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In today’s fast-paced world, stress has become a pervasive problem that affects our physical and mental well-being. Chronic stress can have detrimental effects on our health, leading to various disorders and increasing the risk of cardiovascular problems and mental health issues. For effective stress monitoring and management, it is crucial to accurately measure its impact on our bodies.

Traditional methods of stress assessment, such as physical tests and questionnaires, have limitations in terms of subjectivity and accuracy.

However, advancements in wearable biosensors have paved the way for real-time, continuous monitoring of stress biomarkers, providing valuable insights for clinical diagnoses and personal stress management.

Unraveling the complexities of stress: a holistic approach

Stress, as an intricate and multifaceted physiological response to external demands, triggers the orchestrated release of cortisol, adrenaline, and noradrenaline – molecular protagonists underpinning the “fight-or-flight” reaction.

However, prolonged exposure to stress ushers in a cascade of physiological changes, resulting in disruptions to the harmonious equilibrium orchestrated by the hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic adrenal medullary (SAM) axis. These disruptions contribute substantively to the pathogenesis of anxiety, depression, and cardiovascular morbidity.

Beyond traditional metrics: the futility of conventional stress assessment

Traditionally, stress has been measured through physical tests and questionnaires. The Trier Social Stress Test (TSST) is a commonly used test that assesses acute stress levels by subjecting individuals to public speaking and arithmetic tasks. Saliva, blood, psychophysiological, and cognitive measures are then analyzed to evaluate stress levels.

While these tests provide valuable information, they are not without limitations. Variability in test conditions and the subjective nature of self-reporting can impact the reliability and reproducibility of results.

Another widely used method is the Perceived Stress Scale (PSS), a survey that assesses an individual’s overall stress levels based on their perceived life experiences. Similarly, the Kessler Psychological Distress Scale (K10) measures mental distress levels. These tools provide insights into an individual’s subjective experience of stress but do not offer objective measures of physiological responses.

Wearable biosensors: a panacea for stress monitoring

Recent advancements in stress monitoring focus on the quantification of stress biomarkers, which are molecules or biometrics, or physiological indicators, that provide insight into an individual’s nervous system state. Biomarkers can be detected in various bodily fluids, such as blood, saliva, urine, and sweat. Sweat biomarkers, in particular, have gained attention due to the non-invasiveness and ease of collection.

Sweat contains a wide range of metabolites, electrolytes, and minerals that can serve as indicators of stress levels. Cortisol, a glucocorticoid hormone, is considered the gold standard for evaluating the activity of the HPA axis. Other stress biomarkers include epinephrine, norepinephrine, alpha-amylase, and interleukin-6. Electrochemical and colorimetric transduction methods have been developed to detect and quantify these biomarkers in sweat.

Additionally, the Biostrap Kairos, introduces a novel way to assessing autonomic nervous system balance including sympathetic and parasympathetic branch quantifications. Utilizing raw PPG, Kairos captures relevant biometrics including beat-to-beat heart rate data, heart rate variability (HRV) and respiratory rate to allow for in-depth objective data analysis.

Such real-time, seamless, and unobtrusive collection of stress data is highly valuable for simultaneously prioritizing user comfort and feasibility during diverse physiological parameters.

Challenges of sweat measurements

While sweat analysis have shown great potential in stress monitoring, there are still challenges to overcome. The correlation between sweat analyte (or chemical undergoing analysis) concentrations and blood concentrations is complex, and factors such as sweat rate and analyte distribution can affect the accuracy of measurements. Extracting interstitial fluid (ISF) analytes in a non-invasive manner also presents challenges, as extraction efficiency and skin surface contamination can impact accuracy.

Further research is needed to validate the clinical utility of sweat as a diagnostic biofluid for stress monitoring. Improvements in sampling methods and analyte monitoring techniques are necessary to enhance the reliability and accuracy of wearable stress sensors. Integration of multiple sensing arrays and the development of multiplexed wearable sensing platforms hold promise for comprehensive stress assessment.

Innovations toward a new trajectory

Advancements in wearable biosensors have revolutionized the field of stress monitoring. These devices provide real-time, continuous data on stress biomarkers, allowing for personalized stress management and clinical diagnoses. While sweat sensors offer a non-invasive and convenient method for stress assessment, there are challenges that are yet to be overcome.

By harnessing the power of wearable biosensors, like Biostrap Kairos, we can gain valuable insights into our stress levels in real time and any given time of the day and take proactive steps to improve the state of our nervous system.

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What is it?

Heart rate is defined as the number of contractions of the heart, expressed in beats per minute (bpm). The heart rate is a function of local electrical signals in the cardiac cells, neural inputs, and hormonal influence.

Heart rate changes in response to stressors in order to increase circulation of blood, often by increasing cardiac output. This increase in cardiac output helps meet the demands of physiological responses to stress.

Therefore, heart rate can be a valuable metric in understanding the cumulative stress (e.g. emotional and physical stress) that is placed on the body.

How it’s measured

Heart rate can be measured through palpation, electrocardiography (ECG), and photoplethysmography (PPG). Biostrap measures heart rate using PPG, which captures pulse waves of blood flow using red and infrared light. By using the count of pulse waves per unit of time, heart rate in bpm can be obtained.

Heart rate can be measured during activity (active heart rate). However, resting heart rate (RHR) is most often used to clinically assess cardiovascular health, since extra stress on the cardiovascular system is absent. RHR can be subject to acute stress, including observation bias. Therefore, passive collection of RHR through wearables, particularly during sleep, allows for minimizing error that may artificially raise RHR.

Correlation with health conditions

Chronically increased resting heart rate has been correlated with many diseases and their outcomes, particularly hypertension, obesity, cardiovascular diseases, cancer, and metabolic disorders, among others. In many cases, the increased heart rate is not itself a contributor to the disease progression, but rather a signal that there are down-stream effects of the underlying disease.

Acutely increased resting heart rate may be an indication of altered blood flow, reduced plasma volume, psychological stress, activity, infection, and thermal stress. Monitoring heart rate trends can alert when heart rate has changed acutely, but may not be indicative of the cause of the increase. In times where no change in RHR is expected such as during sleep, follow-up evaluation may be warranted.

What is a “normal” range?

<60 bpm = Bradycardia
60-100 bpm = “Normal”
>100 = Tachycardia

A “normal” RHR is considered to be 60-100 beats per minute. Factors that may influence resting heart rate values include:

  • Fitness level
  • Room temperature
  • Body position
  • Emotional stress
  • Body size and/or composition
  • Use of medications

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Interpreting trends

Resting heart rate, measured over time, provides insights into cardiovascular changes in response to lifestyle or disease progression. Since RHR responds relatively quickly to lifestyle changes, tracking resting heart rate over time is recommended in order to monitor positive and negative health adaptations.

Although RHR alone is not enough to diagnose any particular disease, the American Heart Association recommends lowering resting heart rate as much as possible. Exercise training, dietary changes, meditation, and reducing stress are examples of ways to reduce RHR. The decrease in heart rate reflects increased cardiovascular efficiency and decreased systemic stress.

Increases in RHR over time could be an indication of negative cardiovascular changes, and may warrant follow-up testing or lifestyle intervention.


In a clinical study, the Biostrap PPG-based resting heart rate measurement matched within 1 +/- BPM to the reference research grade ECG.

In a small real-world cohort of elderly people, the standalone Fibricheck AF algorithm can accurately detect AF using Wavelet wristband-derived PPG data. Results are comparable to the Alivecor Kardia one-lead ECG device, with an acceptable unclassifiable/bad quality rate. This opens the door for long-term AF screening and monitoring.


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