Ralston John D, Stanley Scott, Roper Joshua M, Ralston Andreas B
Neursantys Inc., Menlo Park, CA, 94025, USA.
Caring Hands Caregivers, Cupertino, CA, 95014, USA.
Med Devices (Auckl). 2025 Jun 11;18:319-336. doi: 10.2147/MDER.S522827. eCollection 2025.
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.
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.
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.
Phybrata digital biomarkers enable rapid objective assessment of progressive age-related balance impairments, sensory reweighting, and fall risks in older populations.
评估源自头戴式可穿戴生理振动加速度（phybrata）传感器的数字生物标志物在量化老年人群中与年龄相关的平衡障碍、感觉重加权和跌倒风险方面的效用。
收集并分析了来自4个老年居住社区的516名参与者（年龄77.7±8.0岁，最小51岁，最大98岁，女性334名，男性182名）的数据。参与者首先完成一份问卷，其中包括他们过去6个月的跌倒史。然后使用phybrata传感器对每位参与者进行2分钟的站立平衡测试（睁眼1分钟，随后闭眼1分钟）。从phybrata时间序列数据中得出了四个平衡性能生物标志物：睁眼（Eo）和闭眼（Ec）时的phybrata功率、平均phybrata功率（Eo+Ec）/2以及Ec/Eo phybrata功率比。感觉重加权生物标志物源自phybrata加速度谱密度（ASD）分布。比较了在过去6个月中无跌倒史（NF）的参与者和报告有一次或多次跌倒（FR）的参与者的结果。
与NF参与者相比，FR参与者的所有四个phybrata平衡性能生物标志物的值均显著更高。作为跌倒风险生物标志物，发现Ec phybrata功率与过去6个月报告的回顾性跌倒发生率具有最强的统计相关性。Ec phybrata生物标志物在F和M参与者之间也显示出最强的统计差异。Phybrata感觉重加权生物标志物量化了与年龄相关的障碍以及跨感觉输入（视觉、前庭、本体感觉）、中枢神经系统（CNS）处理和神经运动控制（前庭颈反射）的感觉重加权，揭示了视觉和前庭平衡调节以及前庭颈头部稳定的逐渐减少，这些减少被对本体感觉平衡控制的日益依赖所抵消。
Phybrata数字生物标志物能够快速客观地评估老年人群中与年龄相关的渐进性平衡障碍、感觉重加权和跌倒风险。
