of AI and ML presents challenges for regulation, and the FDA is in the process of developing regulations that both allow potentially useful devices to come to market while ensuring patients and doctors can expect devices to be safe and beneficial.

Is It Finally Coming?

Medical devices must meet strict scrutiny. In order to be sold in nearly any market, a device needs to be rigorously shown to be effective and safe. However, medical device designers and manufacturers have long had to deal with competing regulations, most notably the FDA Quality System Regulation, which sets the rules for devices sold in the United States, and the ISO 13485, an international standard used in the European Union, Japan, Canada, and other nations. In order to ease the process of bringing products to the market, the FDA has a goal of harmonizing its requirements with those of ISO 13485, but various factors have delayed this transition and even raised questions over how and whether it can be implemented in a timely manner.

US Task Force Plans to Share Government Data with Academia and Private Sector

On June 10th, 2021, the White House administration launched an effort to provide additional government data to artificial intelligence researchers. The move, which aims to ensure the United States remains at the forefront of AI research, will provide invaluable data to academia and the private sector for developing new tools.

In addition to offering access to data, the initiative may also provide access to government-run computing power, which can be especially useful for cutting-edge academic research.

The initiative seeks to provide a broad range of data, including information about health, driving habits, and demographics.

The Matter Standard

Although Google, Apple, and Amazon are often fierce competitors, there are areas where collaboration between these tech giants can prove beneficial for all. When it comes to the use of Internet of Things devices in residential and commercial environments, adoption has been slow. An initiative formerly known as Project CHIP was recently renamed Matter, and its wide support is poised to provide benefits to tech giants and startups alike.