Tech Meets Mind: Wearable Technology in Mental Health Care

The use of wearable technology in managing mental health conditions is picking up steam much more quickly than I previously thought. In 2022, I wrote a thought piece on what mental health care may look like in 2032. Here was one of my predictions:

I envision wearable technology will be able to analyze data to predict mental stress. I use the word “mental stress” to encompass symptoms of mental illness such as excessive fatigue, anxiety, depressed mood, or decreased interest in activities.

Since people (and medical journals) are chatting more about wearable tech in the mental health space, I thought I’d add my own commentary.

In this article, I’ll highlight the fundamentals of wearable tech, discuss the current mental health wearable tech market, and dive into the promises and challenges ahead.

The Deets

Wearable technology allows continuous monitoring of three general domains:

  • Fitness Activity: GPS capability, pace/speed, stride length, power, run/bike cadence, steps, elevation gain.

  • Physiology: resting heart rate (RHR), heart rate variability (HRV), blood pressure, oxygen saturation, respiratory rate, one-lead EKG, sleep, blood sugar level.

  • Behavior: fall identification, time spent sedentary, gait monitoring, close-contact detection (think Covid-19).

Wearables focusing on these three domains can provide ample insight into users’ mental health, complimenting data obtained during a clinical office visit. For example, the current standard for assessing mental health conditions is a one-on-one interview with a provider (psychiatrist, psychologist, PCP, social worker) and a standardized assessment tool like a PHQ-9. However, these traditional assessments only capture a moment in time vs objective trends over time.

Let’s take a look at depression to see how wearables can capture important trends over time:

  • Depression affects a person’s sleep, energy level, activity level, and appetite. Wearable technology can, directly and indirectly, measure these symptoms or “data points.” Sleep, activity level, and autonomic stress (e.g., HRV) are all directly measured by a wearable. The wearable would note any significant changes from the baseline. Energy level and appetite could be extrapolated from other wearable data. For example, energy level can be extrapolated from fitness activities, heart rate throughout the day, and time spent sedentary. This would assume someone with low energy wouldn’t be moving much throughout the day and would, therefore, have a low daily average heart rate and increased sedentary time. Appetite, too, could be extrapolated through a wearable that measures weight and nutrition intake.

You can imagine if one wears their wearable over an extended period (e.g. months) with quality data, a provider could analyze trends to determine worsening/improvement of depression symptoms.

Mental Health Wearable Tech Space

Wearable tech for monitoring mental health conditions is relatively nascent, but several prominent companies are advancing the field. Notably, many of these companies have been in the consumer wearable game for a while but have slowly added mental health features.

  • Fitbit: Sense 2, Charge 6, and Inspire 3 come with mood logging and stress management scores using data like HRV and skin temperature. The former two also have an EDA scan, which tracks changes in heart rate and electrodermal responses during mindfulness sessions.

  • Feel Therapeutics: Their proprietary algorithms compute various markers and metrics for mental health, such as mood, stress, sleep, and cognitive functioning. They use continuous 24/7 data collection from wearables, digital health apps, and mobile phones, integrating physiological, digital, and clinical data. This data is then used in personalized digital therapeutic and wellness programs to manage mental health conditions.

  • Apollo Neuro: this wearable device is designed to improve stress management by focusing on sleep. It delivers vibrations to the skin to balance the body, aiming to retrain the nervous system for better stress handling and improve sleep, focus, and balance.

  • Apple Watch: Apple launched new mental health features in iOS 17 and watchOS 10 to focus on emotional awareness and resilience. The Health app allows users to reflect on their mental state, identify feelings, and gain insights into factors affecting their mood, like sleep or exercise. It includes mood assessments, similar to those used in clinics, to evaluate anxiety or depression risks and connect users to resources.

  • Lief Therapeutics: they offer a wearable device for mental health that focuses on improving HRV. The device provides real-time biofeedback through vibrations, helping users become aware of stress triggers and self-regulate. It includes personalized coaching and mindfulness tips.

  • Muse: an EEG-powered meditation and sleep headband designed for mental health support. It uses advanced sensors to measure brain activity, heart rate, breath, and body movement. The device offers real-time audio feedback during meditation sessions, helping users focus and manage stress. Muse also features a sleep function, using responsive bedtime stories and smart-fade technology for improved sleep quality.

