Functional synergy recruitment index as a reliable biomarker of motor function and recovery in chronic stroke patients

Abstract

Objective. Stroke affects the expression of muscle synergies underlying motor control, most notably in patients with poorer motor function. The majority of studies on muscle synergies have conventionally approached this analysis by assuming alterations in the inner structures of synergies after stroke. Although different synergy-based features based on this assumption have to some extent described pathological mechanisms in post-stroke neuromuscular control, a biomarker that reliably reflects motor function and recovery is still missing. Approach. Based on the theory of muscle synergies, we alternatively hypothesize that functional synergy structures are physically preserved and measure the temporal correlation between the recruitment profiles of healthy modules by paretic and healthy muscles, a feature hereafter reported as the FSRI. We measured clinical scores and extracted the muscle synergies of both ULs of 18 chronic stroke survivors from the electromyographic activity of 8 muscles during bilateral movements before and after 4 weeks of non-invasive BMI controlled robot therapy and physiotherapy. We computed the FSRI as well as features quantifying inter-limb structural differences and evaluated the correlation of these synergy-based measures with clinical scores. Main results. Correlation analysis revealed weak relationships between conventional features describing inter-limb synergy structural differences and motor function. In contrast, FSRI values during specific or combined movement data significantly correlated with UL motor function and recovery scores. Additionally, we observed that BMI-based training with contingent positive proprioceptive feedback led to improved FSRI values during the specific trained finger extension movement. Significance. We demonstrated that FSRI can be used as a reliable physiological biomarker of motor function and recovery in stroke, which can be targeted via BMI-based proprioceptive therapies and adjuvant physiotherapy to boost effective rehabilitation. Abbreviations and acronymsFSRI functional synergy recruitment index BMI brain-machine interface UL upper limb EMG electromyography FMA Fugl-Meyer assessment MAS modified Ashworth scale VAF variance accounted for nCC normalized correlation coefficient

InfoMuNet: Information-theory-based Functional Muscle Network Tracks Sensorimotor Integration Post-stroke

“…However, previous studies did not indicate changes in W caused by stroke in the patient group (for example one W for the affected and another W for the less-affected limb). In contrast, previous studies supported the notion of having the same W's for both affected and less-affected limbs in stroke patients and emphasized the changes only in the activation coefficients (A) 23,43 . This suggests that synergy reflects mainly spinal control 23 and does not indicate supraspinal changes associated with stroke.…”

Flexible Recruitments of Fundamental Muscle Synergies in the Trunk and Lower Limbs for Highly Variable Movements and Postures

“…Since we identified the fundamental muscle synergies that may underlie diverse human behaviors in healthy individuals, investigating the changes in muscle synergies such as the number of synergies as well as their compositions in a population of interest may facilitate the understanding of distinct features in motor controls that are associated with severity of symptoms [ 41 , 50 ] or that profile myriad skills and performance in athletes [ 27 , 28 ]. Second, previous studies reported that the inner structure of synergies in stroke patients was not necessarily altered, but that their recruitment patterns due to compromising descending signals were [ 41 , 54 ]. Since our study found that the flexible recruitments of fundamental muscle synergies play an important role in executing diverse motor tasks that related to daily activity livings in healthy individuals, it can be speculated that there is a significant relationship between altered recruitments of fundamental muscle synergies and poor motor function in stroke.…”

Neuromechanical Biomarkers for Robotic Neurorehabilitation

“…Since the Rehabilomics has been primarily focused on the proteomics, genomics and metabolomics (Wagner and Zitelli, 2013 ; Skriver et al, 2014 ; Wagner, 2017 ; Wagner and Kumar, 2019 ), kinematics measures, and neuroimaging and electrophysiological recordings, they have also been widely explored as the potential biomarkers in the field of the robot-assisted neurorehabilitation (Philips et al, 2017 ; Belfatto et al, 2018 ; Pirondini et al, 2018 ; Krauth et al, 2019 ; Mane et al, 2019 ; Irastorza-Landa et al, 2021 ). In particular, the kinematics and electrophysiological indicators can be exploited as biomarkers, mainly because they are non-invasive and portable techniques, suitable for measuring the activity in both the acute and chronic phases.…”