Behavioral
Short-horizon exposures
· Steps · Dietary energy · Carbohydrate · Sodium · Alcohol · Daylight
Hours → days
A BIOLOGICAL TIME-MACHINE
Health intelligence
you can interrogate.
A scientific workstation for exploring your health. BioMIR brings behavioral, functional, and cardiometabolic data into Adaptive BioAge, an evolving health index. Like a market index, it summarizes many inputs while keeping its domains and biomarkers open to inspection. Follow trends, review prioritized actions, and record your action check-ins. Separate clinical age models use lab results for a longer-term view.
Explore BioMIR · iPhone1 / 8
Begin with today’s full picture configured to your preference.
See Adaptive BioAge, domain trends, and today’s prioritized action together. Swipe through the recommendations or tap
to open the ranked list. Before check-in, tap 
to plan or to consider an action; use 
to undo a selection or 
to reset. At check-in, record 
for a completed action or 
for a skipped one. Eligible completions earn modeled REC age-equivalent credit. Open a card to inspect its contributing biomarkers.
Set the time for your daily action review.
The check-in settings show the selected review time, optional reminder, and persistence-alert preferences. Before check-in, cycle between Suggested and Planned; afterward, record Completed or Skipped. Use the panel to set when the review takes place and whether a reminder should prompt it, while separate alert controls let you choose which recurring patterns to follow over time.
Close the daily loop with a recorded outcome.
The check-in summary closes the daily review with 5 Done and 3 Skipped outcomes; the REC counter updates alongside recorded follow-through. Use the totals to see which commitments were completed, set aside, or remain unresolved, then compare the day’s action record with its eligible opportunities and running credit in the same view.
Adaptive BioAge summary
The summary brings the selected estimate together with acceleration, its displayed interval, data support, and ranked contributors. Persistence counts qualifying observations across four contribution bands, while Trend summarizes dated direction; these complementary panels help readers inspect the estimate, its support, and its behavior over time.
Reclaimed BioAge detail
The REC detail separates reclaimable and reclaimed modeled years from action counts and completion percentage. The Adherence table groups qualifying days by earned-credit band, while Trend fits the signed daily record; compare these summaries to understand how opportunity-weighted credit and action-by-action follow-through are represented over time.
Reading the three companion measures
The selected Month · Mean view compares the composite series with its fitted direction (↘), high-band persistence, and reclaimed-credit summary. Read the shaded interval alongside the estimate, then compare threshold frequency and opportunity-weighted credit as distinct longitudinal views; together, these measures help organize direction, persistence, and recorded follow-through across the displayed period.
Following a modeled transition
This monthly view follows a synthetic transition through the composite trajectory, persistence summary, and recorded action credit. Compare the direction of the series with the frequency of higher-band observations and the separate credit record; the combined view helps organize temporal patterns without reducing them to a single indicator.
Focus the daily view on the composite and its contributors.
This minimal arrangement gives the composite more room while retaining contribution rings and recent direction below. Use it when a quick overview is the priority, then expand the remaining cards to bring back action guidance, dated clinical context, or information about the data supporting the current result.Swipe to explore · Tap to enlarge
Inspiration
Inspired by the spirit of a tricorder and the familiar logic of a market index, BioMIR makes your trajectory visible—and the contributors behind its movement open to investigation. BioMIR brings that idea to selected, high-value health signals through an engaging glass-like interface—inviting you to navigate the whole and investigate what shapes your vitality and longevity.
No dedicated BioMIR wearable required. Apple Health integration.
Core health calculations on device. Contributor-level interpretation.
Daily biological composite. Distinct clinical perspectives.
- Longitudinal trends
- Quantified persistence
- Prioritized, dose-banded guidance
- Adherence tracking
- Reclaimable BioAge credits
- Daily voice briefing
- Clinical age models
Explore the approach
Trend reveals direction; persistence shows how often an elevated contribution recurs. Adherence tracks eligible action completion and reclaimable age-equivalent credits. Navigate longitudinal peaks and troughs. For each, inspect the dates and biomarker inputs, then compare the pattern with the preceding adherence profile to trace the evidence-to-action loop.