  • WHOOP (my favorite): WHOOP offers top-of-the-line analytics on sleep and bodily stress. The key feature is the daily journal, which includes questions about mental health. WHOOP’s algorithm then produces monthly reports on how certain factors in life (e.g., ‘feeling stressed/anxious’) impact health. A recent WHOOP study of U.S. Army soldiers found that consistent sleep patterns are crucial for psychological well-being, with irregular sleep-wake times predicting mental health decline. I used WHOOP as an example in my previous article on mental health.

  • Garmin: this company, to whom I’ve been loyal since I was 14 years old, is becoming more involved with mental health by supporting mental health research projects (see example here) using its wearables.

Many of the above companies that started out simply as “fitness trackers” are now making headway into the mental health space. Overall, the impact potential is significant: a recent Deloitte consumer survey found that 41% of respondents own a smartwatch or fitness tracker. Ninety percent of these folks use wearables to track fitness and monitor health metrics, and 30% report these wearables have significantly improved their fitness and health. Most interesting is that 55% of wearable tech users in the survey reported sharing their data with medical providers. A patient has yet to share their data with me, though!

Dashevsky’s Dissection

Wearable tech can increase the amount of clinically meaningful data physicians and other providers use to guide management decisions, especially in the realm of mental health. I’m sure many physicians have already experienced using wearable data to further management of patient’s conditions. I have yet to experience it on the physician side, but I’ve personally shown my physician my WHOOP data. However, I’ve had several patient encounters where my first thought after hearing the patient’s presentation was I wish this patient had more data to show me.

Recently, a new patient presented to me complaining of fatigue, weight loss, decreased interest in activities, and insomnia. I was concerned about depression. I asked, “How much weight loss?” “I don’t know,” said the patient. “How much sleep are you now getting?” “I don’t know, I just can’t sleep.” “How often are you moving about?” “I don’t know, just not as much.” Such subjectivity and vagueness! If only I could see objective wearable data showing trends in weight loss, sleep, and activity, I could create a more robust differential for this patient’s presentation.

With the advent of large language models, getting already-analyzed wearable data to physicians may become more streamlined. Per my above patient example, an LLM could interpret the patient’s data trends and send a message to the physician stating:

Over the past three months, the patient’s average sleep duration has decreased by one hour. The patient has spent more time awake throughout the night, reducing the length of her REM and NREM sleep. Heart rate variability has subsequently decreased and resting heart rate has increased. Additionally, the patient has lost around 10 pounds, which doesn’t correlate with an increased activity level. In fact, the patient has been less active as seen by a significant decrease in steps per day and a decrease in her average daily heart rate.

I don’t think it is wishful thinking to want an LLM sending physicians interpreted data like the above. Without a doubt, it would improve clinical decision-making when working up a patient.

While it excites me to think of a future (not too far away!) where nearly all patients have wearable data and an LLM interpreting it, there are several challenges. The first obstacle, which is the obstacle for almost any type of software in healthcare/medicine is data integration. That is, wearable data does not seamlessly integrate into EHRs. I cannot simply log onto Epic and see my patient’s sleep patterns since the last time I saw them. If the data doesn’t integrate into the one platform that physicians and providers spend most of their time on, it likely won’t be seen or used.

The second challenge is ensuring the data is legit, and the wearable is measuring what it should be measuring. I won’t belabor the point, so you can read my article on digital health solutions proving their validity here.

Lastly, there’s no robust reimbursement system in place for wearable technology, which will likely limit widespread adoption. Wearable tech is largely consumer-driven: I have a WHOOP on my right wrist and a Garmin on my left wrist, two wearables I bought. My physician didn’t prescribe them. I believe there will come a time when physicians will get reimbursed for prescribing wearable technology since doing so would meaningfully improve medical management of conditions.

In summary, wearable technology in mental health is rapidly advancing, offering new opportunities for monitoring and managing mental health conditions. My exploration into this field reveals how wearable devices, ranging from wristbands to clothing, can track fitness, physiological, and behavioral data, providing insights into a patient's mental health. These technologies complement traditional mental health assessments by capturing objective, long-term trends. However, challenges such as integrating EHRs, ensuring data accuracy and establishing a reimbursement system still need to be addressed. Looking ahead, the potential integration of large language models could streamline the process of making wearable data clinically useful, marking a significant step forward in the intersection of technology and mental health care.

Which aspect of wearable technology in mental health excites you the most?

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