Details

Autor(en) / Beteiligte

• Azrour, Samir
• Pierard, Sébastien
• Van Droogenbroeck, Marc

Titel

Defining a score based on gait analysis for the longitudinal follow-up of MS patients

Ort / Verlag

SAGE Publications

Erscheinungsjahr

2015

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• BACKGROUND. The project GAIMS [ECTRIMS 2013 P800] aims at developing a gait measuring system particularily suited for the clinical routine, and providing a reference database with the gait characteristics of many MS patients (MSP) and healthy people (HP). As the gait impairments are related to the disease progression, defining an objective and quantitative score based on the gait characteristics would be useful for the longitudinal follow-up. Based on the dataset of GAIMS and machine learning techniques (MLT), a score, well correlated with the EDSS, can be defined [Azrour et al. ESANN 2014]. OBJECTIVE. Burggraaff et al. [ECTRIMS 2014 P033] showed that paired comparisons can help human raters to better judge the state of the patients. In the same spirit, we aim at predicting the difference of EDSS between two persons or between two visits of a same person, based on clinical gait measures. We show that the pairwise comparison strategy leads to a score (Gait-Score) well correlated with the EDSS and sensitive to small modifications of the gait. METHODS. The gait of 162 HP and 72 MSP (44 with EDSS>3) has been recorded and analyzed with GAIMS. The Gait-Score is defined using the MLT of [Geurts et al. 2006]. We can compute the Gait-Score of a person by comparing him to others with known EDSS, and compute the difference of Gait-Score of a same person at two different moments. We measure the merits of the Gait-Score by the correlation between the predicted Gait-Score and the EDSS, as well as the ability to detect subtle gait deteriorations among people with ataxia induced by a low dose of alcohol (data of [Piérard et al. ESANN 2014]). RESULTS. The Gait-Score is well correlated with the EDSS (Pearson’s correlation=0.8743). Moreover, it manages to detect a gait deterioration after a small alcohol intake for 19 persons out of 24 (79% correct) which is much better than what was obtained by visual inspection of neurologists (62% according to [Piérard et al. ESANN 2014]). CONCLUSIONS. Based on the accurate gait measures provided by GAIMS, we are able to derive a Gait-Score, automatically, that is well correlated with the EDSS. Moreover, this score is able to detect subtle deteriorations of the gait caused by a low dose of alcohol. These results reinforce our conviction that the use of an automatic method based on gait analysis is very promising for the longitudinal follow-up of MS patients and the assessment of the impact of new drugs and rehabilitation programs.