Common and Specific Information From Neuroimaging and Smartphone

Nantes University Hospital100 enrolled

Overview

Gait alteration is frequent in MS and limitation in walking ability is a major concern in MS patients. Umanit and LMJL (Nantes university) has developed a device call egait to assess walking ability in individuals (eg MS patients).

This device consists in a commercialized IMU sensor (MetaMotionR Sensor, Mbientilab) worn at the right hip, a smartphone app and dedicated algorithm/mathematical model to extract raw sensor data and calculate individual gait pattern (IGP). This IGP consists of a curve, based on quaternion and representing the rotation recorded by the IMU during an average gait cycle. Pursue previous works conducted on (IGP to assess) gait alteration in MS by adding (to IGP) new information from MRI.

Study Type

OBSERVATIONAL

Enrollment

100

Conditions

Multiple Sclerosis

Interventions

eGaitOTHER

IMU sensor (as part of eGait device) worn at the hip during T25FW

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria : * Diagnosis of MS based on McDonald criteria (including Relapsing-remitting and progressive MS) * Over 18 years old /age greater than 18 years * Patients followed at Nantes university hospital or Rennes university hospital * Last known EDSS before inclusion ranging from 0 to 6 inclusive/EDSS of 0 to 6 inclusive, prior inclusion * No relapse within 3 months * With a Medullar MRI planed as part as usual care * Affiliated person or beneficiary of a social security scheme Exclusion Criteria : * Bilateral aid needed to walk * Women who are pregnant * Patient having expressed their opposition * Patient under guardianship or security measure

Locations (1)

Nantes University Hospital

Nantes, Loire-Atlantique, France

RECRUITING

Outcomes

Primary Outcomes

Clustering analyze based on IGP

IGP consists of a curve, based on quaternion and representing the rotation recorded by the IMU during an average gait cycle (0-1).

Time frame: At the inclusion

Clustering analyze based on EDSS score

EDSS is an ordinal scale measuring disability and ranging from 0 (normal examination) to 10 (death due to MS) in a 0,5-point increments from score 1.

Time frame: At the inclusion

Clustering analyze based on MRI lesion load

MRI characteristics are spinal and extraspinal lesion volumes.

Time frame: At the inclusion

Secondary Outcomes

Correlation with disability

Correlation of IGP obtained during a walk of 25 feet with Expanded Disability Status Scale (EDSS). EDSS is an ordinal scale measuring disability and ranging from 0 (normal examination) to 10 (death due to MS) in a 0,5-point increments from score 1. Here EDSS of 0 to 2 inclusive defined as mild, 2,5 to 4 inclusive as moderate and EFDSS of 4,5 to 6 inclusive defined as severe

Time frame: At the inclusion

Correlation with MRI lesion load

Add lesion load (Spinal and extraspinal lesion volume) from MRI to previous correlation.

Time frame: At the inclusion

Building a predictive model for lesion load involving in walk ability from IGP

Root mean square error between observed and lesion load predicted by the model, calculated by cross-validation.

Time frame: At the inclusion

Building a predictive model for group belonging from group established in main outcome based on IGP

Central Contacts

David LAPLAUD, PHD

CONTACT

33 2 40 16 52 00 david.laplaud@chu-nantes.fr

Data from ClinicalTrials.gov

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