Posture Detection with Feedback

Forward Head Posture (FHP) is a common musculoskeletal disorder correlated with neck pain that affects a large percentage of the population. Though much medical research has suggested methods for diagnosis and detection of this posture, assessment has been limited due to reliance on individual in-clinic visits. In order to provide timely detection of FHP and real-time feedback for postural correction, continuous monitoring of craniovertebral (CV) angle is needed. This report introduces a solution for continuous, non-invasive assessment of CV angle for FHP detection using a wireless inertial body sensor platform. In addition, a real-time bio-feedback mechanism for postural correction and preventive medicine is presented. The results obtained are validated against a conventional in-clinic method, the Electronics Head Posture Instrument (EHPI), demonstrating the possibility of pervasive detection of FHP.


Forward Head Posture (FHP) is

  • Correlated with neck pain problem
  • Putting stress on entire spine
  • Afflicts large percentage of population
  • Invoked in different scenarios

Need for continuous monitoring

  • Bio-feedback to be provded to correct the bad posture in time
  • FHP can be evaluated through measuring the cranioverterbral (CV) angle


  • Using accelerometer to assess CV angle to detect FHP
  • Provide bio-feedback to correct the bad posture

Research Platform

  • Tempo – Wireless inertial sensing platform, siz-degrees-of-freedom of motion sensing

Bio-feedback System Design


  • Sliding windows technique for CV angle monitoring
  • Threshould detection for FHP

Real-time monitoring and bio-feedback

 Experimental Setup

  1. Elimination of nodes
  2. Inclinometer for initial calibration
  3. Parallel viddeo camera setup for validation


Video validation

  • Overall precision: 88.2%
  • Overall accuracy: 94.5%

Future Work


  • Exploring effective biofeedback types
  • Exploring reasonable frequency for alarm

Form factor

  • Exploring less invasive form factor

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