Evidence

Medical Evidence

Scientific sources behind the biomarkers and scores used in Sam — heart rate, HRV, VO₂ max, sleep quality, stress.

Biomarker Guidelines

Reference ranges and thresholds used in Sam, with the institution or peer-reviewed source that defines each one.

Heart rate (resting)

60–100 bpm = normal adult range; >100 bpm (tachycardia) or <50 bpm with symptoms should prompt medical review because such extremes can signal arrhythmia, infection, or endocrine/metabolic stress.

Source: American Heart Association (AHA)

https://www.heart.org/en/healthy-living/fitness/fitness-basics/target-heart-rates

Resting heart rate (14-day median)

Keep within the same 60–100 bpm band; persistent values outside it carry the same tachy-/bradycardia risks noted above.

Source: American Heart Association (AHA)

https://www.heart.org/en/healthy-living/fitness/fitness-basics/target-heart-rates

Heart rate variability (24 h SDNN)

≥50 ms is considered low cardiac risk; <50 ms is associated with higher post-MI and all-cause mortality. Threshold defined by the Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (ESC/NASPE, 1996).

Source: ESC / NASPE HRV Task Force (1996)

https://www.escardio.org/static-file/Escardio/Guidelines/Scientific-Statements/guidelines-Heart-Rate-Variability-FT-1996.pdf

VO₂ max (20–29 y adults)

Good fitness ≥50 ml·kg⁻¹·min⁻¹ (men) or ≥40 ml·kg⁻¹·min⁻¹ (women); lower values fall into average / below-average categories and are linked to higher cardiometabolic risk. Normative table compiled from American College of Sports Medicine data.

Source: American College of Sports Medicine (ACSM)

https://www.scienceforsport.com/vo2-max/

Daily steps

Sedentary <5,000 steps/day; Active ≥10,000 steps/day. Cut-points come from the Tudor-Locke step-defined activity index, widely used in epidemiological studies linking <5,000 steps with adverse metabolic profiles.

Source: Medicine & Science in Sports & Exercise

https://pubmed.ncbi.nlm.nih.gov/22208412/

Active energy / activity volume

Accumulate ≥500–1,000 MET-min per week (≈450–900 kcal for a 70 kg adult) to meet the 2018 Physical Activity Guidelines for Americans minimum dose for substantial health benefit.

Source: U.S. DHHS / CDC

https://www.cdc.gov/physical-activity/media/pdfs/Physical_Activity_Guidelines_2nd_edition.pdf

Exercise time

At least 150 min/wk moderate-intensity or 75 min/wk vigorous-intensity aerobic activity, as prescribed by the WHO 2020 Global Physical Activity Guidelines, to reduce non-communicable disease risk.

Source: World Health Organization (WHO)

https://www.who.int/initiatives/behealthy/physical-activity

Flights climbed

Climbing >5 flights (≈50 steps) per day was associated with a ~20% lower risk of atherosclerotic cardiovascular disease in a 458,000-participant UK Biobank cohort.

Source: Atherosclerosis (2023) — Tulane Univ. / Harvard collaborators

https://www.atherosclerosis-journal.com/article/S0021-9150%2823%2905221-8/fulltext

Oxygen saturation (SpO₂)

Normal 95–100%; urgent clinical review if ≤94%, or if a reading is ≥3 percentage points lower than the user's usual level. Threshold adopted in the NHS England COVID-19 Oximetry @ Home programme.

Source: NHS England — Oximetry @ Home

https://www.england.nhs.uk/coronavirus/wp-content/uploads/sites/52/2020/06/C1541-Self-monitoring-COVID-19-diary-version-2-January-2022.pdf

Respiratory rate (resting)

12–20 breaths/min is normal; ≥22 breaths/min meets the SIRS/sepsis screening criterion for tachypnea.

Source: U.S. National Library of Medicine / NIH MedlinePlus

https://medlineplus.gov/ency/article/007198.htm

Body temperature (oral)

36.4–37.6 °C is normal; fever ≥38 °C indicates possible infection; <35 °C signals hypothermia.

Source: Cleveland Clinic — evidence-based patient education

https://my.clevelandclinic.org/health/symptoms/10880-fever

Scientific Basis for Health Tracking Metrics

The peer-reviewed evidence behind why each tracked metric matters for long-term health.

Step count

High step counts are associated with reduced all-cause mortality and chronic disease risk.

Source: JAMA Network Open, 2021

Distance walked / run

Increased walking and running distance is linked to improved metabolic health and reduced obesity risk.

Source: British Journal of Sports Medicine, 2019

Active energy burned

Caloric expenditure through activity correlates with lower risk of cardiovascular disease and diabetes.

Source: Circulation, 2016

Flights climbed

Climbing stairs has been shown to improve musculoskeletal and metabolic health.

Source: Journal of Physical Activity & Health, 2017

Walking speed

Faster walking speeds are associated with lower mortality and better functional mobility.

Source: JAMA, 2011

VO₂ max

Gold standard for assessing cardiovascular fitness. Higher VO₂ max correlates with lower cardiovascular disease risk and mortality.

Source: Circulation, 2016

Resting heart rate (RHR)

Lower RHR is a marker of better cardiovascular health and aerobic fitness.

Source: American Heart Association, 2020

Heart rate variability (HRV)

Higher HRV indicates better autonomic regulation and recovery, correlating with reduced cardiovascular risk.

Source: European Heart Journal, 2017

Blood oxygen (SpO₂)

Healthy SpO₂ levels are necessary for optimal aerobic function and cardiovascular efficiency.

