Research Paper Volume 13, Issue 6 pp 7900—7913

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

Resilience and its age-related degradation can be measured using longitudinal motion sensor data. (A) The relaxation rate (or the inverse characteristic recovery time) computed for sequential age-matched cohorts of Fitbit users decreased approximately linearly with age. The recovery rate could be extrapolated to zero in the age exceeding ~110 y.o. (at this point, we may expect the complete loss of resilience and, hence, loss of stability of the organism state). The shaded area shows the 95% confidence interval of fit using GeroSense BAA. (B) The fraction of individuals suffering from the lack of resilience (defined as BAA’s autocorrelation time exceeding 3 weeks; the vertical axis) as the function of chronological age (the horizontal axis). The autocorrelation time was computed from longitudinal tracks of GeroSense BAA predicted for Fitbit wristband users.

Figure 8. Resilience and its age-related degradation can be measured using longitudinal motion sensor data. (A) The relaxation rate (or the inverse characteristic recovery time) computed for sequential age-matched cohorts of Fitbit users decreased approximately linearly with age. The recovery rate could be extrapolated to zero in the age exceeding ~110 y.o. (at this point, we may expect the complete loss of resilience and, hence, loss of stability of the organism state). The shaded area shows the 95% confidence interval of fit using GeroSense BAA. (B) The fraction of individuals suffering from the lack of resilience (defined as BAA’s autocorrelation time exceeding 3 weeks; the vertical axis) as the function of chronological age (the horizontal axis). The autocorrelation time was computed from longitudinal tracks of GeroSense BAA predicted for Fitbit wristband users.