Post-stroke trunk motor output was most clearly detected as an upper-tail motor unit discharge-rate difference rather than altered mean firing, with motor unit decomposition serving as a useful physiological reference for trunk motor control after stroke.
Key Findings
Results
Individuals with subacute stroke showed higher 95th percentile motor unit discharge rates in trunk muscles compared to elderly controls during seated postural maintenance.
Mixed-effects models showed a statistically significant difference in 95th percentile discharge rate after stroke (beta = 4.70 Hz, p = 0.037)
Cluster-bootstrap analysis confirmed the finding (p = 0.0098)
Twenty-two motor units from 12 participants with stroke and 14 motor units from 10 elderly participants were analyzed
Mean discharge rate and inter-spike interval variability were not significantly different between groups
Results
EMG envelope power showed frequency-band and group-by-band interaction effects, with the clearest between-group difference observed at the 0.5–5 Hz frequency band.
Surface EMG envelope power was analyzed across multiple frequency bands
Significant frequency-band and group-by-band effects were identified using mixed-effects models
The 0.5–5 Hz band showed the clearest difference between stroke and elderly control groups
This finding provided secondary evidence of altered low-frequency neural modulation after stroke
Results
sEMG-kinematic coherence between lumbar longissimus muscle activity and pelvic motion showed no significant stroke-specific effects.
Coherence between surface EMG and pelvic kinematics was quantified using inertial measurement unit data
Mixed-effects models showed no significant group or interaction effects for sEMG-kinematic coherence
This measure was characterized as showing 'no stroke-specific modulation'
Muscle-motion coupling therefore did not differentiate post-stroke from control trunk motor behavior
Methods
The study examined trunk muscle neural output at three distinct levels: motor unit firing behavior, sEMG envelope power frequency distribution, and low-frequency sEMG-kinematic coherence.
Twenty individuals with subacute stroke and 20 elderly controls participated
High-density sEMG was recorded from the lumbar longissimus muscle
Pelvic motion was measured using an inertial measurement unit
The task involved seated postural maintenance with bilateral arm elevation
Motor unit decomposition from high-density sEMG was used to obtain individual discharge metrics
Conclusions
Motor unit decomposition was identified as a more sensitive physiological tool for detecting post-stroke trunk motor output changes than EMG envelope or muscle-motion coherence measures.
The upper-tail (95th percentile) discharge rate, rather than mean firing rate, was the metric that distinguished stroke from control groups
Authors concluded that 'motor unit decomposition may therefore serve as a useful physiological reference for trunk motor control after stroke'
EMG envelope power provided only 'secondary evidence' of altered low-frequency modulation
The authors noted this finding has implications for neuromodulation technology development targeting trunk dysfunction post-stroke
What This Means
This research suggests that after a stroke, the way the brain controls trunk muscles during sitting tasks is altered in subtle but detectable ways. By using advanced electrode arrays placed on the lower back muscles and analyzing the firing patterns of individual motor units (the basic functional units of muscle control), researchers found that stroke survivors occasionally fired their trunk motor units at unusually high rates compared to healthy older adults, even though the average firing rate was similar between groups. This upper-tail difference in discharge rate was the clearest signal distinguishing the two groups, and it was only detectable through detailed motor unit decomposition rather than simpler EMG measures.
The study also found some differences in low-frequency patterns of muscle electrical activity between stroke survivors and healthy controls, but no differences in how well muscle activity coordinated with pelvic movement. Together, these findings suggest that trunk muscle dysfunction after stroke may be more about occasional bursts of abnormal neural output than a general change in how hard the muscles are working on average.
This research matters because poor trunk control is a major barrier to recovery after stroke and affects independence in daily activities. Current clinical assessments of trunk control are limited, and understanding the underlying neural mechanisms could help develop better targeted therapies, including brain or spinal cord stimulation approaches. The findings suggest that high-density EMG with motor unit decomposition could serve as a more precise physiological tool for characterizing and potentially guiding rehabilitation of trunk control after stroke.
Hanawa H, Hirata K, Miyazawa T. (2026). Motor unit decomposition detects altered trunk neural output during seated postural maintenance after stroke.. Journal of neural engineering. https://doi.org/10.1088/1741-2552/ae9db9