A Novel Method for Tracking Neck Motions Using a Skin-Conformable Wireless Accelerometer: A Pilot Study

Cervical spine disease is a leading cause of pain and disability. Degenerative conditions of the spine can result in neurologic compression of the cervical spinal cord or nerve roots and may be surgically treated with an anterior cervical discectomy and fusion (ACDF) in up to 137,000 people per year in the United States. A common sequelae of ACDF is reduced cervical range of motion (CROM) with patient-based complaints of stiffness and neck pain. Currently, tools for assessment of CROM are manual, subjective, and only intermittently utilized during doctor or physical therapy visits. We propose a skin-mountable acousto-mechanic sensor (ADvanced Acousto-Mechanic sensor; ADAM) as a tool for continuous neck motion monitoring in postoperative ACDF patients. We have developed and validated a machine learning neck motion classification algorithm to differentiate between eight neck motions (right/left rotation, right/left lateral bending, flexion, extension, retraction, protraction) in healthy normal subjects and patients.