How Wearables Are Being Used to Monitor and Treat Stress

With a range of fitness devices capable of being diagnostic tools ([see the July 15, 2016 LRWEJ] client registration required), many developers are now turning to wearables to monitor and alleviate stress. This includes wearables that contain one or more of the following sensors: optical/ECG heart rate sensors, EEG sensors, temperature sensors, and impedance/galvanic skin response sensors.

  • Optical/ECG heart rate sensors. Heart rate sensors often monitor and track a user’s heart rate variability (HRV), which is a variation in time intervals between heartbeats. Deviations from the norm/user’s baseline HRV is an indicator of stress. If a user shows deviation from his or her baseline HRV, a developer could use an app to guide the user towards mediation to return to the baseline. Companies working in this space include Biobeats, which monitors HRV and uses a personalized music profile to treat stress.
  • EEG sensors. EEG sensors are used to monitor neurological signals and map brain activity. Often, EEG sensors are incorporated in a headset that is able to measure a user’s emotional state, including stress. If an EEG headset detects that a user is under stress, it can either use hardware, such as transcranial stimulation (tCS), to induce calming effects, or it can use software to help the user meditate. Companies working in this space include Interaxon and Emotiv, which combine measurements from EEG headsets with meditation and brain exercise to promote wellness.
  • Temperature sensors. Temperature sensors are often used to monitor signs of heat stress, but can also be used to monitor anxiety and emotional stress. A rapid increase or decrease in core or skin temperature may indicate that a user is undergoing stress, and developers could either use hardware that directly regulates a user’s body temperature or a software solution to intervene. Companies working in this space include Dhama Innovations and Equivital, which use wearables to cool down the user and monitor skin temperature respectively.
  • Impedance/GSR sensors. Galvanic skin response (GSR) sensors measure the electrical conductance of a user’s skin. An increase in skin conductance can indicate signs of a user’s stress. If an increase is detected, developers could use an app to guide the user towards meditation to return to baseline. Companies in this space include Empatica and Healbe, which are using GSR measurements to predict stress-based events.
  • Hydration/biomarker sensors. Hydration and sensors are used to analyze biomarkers found in a user’s sweat/bodily fluids, one of which may include cortisol. Cortisol is a hormone that is released in response to stress, so increased levels may indicate that a user is under distress. Cortisol levels are often decreased with regular physical activity or meditation, and developers who target these issues for users may be able to help decrease stress. Companies working in this space include Kenzen and Eccrine Systems, which are using analytes from sweat to determine stress levels.

The most comprehensive physiological analysis currently relies on a combination of sensors to monitor stress. These sensors would monitor the skin temperature, skin conductance, and heart rate to provide insight on both acute and chronic stress, but there are no wearable devices actively monitoring stress with these sensors. Hydration sensors could detect cortisone levels, but they would not be worn continuously like other form factors. Most stress-sensing devices are wrist-based, because they can be worn continuously and the skin conductance on the palm side of the wrist increases with both chronic and acute stress levels. Additionally, HRV is gaining adoption in fitness wearables and can be readily used to monitor for stress, albeit with slightly lower accuracy when used alone. So the same sensors that are being used to provide input on physical activity or sleeping habits can also be used to monitor stress. Combining these wearable stress sensors with existing medical analytics solutions that already exist, such as PhysIQ, NIESM, or even Apple’s Health Kit, can further help individuals live a healthier lifestyle by aggregating multiple streams of data to provide a more holistic picture of health. The insights can move beyond a single recommendation on breathing exercises that reduce stress to provide a more personalized sleeping or eating schedule. This will be one of the trends seen in digital health this year as developers work to include greater personalization and coaching solutions.

By: Reginald Parris