Understanding Δ-years
Read the direction. Negative Δ-years indicate favorable model contributions; positive values indicate adverse ones. Blue and red contribution colors reinforce that direction, while chart hues distinguish domains. These are model estimates, not years of lifespan gained or lost.
BioMIR analytical architecture
One record.
Distinct model views.
Behavioral, Functional, and Cardiometabolic inputs form Adaptive BioAge. KDM and Levine PhenoAge provide separate context from episodic clinical panels.
View 1 Lifestyle Short View Daily longitudinal synthesis
View 2 Clinical Long View Episodic longitudinal synthesis
Functional
Responsive physiologic capacity
· HRV · Resting HR · VO₂max · Total sleep · Walking speed · Cardio Recovery
Days → months
Cardiometabolic
Slow-moving baseline state
· BMI · SBP · FBG
Weeks → months
Clinical panel
Episodic reference state
· Alb · ALP · BUN · Cr · CRP · HbA1c · SBP · TC · Glu · Lymph% · MCV · RDW · WBC
Episodic · dated panels
Adaptive BioAge
Integrated longitudinal model
Hierarchical composite with an age-calibrated cardiometabolic baseline and bounded, asymmetric Functional and Behavioral Δ-year contributions. The output is expressed in age-equivalent Δ-years relative to chronological age, with negative values representing age-equivalent reward and positive values age-equivalent penalty, while retaining contributor attribution over time.
Klemera–Doubal Method (KDM)
Multivariate biological-age estimator combining age-calibrated biomarker regressions with chronological age.
Levine PhenoAge
Mortality-trained multivariable biomarker score mapped through a Gompertz function to an age-equivalent phenotype.
Cadence depicts characteristic observation and interpretation timescale—not a causal sequence, fixed biological deadline, or prescribed testing interval. Cardiometabolic state is interpreted longitudinally; KDM and Levine PhenoAge use separate clinical-panel context.
Evidence to action · a separate record
Reclaimed BioAge (REC)
REC turns prioritized signals into a short action list and records whether eligible actions are reported complete. Its Adherence view summarizes those reports and can be reviewed beside Adaptive BioAge and later observations, while each remains a separate record.
- 01Prioritize signals
- 02Choose a useful action
- 03Record follow-through
Conceptual sequence, not measured data; timing alone does not establish cause or response.
What sits beneath the model
Fifteen active inputs.
Three complementary domains.
Six Behavioral, six Functional, and three Cardiometabolic inputs are grouped by their distinct roles and timescales—not treated as interchangeable votes. Meditation is not active in scoring.
017 exposure inputs
Behavioral
Modifiable routines and exposures enter Adaptive BioAge as bounded contributors rather than direct measurements of physiological state.
026 physiology inputs
Functional
Heart rate variability and resting heart rate describe autonomic context; VO₂max reflects cardiorespiratory capacity; Cardio Recovery captures post-exercise response; Walking Speed reflects mobility; and Total Sleep provides restorative context.
033 baseline inputs
Cardiometabolic
A slower-moving age-equivalent baseline anchors the daily composite, with original observation dates preserved when eligible prior values are carried forward.
Adaptive BioAge uses all three domains. KDM and Levine PhenoAge remain separate in Clinical Long View. Reclaimed BioAge (REC) connects prioritized signals with practical actions and recorded follow-through. See how prioritized actions work ↗
A controlled scientific core
Deterministic science.
Adaptive personalization.
Current core. Adaptive BioAge is computed from prespecified, version-controlled model rules rather than a self-training model. For the same eligible inputs evaluated under the same model version, the scientific calculation remains reproducible and the result can be traced back through domains and contributors.
