Muscle synergies model has been purposed as a solution to explain how Central Nervous System can control the dimensionality and redundancy in voluntary movements. In experimental setting, the set of synergies was extracted from the surface electromyography (sEMG) patterns recorded during tasks execution by using decomposition algorithms. In stroke rehabilitation scenario, muscles synergies features have been viewed as a biomarker of prognosis of motor recovery, according to clinical outcome. In this PhD project, the main goal is to investigate the muscle synergies model to describe the motor recovery in stroke survivors, both in upper limb and hand motor recovery. In Study N.1, we analysed muscle synergies parameters extracted from a sample of 62 stroke survivors who underwent a specific upper limb treatment. Overall, patients improved upper limb motor function (Fugl-Meyer Assessment Upper Extremity, FMA-UE Δ= 7.2 ± 7.5, p< 0.001). However, 34 (54.8%) patients resulted Responder and 28 (45.2%) No-Responder to the treatment (based on Minimal Clinical Important Difference > 5 points). We observed a significant difference in the percentage of merged muscle synergies between subgroups, with only the Responder group significantly decreased the percentage of merged muscle synergies (p=0.004). Moreover, we identified the Vocabularies of affected upper limb motor functions, before (Vpre, No. 13 synergies) and after treatment (Vpost, No. 14 synergies), and in unaffected upper limb (Vhealthy, No. 16 synergies). There where no differences in motor functions characterizing Responder patients, but both Responder and No-Responder groups, after therapy, were characterized by the same motor function than healthy limb. In Study N.2, we developed a wearable device REMO (i.e., Morecognition Ltd, Turin, Italy), composed of 8 dry bipolar electrodes able to detect muscle activation (i.e., sEMG) during wrist and hand movements. We tested the REMO on 10 healthy subjects to define the safety, reliability, repeatability of the measurement and the accuracy in muscle activation detection (trial for CE Marking, Class1 medical device). In Study N.3, we tested REMO on a sample of 117 stroke survivors to determine the clinical determinants needed to use REMO wearable to control a computer interface, in order to test the device in hand rehabilitation setting. We tested REMO in three conditions: 1, 5 or 10 hand gestures control. Results showed that 65% of patients were able to control 10 gestures, 19% of patients control 9 to 1 gestures, and 16% control no gestures. Results showed that mild upper limb motor impairment (FMA-UE ≥ 18 points), the level of spasticity at flexor carpi muscles and the level of pain and joint-restrictions of upper limb predicted the control of wearable REMO. Finally, in Study N.4, we implemented a new muscle-synergies based method to describe the motor recovery after a hand specific motor training in 10 stroke survivors using REMO. The treatment consisted of 15 sessions of task-specific training provided by REMO or in a conventional environment. Then, we calculated the percentage of similarity comparing the sEMG of stroke survivors with the sEMG signals collected in 4 age-matched healthy subjects, during the same 12 tasks. Results showed that there was an improvement in motor function in all patients (FMA-UE Δ= 7.88 ± 4.82, p= 0.008) but no differences in comparing two types of treatment (p=0.241). Moreover, in all subjects, in sEMG similarity index, there were significant differences only in the task grasping a pencil. Thus, new improvements in similarity index calculation using REMO will be needed for hand motor assessment. In conclusion, muscle synergies analysis may provide new information about neural mechanisms of upper limb and hand motor recovery. Further, future research may investigate the application of muscle synergies in clinical assessment and in controlling new technological solution in neurorehabilitation.
Il modello delle sinergie muscolari è stato proposto come soluzione per spiegare come il Sistema Nervoso Centrale possa controllare la dimensionalità e la ridondanza nei movimenti volontari. In un contesto sperimentale, le sinergie muscolari vengono estratte applicando algoritmi di decomposizione del segnale elettromiografico (sEMG) registrato durante l'esecuzione di task motori. Nel contesto della riabilitazione post-ictus, le caratteristiche delle sinergie muscolari sono state studiate come biomarcatori prognostici del recupero motorio. In questo progetto di dottorato, l'obiettivo principale è investigare l’applicazione del modello delle sinergie muscolari per descrivere il recupero motorio post-ictus, nel recupero della funzione motoria dell’arto superiore e della mano. Nello Studio N.1 abbiamo analizzato i parametri delle sinergie muscolari estratte da un campione di 62 pazienti post-ictus sottoposti a un trattamento specifico per l'arto superiore. Complessivamente, i pazienti hanno migliorato la funzione motoria dell'arto superiore (Fugl-Meyer Assessment-Upper Extremity, FMA-UE Δ= 7.2 ± 7.5, p< 0.001). Tuttavia, 34 (54.8%) pazienti sono risultati "Responder" e 28 (45.2%) "Non-Responder" al trattamento, sulla base del valore di Minimal Clinical Important Difference della scala FMA-UE (MCID >5 punti). Abbiamo osservato una diminuzione della percentuale di sinergie muscolari fuse solo nel gruppo "Responder" (p=0.004). Inoltre, abbiamo identificato il vocabolario delle funzioni motorie dell'arto superiore, prima e dopo la terapia, e non vi erano differenze nelle funzioni motorie tra i sottogruppi, ma, dopo la terapia, sia nei pazienti "Responder" che "Non-Responder", le funzioni dell’arto superiore leso erano più simili all'arto sano. Nello Studio N.2, abbiamo sviluppato un dispositivo indossabile REMO (Morecognition Ltd, Torino, Italia), composto da 8 elettrodi bipolari in grado di rilevare l'attivazione muscolare (elettromiografia di superficie, sEMG) durante i movimenti di polso e mano. Abbiamo testato REMO su 10 soggetti sani per definire la sicurezza, l'affidabilità, la