In stroke rehabilitation, muscle synergies have been investigated to provide information on the level of upper limb motor impairment, but not yet for explaining motor recovery after therapy. In this study, we analysed muscle synergies parameters extracted from 62 people with stroke who underwent a specific upper limb treatment (20 sessions, 1h/day, 5d/week, 4 weeks) consisting of virtual reality, robotic or conventional treatment. Overall, participants improved upper limb motor function (Fugl-Meyer Assessment Upper Extremity-FMA-UE: Δ= 7.14 ± 7.46, p< 0.001) but the number of muscle synergies of the impaired side (N-aff) did not change after treatment (N-aff: T0= 8.8 ± 1.5; T1=8.7 ± 1.4; p=0.374). Then, we stratified the sample into Responder (No.=34) and Non-Responder (No.=28) participants, based on the Minimal Clinical Important Difference value of FMA-UE (Δ >5 points). We investigated merging and fractionation indexes in both subgroups and only the Responder subgroup significantly decreased the percentage of merged muscle synergies (p=0.004). No significant changes in the fractionation index resulted in either subgroup. Finally, we identified vocabularies of affected upper limb motor synergies, before (No. 13 synergies) and after treatment (No. 14 synergies), and in unaffected upper limb (No. 16 synergies). We identified upper limb motor functions associated with each muscle synergy in each vocabulary based on the muscles represented in the muscle synergy. There were no differences in motor functions characterizing Responder patients. However, after therapy, both Responder and Non-Responder subgroups were characterized by the same distribution of motor functions across muscle synergies observed in the unaffected limb.

The authors have declared no competing interest.

Clinical Trial ID NCT03530358

https://clinicaltrials.gov/study/NCT03530358

This publication has emanated from research supported under the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 101034252. AT and TL were sustained by the Italian Ministry of Health (Grant Agreement No. GR-2011-02348942 and No. RF-2019-12371486). VCKC was supported by Research Grants Council of Hong Kong (Project No. R4022-18 [RIF], N-CUHK456/21 [NSFC-RGC], 14114721 [GRF], and 14119022 [GRF] to V.C.K.C.). TL, IC, MF and JJ were supported by the European Union-NextGenerationEU (Project RAISE-Robotics and AI for Socio-economic Empowerment).

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