Evaluation of Optical and Radar Based Motion Capturing Technologies for Characterizing Hand Movement in Rheumatoid Arthritis-A Pilot Study.
Uday PhutaneAnna-Maria LiphardtJohanna BräunigJohann PennerMichael KleblKoray TascilarMartin VossiekArnd KleyerGeorg SchettSigrid LeyendeckerPublished in: Sensors (Basel, Switzerland) (2021)
In light of the state-of-the-art treatment options for patients with rheumatoid arthritis (RA), a detailed and early quantification and detection of impaired hand function is desirable to allow personalized treatment regiments and amend currently used subjective patient reported outcome measures. This is the motivation to apply and adapt modern measurement technologies to quantify, assess and analyze human hand movement using a marker-based optoelectronic measurement system (OMS), which has been widely used to measure human motion. We complement these recordings with data from markerless (Doppler radar) sensors and data from both sensor technologies are integrated with clinical outcomes of hand function. The technologies are leveraged to identify hand movement characteristics in RA affected patients in comparison to healthy control subjects, while performing functional tests, such as the Moberg-Picking-Up Test. The results presented discuss the experimental framework and present the limiting factors imposed by the use of marker-based measurements on hand function. The comparison of simple finger motion data, collected by the OMS, to data recorded by a simple continuous wave radar suggests that radar is a promising option for the objective assessment of hand function. Overall, the broad scope of integrating two measurement technologies with traditional clinical tests shows promising potential for developing new pathways in understanding of the role of functional outcomes for the RA pathology.
Keyphrases
- rheumatoid arthritis
- electronic health record
- patient reported
- endothelial cells
- disease activity
- high speed
- ankylosing spondylitis
- newly diagnosed
- ejection fraction
- induced pluripotent stem cells
- mass spectrometry
- high resolution
- systemic lupus erythematosus
- machine learning
- data analysis
- risk assessment
- chronic kidney disease
- sleep quality
- patient reported outcomes
- smoking cessation