We present SpineSense , an interactive earable-based framework for continuous monitoring of cervical spine posture and discomfort-related behavior in daily life. Leveraging inertial data from commercial off-the-shelf (COTS) earables (e.g., Apple AirPods Pro 2), SpineSense models the cervical vertebral chain (C1–C7) using SLERP-interpolated quaternions to estimate craniovertebral (CV) angles and identify early pain-relief gestures (e.g., neck rubbing, circular head rolls) that are associated with early signs of musculoskeletal fatigue, as informed by clinical observation. A real-time feedback loop delivers posture-based alerts and weekly compliance summaries to support user awareness and long-term posture correction. Central to our design is a clinician-in-the-loop methodology: clinical experts (including orthopedic surgeons and physiotherapists) informed threshold selection (e.g., CV angle cutoffs), interpreted common discomfort behaviors, and iteratively guided the structure of weekly feedback reports. We evaluate the system on 20 participants and achieve low spine angle estimation error (MAE: 0.876° , RMSE: 1.02° , r = 0.95), and discomfort gesture classification accuracy of F 1 = 0.97. Usability studies across diverse activities show high acceptance (SUS = 84.75, NASA-TLX = 32.7, PSSUQ = 2.13), with formal ANOVA tests validating statistically significant improvements over baseline interfaces. Together, our findings establish the feasibility of engineering interactive cervical health systems using COTS earables that support real-time feedback, clinician-informed reporting, and pervasive deployment in naturalistic settings.
Chugh et al. (Mon,) studied this question.