Source: Respiratory Medicine, 2020

Exercise duration

Time spent in intentional physical activity is a key factor in improving cardiovascular health; regular, sustained activity increases stroke volume and oxygen uptake efficiency.

Source: Mayo Clinic Proceedings, 2018; Circulation, 2016

Exercise type & intensity

Activities like running and cycling improve cardiovascular fitness when performed at moderate to high intensity.

Source: Mayo Clinic Proceedings, 2018

Total sleep duration

Adults need 7–9 hours of sleep per night for optimal health. Insufficient sleep is linked to increased risk of cardiovascular disease, obesity, and diabetes.

Source: Sleep Medicine Reviews, 2010

Sleep efficiency

Ratio of time asleep to time spent in bed. Higher efficiency is associated with better recovery and reduced fatigue; inefficiency often correlates with insomnia or stress.

Source: Journal of Clinical Sleep Medicine, 2006

Time spent in deep sleep

Deep (slow-wave) sleep is essential for physical recovery, immune function, and memory consolidation.

Source: Nature Reviews Neuroscience, 2017

Sleep onset latency

Time it takes to fall asleep. Longer latency (>30 minutes) is associated with insomnia and increased stress.

Source: Journal of Psychiatric Research, 2015

Sleep regularity

Consistency of sleep and wake times. Irregular sleep patterns are linked to circadian rhythm disorders and increased cardiometabolic risk.

Source: PLOS Biology, 2017

Sleep interruptions

Frequency of awakenings during the night. Frequent interruptions disrupt sleep cycles, impairing recovery and increasing fatigue.

Source: Sleep, 2014

Body Mass Index (BMI)

BMI is correlated with obesity-related risks like diabetes, cardiovascular disease, and certain cancers.

Source: The Lancet, 2016

Body fat percentage

Elevated body fat is linked to increased risk of diabetes and hypertension. Lower percentages within healthy ranges correlate with better metabolic health.

Source: Obesity Reviews, 2010

Lean body mass

Higher lean (muscle) mass correlates with improved metabolic health and reduced risk of sarcopenia with age.

Source: Journal of Cachexia, Sarcopenia and Muscle, 2019

Sleep-Quality Analysis

The clinical and wearable-research foundations behind how Sam scores sleep quality.

Buysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R., & Kupfer, D. J. (1989). The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Research, 28(2), 193–213.Defines clinically validated components of sleep quality (duration, latency, efficiency, disturbances) used as the structural base for the Sam sleep score.
Ohayon, M. M., & Wickwire, E. M. (2019). Sleep efficiency and its clinical relevance: A review. Sleep Medicine Reviews, 44, 23–36.Establishes 85% efficiency as the cutoff between good and poor sleepers; supports our efficiency thresholds.
Mander, B. A., Winer, J. R., & Walker, M. P. (2017). Sleep and human aging: Mechanisms and consequences. Neuron, 94(1), 19–36.Demonstrates the restorative role of deep (slow-wave) and REM sleep, validating inclusion of stage proportions.
Shaffer, F., & Ginsberg, J. P. (2017). An overview of heart rate variability metrics and norms. Frontiers in Public Health, 5, 258.Identifies RMSSD as the preferred short-term HRV index and links low HRV with reduced parasympathetic recovery.
Stanley, D. M., et al. (2013). Heart rate variability and perceived sleep quality: A multi-night field study. Psychophysiology, 50(11), 1034–1039.Empirically connects higher nocturnal HRV with better subjective sleep quality in real-world settings.
Liu, J., et al. (2023). Wearable-based sleep quality assessment using multi-parameter features. IEEE Journal of Biomedical and Health Informatics, 27(4), 1801–1812.Shows that combining efficiency, fragmentation, sleep stages, and HR/HRV yields the most accurate wearable-derived sleep-quality estimates.

Stress Analysis

The HRV-based stress detection literature underpinning Sam's stress metrics.

Shaffer, F., & Ginsberg, J. P. (2017). An overview of heart rate variability metrics and norms. Frontiers in Public Health, 5, 258.Defines HRV measures (SDNN, RMSSD, LF/HF) and their physiological meaning.
Kim, H.-G., Cheon, E.-J., Bai, D.-S., Lee, Y. H., & Koo, B.-H. (2018). Stress and heart rate variability: A meta-analysis and review of the literature. Psychiatry Investigation, 15(3), 235–245.Confirms consistent HRV reduction and LF/HF increase under stress.
Castaldo, R., Melillo, P., Bracale, U., Caserta, M., Triassi, M., & Pecchia, L. (2015). Acute mental stress assessment via short-term HRV analysis in healthy adults: A systematic review with meta-analysis. Biomedical Signal Processing and Control, 18, 370–377.Quantifies HRV metric changes across studies; establishes short-term HRV validity for stress detection.
Delaney, J. P. A., & Brodie, D. A. (2000). Effects of short-term psychological stress on the time and frequency domains of heart rate variability. Biological Psychology, 53(3), 233–243.Experimental proof of decreased HF power, increased HR, and elevated LF/HF during acute stress.
Taelman, J., Vandeput, S., Spaepen, A., & Van Huffel, S. (2009). Influence of mental stress on heart rate and heart rate variability. Proceedings of the 4th European Conference of the IFMBE, 1366–1369.Found HR increase and HRV suppression under cognitive load; foundational for HRV-based stress indices.
Melillo, P., Bracale, U., & Pecchia, L. (2011). Nonlinear heart rate variability features for real-life stress detection: A pilot study on wearable monitoring. IEEE Transactions on Information Technology in Biomedicine, 16(3), 333–341.Demonstrates real-time stress detection using wearable HRV signals.