Phybrata Digital Biomarkers of Age-Related Balance Impairments, Sensory Reweighting, and Intrinsic Fall Risk

John D Ralston,1 Scott Stanley,2 Joshua M Roper,1 Andreas B Ralston3 1Neursantys Inc., Menlo Park, CA, 94025, USA; 2Caring Hands Caregivers, Cupertino, CA, 95014, USA; 3Vizient Inc., Chicago, IL, 60607, USACorrespondence: John D Ralston, Email [email protected]: To assess the utility of digital biomarkers derived from a head-mounted wearable physiological vibration acceleration (phybrata) sensor to quantify age-related balance impairments, sensory reweighting, and fall risks in older populations.Methods: Data were collected and analyzed from 516 participants aged 77.7 ± 8.0 yrs (min 51 yrs, max 98 yrs, 334 females, 182 males) in 4 residential senior living communities. Participants first completed a questionnaire that included their fall history in the past 6 months. A 2-minute standing balance test was then carried out for each participant using the phybrata sensor (1 minute with eyes open, followed by 1 minute with eyes closed). Four balance performance biomarkers were derived from the phybrata time series data: eyes open (Eo) and eyes closed (Ec) phybrata powers, average phybrata power (Eo+Ec)/2, and Ec/Eo phybrata power ratio. Sensory reweighting biomarkers were derived from phybrata acceleration spectral density (ASD) distributions. Results are compared for participants with no reported fall history (NF) and those reporting one or more falls (FR) in the previous 6 months.Results: All four phybrata balance performance biomarkers show significantly higher values for FR participants vs NF participants. As a fall risk biomarker, Ec phybrata power was found to have the strongest statistical correlation with the reported retrospective incidence of falls within the previous 6 months. The Ec phybrata biomarker also showed the strongest statistical difference between F and M participants. Phybrata sensory reweighting biomarkers quantify age-related impairments and sensory reweighting across sensory inputs (visual, vestibular, proprioceptive), central nervous system (CNS) processing, and neuromotor control (vestibulocollic reflex), revealing progressive reductions in visual and vestibular balance regulation and vestibulocollic head stabilization that are offset by an increasing reliance on proprioceptive balance control.Conclusion: Phybrata digital biomarkers enable rapid objective assessment of progressive age-related balance impairments, sensory reweighting, and fall risks in older populations.Keywords: presbystasis, age-related balance decline, vestibular, phybrata, wearable sensor, biomarker, balance performance, fall risk, sensory reweighting