Future personalization. BioMIR’s roadmap keeps adaptive intelligence downstream of that authoritative calculation. On-device learning may eventually characterize individual baseline, variability, temporal response, and action-response patterns without silently rewriting the equations that produced the underlying BioMIR result.
See the architecture and roadmapA model output expressed in age-equivalent units. A way to put signals into context.
Adaptive BioAge is a model output expressed in age-equivalent units relative to chronological age. Negative or positive Δ-years indicate position on the model’s reference scale; they are not rewards, penalties, or direct measurements of years gained or lost. In the current provisional model, Cardiometabolic Age is the principal uncapped anchor, the Behavioral contribution is signed and bounded, and the Functional contribution is adverse-only and bounded.
Short-term movement can reflect recent behavior, functional physiology, available data, or model assumptions. It does not establish a change in lifespan.
Interpret the result alongside its contributors, Data Confidence, Data Freshness, and trends—not as a verdict on your health.
From signals to understanding
See what contributes.
Choose what comes next.
Follow a change over time. Inspect its contributors. Understand the measurements behind it. Move from Trends to domain and biomarker detail with Dashboard and Trends sharing period and statistic selections.
Take a closer look- 01
Look beneath the headline
Explore biomarker-level contributions instead of stopping at a single summary estimate.
- 02
Put patterns in perspective
Read trends with Data Confidence and Data Freshness. Data Confidence summarizes daily input support and reflects the age of carried Functional and Cardiometabolic observations; separate Data Freshness displays show Cardiometabolic and clinical-panel recency.
- 03
Make space for action
Review prioritized actions as Suggested, Considered, or Planned, then record Completed or Skipped at check-in. Recent Behavioral observations can keep advice useful the next day; supported persistence and trend help focus attention before the next choice.
Set an evening check-in time and choose whether to receive a daily completion reminder at that time in
Action Check-in settings.
An open, careful approach
Good questions
are part of the science.
01 / Methodology
How the models work
Understand reference context, age-equivalent outputs, assumptions, data support, and the distinction between a model output and a clinical conclusion.
Explore the science02 / Resources
Go deeper into the evidence
Explore scientific reading and discussion, keeping population evidence separate from individual observations.
Browse resourcesEvidence-grounded explainers
Ask better questions
of biological age.
Short, referenced guides on the scientific ideas behind age-like health scores, wearables, functional physiology, cardiometabolic context, and longitudinal interpretation.
Browse all InsightsBiological age fundamentals
Biological age vs. health age: what do these scores actually mean?
Age-like health scores can be useful summaries, but the number only makes sense in the context of the inputs, reference population, outcome, and model assumptions behind it.
Read the explainerLongitudinal interpretation
Why can a biological-age estimate change from day to day?
High-frequency age estimates are dynamic summaries. Short-term movement can be informative without being interpreted as irreversible aging or lifespan change.
Read the explainerDigital health landscape
Apple Health Age and BioMIR: similar inputs, different modeling questions
Apple has announced Health Age for a forthcoming Health app update, making model transparency and interpretation an increasingly important comparison.
Read the explainerChoose your path
Use it. Examine it.
Help validate it.
01
Use BioMIR
Download the current public release and explore Adaptive BioAge, contributors, trends, and clinical long-view models.
App Store ↗ 02Study the model
Review the architecture, model assumptions, evidence boundaries, missing-data logic, and validation status.
Methods ↗ 03Research with BioMIR
Explore collaboration priorities for longitudinal convergence, preventive engagement, reliability, interpretability, and prospective validation.
Research & collaboration ↗Help shape BioMIR
Bring your curiosity.
Explore the beta and share your experience. Thoughtful feedback helps inform what comes next.
Daily insight with the evidence in view.
BioMIR helps adults inspect habits and physiology alongside slower cardiometabolic measurements and separate clinical age models. Trace contributors, supporting dates and persistence across a personal timeline. Independent validation of the proprietary composite remains pending.
Check whether BioMIR fits your data and goals · Compare approaches · See what software controls establish