Science · Publications

Peer-reviewed publications and external research.

The methodology described in the whitebook is grounded in six peer-reviewed papers (below). Beyond our own work, we curate a review of external research linking locomotor activity, lifestyle, biological age, and mortality.

↓ Our publications ↓ Related research

Our publications

Six peer-reviewed papers, 2018–2025

P1 · 2018

Quantitative characterization of biological age and frailty based on locomotor activity records

T. V. Pyrkov, E. Getmantsev, B. Zhurov, K. Avchaciov, M. Pyatnitskiy, L. Menshikov, K. Khodova, A. V. Gudkov, P. O. Fedichev

Aging (Albany NY), Vol. 10, Issue 10

Foundational paper. Establishes that step-count patterns alone are sufficient input for a quantitative biological-age model — the technical premise of the consumer app.

Methodology · Validation on NHANES + UK Biobank

DOI: 10.18632/aging.101603 Read article →

P2 · 2018

Hacking aging: a strategy to use big data from medical studies to extend human life

P. O. Fedichev

Frontiers in Genetics, Vol. 9, Sec. Genetics of Aging

Strategic perspective. Names retirement planning and life insurance as initial commercial applications for the BAA approach — the framing PensionPulse executes on.

Strategic framing

DOI: 10.3389/fgene.2018.00483 Read article →

P3 · 2019

Biological age is a universal marker of aging, stress, and frailty

T. V. Pyrkov, P. O. Fedichev

bioRxiv preprint; book chapter in Biomarkers of Human Aging, Springer

Methodologically defends the choice of risk-based biological-age targets over chronological-age regression. The BAA reading is a meaningful health and financial-risk signal.

Methodology comparison

DOI: 10.1101/578245 Read article →

P4 · 2021

Deep longitudinal phenotyping of wearable sensor data reveals independent markers of longevity, stress, and resilience

T. V. Pyrkov, I. S. Sokolov, P. O. Fedichev

Aging (Albany NY), Vol. 13, Issue 6

The technical engine. Demonstrates the smartphone-only data path delivers actuarially meaningful signal. Introduces the resilience metric supporting the aging-speed framing.

Technical core · 103,830 samples across NHANES, UK Biobank, smartphone, smartwatch

DOI: 10.18632/aging.202816 Read article →

P5 · 2025

Featured

Digital biomarkers of ageing for monitoring physiological systems in community-dwelling adults

J. K. Lu, W. Wang, M. D. A. Mahadzir, J. R. Poganik, M. Moqri, C. Herzog, E. Verdin, V. Sebastiano, V. N. Gladyshev, A. B. Maier; Biomarkers of Aging Consortium

The Lancet Healthy Longevity, Vol. 6, Issue 6

External, recent (2025) third-party validation that the locomotor-activity input class is the right one for population-scale monitoring. Strongest single citation for credibility with regulated counterparties.

Independent validation · Harvard, Stanford, NUS Singapore, Buck Institute

DOI: 10.1016/j.lanhl.2025.100725 Read article →

P6 · 2019

Assessment of aging parameters using wearable electronics

P. O. Fedichev

Recorded lecture, June 2019

Educational asset for non-technical audiences. Useful for advisor channel onboarding and pension-provider audiences.

Educational

Read article →

Want the methodology in plain language?

The methodology page explains how biological age and aging speed are computed without the technical depth of the papers themselves.

Methodology