A Wearable System Based on Multiple Magnetic and Inertial Measurement Units for Spine Mobility Assessment: A Reliability Study for the Evaluation of Ankylosing Spondylitis.
Adriana Martínez-HernándezJuan S Perez-LomelíRuben Burgos-VargasMiguel Angel Padilla CastañedaPublished in: Sensors (Basel, Switzerland) (2022)
Spinal mobility assessment is essential for the diagnostic of patients with ankylosing spondylitis. BASMI is a routine clinical evaluation of the spine; its measurements are made with goniometers and tape measures, implying systematic errors, subjectivity, and low sensitivity. Therefore, it is crucial to develop better mobility assessment methods. The design, implementation, and evaluation of a novel system for assessing the entire spine's motion are presented. It consists of 16 magnetic and inertial measurement units (MIMUs) communicated wirelessly with a computer. The system evaluates the patient's movements by implementing a sensor fusion of the triaxial gyroscope, accelerometer, and magnetometer signals using a Kalman filter. Fifteen healthy participants were assessed with the system through six movements involving the entire spine to calculate continuous kinematics and maximum range of motion (RoM). The intrarater reliability was computed over the observed RoM, showing excellent reliability levels (intraclass correlation >0.9) in five of the six movements. The results demonstrate the feasibility of the system for further clinical studies with patients. The system has the potential to improve the BASMI method. To the best of our knowledge, our system involves the highest number of sensors, thus providing more objective information than current similar systems.
Keyphrases
- ankylosing spondylitis
- disease activity
- rheumatoid arthritis
- healthcare
- end stage renal disease
- primary care
- ejection fraction
- physical activity
- newly diagnosed
- molecularly imprinted
- quality improvement
- chronic kidney disease
- systemic lupus erythematosus
- prognostic factors
- case report
- computed tomography
- blood pressure
- deep learning
- peritoneal dialysis
- clinical practice
- high speed
- climate change
- spinal cord injury
- social media
- drug induced
- solid phase extraction