Article
Reference
A multimodal approach to capture post-stroke temporal dynamics of recovery
PIERELLA, Camilla, et al.
Abstract
Several training programs have been developed in the past to restore motor functions after stroke. Their efficacy strongly relies on the possibility to assess individual levels of impairment and recovery rate. However, commonly used clinical scales rely mainly on subjective functional assessments and are not able to provide a complete description of patients' neuro-biomechanical status. Therefore, current clinical tests should be integrated with specific physiological measurements, i.e. kinematic, muscular, and brain activities, to obtain a deep understanding of patients' condition and of its evolution through time and rehabilitative intervention.
PIERELLA, Camilla, et al . A multimodal approach to capture post-stroke temporal dynamics of recovery. Journal of Neural Engineering , 2020, vol. 17, no. 4, p. 045002
DOI : 10.1088/1741-2552/ab9ada PMID : 32516757
Available at:
http://archive-ouverte.unige.ch/unige:140115
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1 Supplementary materials
1.1 Patients’ division in training groups
The stroke participants were enrolled one at a time on a continuous basis. The subjects were randomly divided in the three different groups of experimental training. Specifically, subjects S1 and S2 were assigned to treatment group 1 (additional dose of conventional therapy), subjects S3 and S4 to treatment group 2 (additional standard robotic therapy), and subjects S5 and S6 to treatment group 3 (additional automatic personalized robotic therapy [31]).
1.2 Muscle innervation from the spinal segments
Table 1 Muscle innervated by each spinal cord segment. X correspond to a weight coefficient equal 1
C2 C3 C4 C5 C6 C7 C8 T1
TRAPS X X X
TRAPM X X X
DANT X X
DMED X X
DPOS X X
PECM X X X
LAT X X X
INFRA X X X
RHO X X
BICL X X
BICS X X
BRAD X X
TRILA X X X X
TRILO X X X X
PRO X X
1.3 Details on muscle synergies similarities
Figure 1 Muscle synergies similarity. Results of the comparison between each muscle synergy of the stroke subjects with the ones of the healthy population at different time points, before (shades of blue) and after (shades of green) the rehabilitative intervention. The shaded area reports the mean and standard error for the healthy population and the bar plot the mean value of the stroke one.
1.4 Subject- and session-specific SVD maps
In order to demonstrate that all subjects had similar spatial map per component, we performed SVD decomposition of the EEG signal of each subject and session. We then matched the spatial map obtained for each participant and session (i.e., individual EEG-SVD maps) to the spatial maps obtained concatenating all subjects and sessions (i.e., group-level EEG-SVD maps) using Hungarian algorithm [56].
We computed correlation values between the individual spatial maps and the group-level EEG-SVD maps.
The correlation was high for all top-five components (mean and standard deviation across components:
0.88 ± 0.02 – see Supplementary Figure 2) highlighting that all the subjects had similar spatial maps.
Figure 2 Individual maps. Correlation between individual maps and group-level EEG-SVD maps for the first five components. Error bars represent mean±standard error of the mean across participants
