Usability and acceptability of the ASSESS MS movement recording tool in Multiple Sclerosis using depth-sensing computer vision (P3.220)

Objectives: To test the usability and acceptability of the ASSESS MS movement recording tool with health professionals and multiple sclerosis patients. Background: Sensor-based recordings of human movements are become increasingly important for the assessment of motor symptoms in neurological disorders beyond rehabilitative purposes. The ASSESS MS system is being developed with the aim of providing a more consistent and finer grained measurement of motor dysfunction in Multiple Sclerosis than currently possible. The recording tool was designed to achieve the quality of depth-sensor data capture in the clinical environment needed for system accuracy. Methods: A prospective mixed methods study was carried out at three centres. After training, health professionals performed recordings of standardized movements with the recording tool. Recordings were video-taped. Patients and health professionals completed Likert-scale questionnaires with range 1 to 7 after each visit and a final interview was done with the health professional. Videos and interviews were coded and descriptive statistics used to analyse the questionnaires. Results: The recording tool was successfully used by all health professionals, with no differences in length of examination, data quality or questionnaire scores between nurses and doctors. Ninety-eight percent of the pre-defined movement protocol was performed correctly. Patients “understood what to do during the study examination“ (6.6 / strongly agree) and health professionals thought “the recording tool was easy to use“ (5.9 / agree). Patients “would like my health professional to use the recording system during my future examinations“ (6 / agree - inverted data). Health professionals ,,would use the recording system in future examinations“ (5.4 / agree). Conclusions: The ASSESS MS movement recording tool is usable and acceptable to patients and health professional with high consistency of the data captured. It can be deployed in new clinics to be used by a range of health professionals with minimal training. Disclosure: Dr. Morrison has received personal compensation for activities with Microsoft Research as an employee. Dr. D9Souza has received personal compensation for activities with Bayer AG, Teva, and Genzyme. Dr. D9Souza has received research support from the University of Basel. Dr. Huckvale has received personal compensation for activities with Microsoft Research as an employee. Dr. Dorn has received personal compensation for activities with Novartis Pharma AG as an employee. Dr. Burggraaff has received personal compensation for activities with Novartis. Dr. Kamm has received personal compensation for activities with Biogen Idec, Novartis, Bayer Pharmaceuticals, Merck Serono, Genzyme, and Pfizer Inc. Dr. Steinheimer has nothing to disclose. Dr. Kontschieder has received personal compensation for activities with Microsoft Research as an employee. Dr. Vogel has received personal compensation for activities with Novartis as an employee. Dr. Criminisi has received personal compensation for activities with Microsoft as an employee. Dr. Uitdehaag has received personal compensation for activities with Biogen Idec, Novartis, EMD Serono, Teva Neuroscience, Genzyme Corporation, and Roche Diagnostics Corporation. Dr. Dahlke has received personal compensation for activities with Novartis as an employee. Dr. Kappos has received personal compensation for activities with Actelion Pharmaceuticals. Dr. Sellen has received personal compensation for activities with Microsoft Research as an employee.