ripetibilità della misurazione e l'accuratezza nella rilevazione dell'attivazione muscolare (test marcatura CE, dispositivo medico di Classe 1). Nello Studio N.3, abbiamo testato REMO su un campione di 117 pazienti post-ictus per determinare le caratteristiche cliniche dei pazienti in grado di utilizzare REMO. Il 65% dei pazienti era in grado di controllare 10 gesti, il 19% dei pazienti controllava da 9 a 1 gesti e il 16% non controllava alcun gesto. Le analisi hanno evidenziato che il controllo di REMO è definito dal deficit motorio dell'arto superiore (FMA-UE ≥ 18 punti), il livello di spasticità ai muscoli flessori del carpo, e il livello di dolore e restrizioni articolari dell'arto superiore. Infine, nello Studio N.4, abbiamo utilizzato REMO nel trattamento della mano in 10 pazienti post-ictus. Il trattamento consisteva in 15 sessioni di allenamento task-specifico utilizzando REMO o in un ambiente convenzionale. Abbiamo calcolato la percentuale di similarità confrontando il sEMG dei pazienti con i segnali sEMG raccolti in 4 soggetti sani della stessa età, durante gli stessi 12 compiti. I risultati hanno mostrato un miglioramento della funzione motoria in tutti i pazienti (FMA-UE Δ= 7.88 ± 4.82, p= 0.008) ma nessuna differenza nel confronto tra i due tipi di trattamento (p=0.241). Inoltre, nell'indice di similarità sEMG, vi erano differenze significative solo nella presa a pinza. Pertanto, saranno necessari miglioramenti nel calcolo dell'indice di similarità utilizzando REMO per la valutazione motoria della mano. In conclusione, l'analisi delle sinergie muscolari può fornire nuove informazioni sui meccanismi neurali del recupero motorio dell'arto superiore e della mano. Inoltre, ricerche future potrebbero indagare sull'applicazione delle sinergie muscolari nella valutazione clinica e nel controllo di nuove soluzioni tecnologiche nella neuroriabilitazione.
Muscle synergies parameters to explain upper limb and hand motor recovery after stroke
Pregnolato, Giorgia
2024-01-01
Abstract
Muscle synergies model has been purposed as a solution to explain how Central Nervous System can control the dimensionality and redundancy in voluntary movements. In experimental setting, the set of synergies was extracted from the surface electromyography (sEMG) patterns recorded during tasks execution by using decomposition algorithms. In stroke rehabilitation scenario, muscles synergies features have been viewed as a biomarker of prognosis of motor recovery, according to clinical outcome. In this PhD project, the main goal is to investigate the muscle synergies model to describe the motor recovery in stroke survivors, both in upper limb and hand motor recovery. In Study N.1, we analysed muscle synergies parameters extracted from a sample of 62 stroke survivors who underwent a specific upper limb treatment. Overall, patients improved upper limb motor function (Fugl-Meyer Assessment Upper Extremity, FMA-UE Δ= 7.2 ± 7.5, p< 0.001). However, 34 (54.8%) patients resulted Responder and 28 (45.2%) No-Responder to the treatment (based on Minimal Clinical Important Difference > 5 points). We observed a significant difference in the percentage of merged muscle synergies between subgroups, with only the Responder group significantly decreased the percentage of merged muscle synergies (p=0.004). Moreover, we identified the Vocabularies of affected upper limb motor functions, before (Vpre, No. 13 synergies) and after treatment (Vpost, No. 14 synergies), and in unaffected upper limb (Vhealthy, No. 16 synergies). There where no differences in motor functions characterizing Responder patients, but both Responder and No-Responder groups, after therapy, were characterized by the same motor function than healthy limb. In Study N.2, we developed a wearable device REMO (i.e., Morecognition Ltd, Turin, Italy), composed of 8 dry bipolar electrodes able to detect muscle activation (i.e., sEMG) during wrist and hand movements. We tested the REMO on 10 healthy subjects to define the safety, reliability, repeatability of the measurement and the accuracy in muscle activation detection (trial for CE Marking, Class1 medical device). In Study N.3, we tested REMO on a sample of 117 stroke survivors to determine the clinical determinants needed to use REMO wearable to control a computer interface, in order to test the device in hand rehabilitation setting. We tested REMO in three conditions: 1, 5 or 10 hand gestures control. Results showed that 65% of patients were able to control 10 gestures, 19% of patients control 9 to 1 gestures, and 16% control no gestures. Results showed that mild upper limb motor impairment (FMA-UE ≥ 18 points), the level of spasticity at flexor carpi muscles and the level of pain and joint-restrictions of upper limb predicted the control of wearable REMO. Finally, in Study N.4, we implemented a new muscle-synergies based method to describe the motor recovery after a hand specific motor training in 10 stroke survivors using REMO. The treatment consisted of 15 sessions of task-specific training provided by REMO or in a conventional environment. Then, we calculated the percentage of similarity comparing the sEMG of stroke survivors with the sEMG signals collected in 4 age-matched healthy subjects, during the same 12 tasks. Results showed that there was an improvement in motor function in all patients (FMA-UE Δ= 7.88 ± 4.82, p= 0.008) but no differences in comparing two types of treatment (p=0.241). Moreover, in all subjects, in sEMG similarity index, there were significant differences only in the task grasping a pencil. Thus, new improvements in similarity index calculation using REMO will be needed for hand motor assessment. In conclusion, muscle synergies analysis may provide new information about neural mechanisms of upper limb and hand motor recovery. Further, future research may investigate the application of muscle synergies in clinical assessment and in controlling new technological solution in neurorehabilitation.File | Dimensione | Formato | |
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