Deans' stroke musings: Quantitative Assessment via Multi-Domain Fusion of Muscle Synergy Associated with Upper-Limb Motor Function for Stroke Rehabilitation

Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Friday, December 8, 2023

Quantitative Assessment via Multi-Domain Fusion of Muscle Synergy Associated with Upper-Limb Motor Function for Stroke Rehabilitation

No clue how this is going to get survivors recovered. Great word salad though.

Quantitative Assessment via Multi-Domain Fusion of Muscle Synergy Associated with Upper-Limb Motor Function for Stroke Rehabilitation

Xiao Li, Hong Zeng, Yongqiang Li, Aiguo Song

PMID: 38051628
DOI: 10.1109/TBME.2023.3339634

Abstract

Quantitative assessment of upper limb motor function can assist therapists in providing appropriate rehabilitation strategies, which plays an essential role in post-stroke rehabilitation. Conventionally, the most frequently used assessments are based on clinical scales or kinematic metrics, which rely on subjective scores or may be masked at the kinematic level by compensatory strategies. Recently, muscle synergies which encodes the simplified neuromuscular control strategy deployed by the central nervous system have been gradually used to assess post-stroke impairment. In general, muscle synergies are decomposed into two components: synergy vectors and synergy activation. Synergy vectors represent the relative weighting of each muscle within each synergy, that is muscle coordination; synergy activation represents the recruitment of the muscle synergy over time, that is muscle activation strength. Both the characteristics of synergy vectors and synergy activation are crucial for adequately assessing patients' motor function. Therefore, we integrate the spatial domain and temporal domain features extracted from synergy vectors and synergy activation for constructing a multi-domain assessment system based on Random Forest classifier, which may provide great qualitative classification accuracy. Furthermore, a novel functional score is generated from the probabilities belonging to the pathological group. Finally, we conduct a study with ten healthy subjects and ten post-stroke patients to verify the effectiveness of the proposed method. The experimental results show that the classification accuracy was enhanced to 98.56% by fusing the characteristics derived from different domains, which was higher than that based on spatial domain (94.90%) and temporal domain (91.08%), respectively. Furthermore, the assessment score generated by multi-domain fusion framework exhibited a significant correlation with the clinical score. These promising results show the potential of applying the proposed method to clinical assessments for post-stroke patients.

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