Multiple Sclerosis
Conditions
Keywords
Wearable sensor, Gait, MRI
Brief summary
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).
Detailed description
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.
Interventions
OTHEReGait
IMU sensor (as part of eGait device) worn at the hip during T25FW
Sponsors
Nantes University Hospital
Rennes University Hospital
Study design
Observational model
OTHER
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
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 * MRI scan can be performed within a maximum of 4 months after or before the walking test. * 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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Clustering analyze based on IGP | At the inclusion | IGP consists of a curve, based on quaternion and representing the rotation recorded by the IMU during an average gait cycle (0-1). |
| Clustering analyze based on EDSS score | At the inclusion | 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. |
| Clustering analyze based on MRI lesion load | At the inclusion | MRI characteristics are spinal and extraspinal lesion volumes. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Correlation with disability | At the inclusion | 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 |
| Correlation with MRI lesion load | At the inclusion | Add lesion load (Spinal and extraspinal lesion volume) from MRI to previous correlation. |
| Building a predictive model for lesion load involving in walk ability from IGP | At the inclusion | Root mean square error between observed and lesion load predicted by the model, calculated by cross-validation. |
| Building a predictive model for group belonging from group established in main outcome based on IGP | At the inclusion | Multiclass accuracy between real and predict group, calculated by cross-validation |
Countries
France
Contacts
CONTACTDavid LAPLAUD, PHD
Outcome results
None listed