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By quantifying and surfacing insights about stress load and changes in mental health, users improve their state of mind.
Spren monitors fitness, recovery, and strain, so you can suggest ideal workouts and optimal training programs depending on user goals.
Through quantifying the impact of sleep and optimizing sleep patterns, Spren helps users improve their overall health.
Spren encourages better mindfulness practice by quantifying and gamifying the impact of meditation and breathing on users.
Users quantify and receive insights about the impact of stress, diet, and other lifestyle factors that can accelerate weight loss.
Integrate your product with the Spren API.
Collect powerful biomaker data.
Deliver meaningful insights to your users.
Considered the most comprehensive biomarker of health and fitness, HRV refers to the millisecond variations between heartbeats used to measure the autonomic nervous system.
Respiration rate, or breathing rate, is the number of breaths per minute while at rest.
Acute changes in resting respiration rate can indicate poor rest and recovery or the onset of illness.
A useful metric for monitoring user fitness level and overall health, resting heart rate is the measure of average heart beats per minute (BPM) while the body is in a rested state.
Oxygen saturation, the measure of oxygen-carrying hemoglobin in the blood relative to the amount of hemoglobin not carrying oxygen, dictates whether or not the body is functioning as efficiently as possible.
Spren uses key biomarker metrics to quantify your users' ability to handle challenges based on their body’s cumulative stress load and recovery status. We use these insights to deliver a Daily Readiness Score that helps users optimize their behavior and achieve better long-term results.
Spren recommends ideal workouts and training programs based on each user's goals-and fitness, recovery, and strain levels. These recommendations are adaptable to Power Zone, Strain, Freshness, or any other workout tailoring.
We use a combination of HRV-powered machine learning and context-based reasoning to determine user Stress Score, which represents the acute mental stress load on an individual, as measured by the relative changes in heart rate and heart rate variability.
Small improvements in sleep can have outsized impacts on well being and performance, not to mention on longevity. Spren uses a multitude of data points to analyze user sleep patterns and determine if their sleep quality, quantity, and circadian timing are producing sufficient recovery.
The future of biomarker technology is rapidly evolving. Now your users can harness the power of their smartphone cameras to capture physiological data anytime, anywhere without the need for an additional device.