In Ten Years, Brain Wearables May Be as Ubiquitous as FitBits

Technology Policy Reimagining Health

In Ten Years, Brain Wearables May Be as Ubiquitous as FitBits

Commentary
Posted on: 3rd May 2022
By Multiple Authors
Lauren Packard
Senior Policy Analyst, Science and Innovation Unit
Ariel Ganz
Precision Medicine and Mental Health Researcher, Stanford University School of Medicine

The brain is the most important organ in the body, but we barely understand it.

The brain is arguably the most important organ in the body. It helps control breathing, vision, thought, memory, and emotions, among many other functions. The brain is also the locus of psychological and neurological issues that impact hundreds of millions of people around the world each year, including depression, anxiety, stress, epilepsy, and Alzheimer’s.

 Although the brain is a core aspect of human existence and thriving, we still don't really understand how it works to influence health and disease. And moreover, we don’t measure it. 

Emerging technological advances allow us to measure brain activity at scales and contexts previously thought to be impossible. Until quite recently, patients had to come into a lab to conduct brain measurements, but the advent of accessible non-invasive brain activity imaging devices means that researchers can learn more about how a brain acts outside the lab. Clinicians can monitor patient progress outside the clinic and enterprising consumers can better understand their own unique physiology. Each brain is totally different—a novel personal neural structure developed over a lifetime of unique experiences. Interventions (such as a pharmaceutical) that work for one person might not work for another—and we don’t fully understand why. Data generated in this way can help tailor therapies to individual patients, and better understand the dynamics

The expense and size of neuroimaging devices are decreasing exponentially.

A number of non-invasive modalities are able to  measure the brain in all its complexity: magnetic resonance imaging technology (MRI) creates an image of the brain using magnetic imaging; functional magnetic resonance imaging technology (fMRI) measures changes in oxygenation across the brain. Functional near-infrared spectroscopy scans (fNIRS) measure oxygenation of a portion of the brain and electroencephalography (EEG) measures electrical activity, or brainwaves.

Historically, these diagnostics have been expensive and unwieldy. An fMRI machine used in neuroscience research can cost anywhere from $500,000 to $3 million and is the size of a small room. A hospital-grade fNIRS machine can cost from $100,000 to $400,000, while an EEG machine can cost up to $100,000. However, technological advances are driving down costs and emerging brain wearables are making noninvasive brain-imaging more accessible than ever before.

About 15 years ago, advances in processor and sensor manufacturing drastically reduced the costs of EEGs. Decreases in the cost of low-noise, high-impedance amplifiers and active electrodes, alongside the introduction of machine learning algorithms, meant EEGs could be brought to market at lower price points. Today, there are a number of consumer EEG products on the market that cost about half as much as an iPhone 13, such as headsets from Muse, Flowtime, and URGOnight and headphones from Eno.

Advances in other types of imaging are nascent, albeit not far behind. Kernel is developing a helmet that uses time-domain (TD)-fNIRS to image the brain. They aim to release a commercial model which will cost the same as a smartphone in 2024.

Accessible neural imaging could further research and clinical care.

When Fitbits and AppleWatches first emerged, there was pushback around their limited accuracy compared to hospital-grade devices. However, the value of imperfect yet continuous measurements is becoming increasingly clear. For example, Mike Snyder at Stanford and others have shown that wearable devices can detect COVID-19 days before patients experience symptoms

When a person is measured once in a clinical setting, we get a great idea of the exact measurement at that point in time. However, that moment may not be representative of the patient’s baseline state, and what is typical for one person may be problematic for another. More importantly, people’s physiological and biological data change dynamically over time. The dynamic pattern of these changes, which were previously thought of as “noise,” are increasingly being recognized as powerful tools for predictive analytics and even diagnostics. Medicine is moving from focusing on averages to personalized care, and from static measurements to dynamic measurements.

The dynamic and continuous datasets offered by wearable fNIRS and EEGs can help ascertain the effectiveness of tried-and-true mental health interventions as well as identify novel alternatives. Wearable devices can create baseline measurements of the brain and then show whether and how an individual responds to treatment. Dr. Leanne Williams at Stanford has been leveraging personalized fMRI patterns to better diagnose and treat depression. Similarly, Kernel’s brain-imaging helmet has recently achieved approval from the U.S. Food and Drug Administration to measure the impacts on the brain when the wearer takes a therapeutic psychedelic dose of ketamine

In the EEG space, Startup Alto Neuroscience is using EEG data to develop precision mental health care--doctors could soon match patients to the therapies best suited to them, circumventing the frustrating cycle of trial-and-error typical of mental health treatment. It’s launching Phase IIa trials for treatment-resistant depression and PTSD soon and expects to have its first data by 2023. These trials will take place entirely in participants’ homes, thanks to portable EEG caps. Wearables will also help determine whether brain stimulation techniques such as electric, magnetic, or ultrasound stimulation to treat mental health conditions and increase wellbeing are having an impact on a biological level.

Neurofeedback from EEG sensors (like the Muse headset mentioned above) can help people determine whether meditation practitioners are in fact reaching desired Beta or Theta waves. In this instance, the EEG is the measurement and the intervention—real time audio and/or visual stimuli inform the wearer of her brain activity and help her recognize the feeling of optimal brain states so she can “train” her brain to reach there faster and stay there longer.

A new frontier in mental health?

We’re on the cusp of a surge of emerging brain-based healing technologies—from concentration-enhancing video games to psychiatric use of psychedelics to transcranial ultrasound stimulation. Brain wearables can help us make sure we’re leveraging these mental health and healing innovations to their full potential.

At the Tony Blair Institute and Stanford Health Innovation Lab, we think monitoring the brain isinstrumental to ushering in a new era of personalised mental healthcare. Keep an eye out for our upcoming policy recommendations. 

Lead Image: Getty 

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