Combining ultrafast ultrasound and high-density EMG to assess local electromechanical muscle dynamics: a feasibility study

Skeletal muscles generate force, enabling movement through a series of fast electro-mechanical activations coordinated by the central nervous system. Understanding the underlying mechanism of such fast muscle dynamics is essential in neuromuscular diagnostics, rehabilitation medicine and sports biomechanics. The unique combination of electromyography (EMG) and ultrafast ultrasound imaging (UUI) provides valuable insights into both electrical and mechanical activity of muscle fibers simultaneously, the excitation-contraction (E-C) coupling. In this feasibility study we propose a novel non-invasive method to simultaneously track the propagation of both electrical and mechanical waves in muscles using high-density electromyography and ultrafast ultrasound imaging (5000 fps). Mechanical waves were extracted from the data through an axial tissue velocity estimator based on one-lag autocorrelation. The E-C coupling in electrically evoked twitch contractions of the Biceps Brachii in healthy participants could successfully be tracked. The excitation wave (i.e. action potential) had a velocity of 3.9±0.5ms-1 and the subsequent mechanical (i.e. contraction) wave had a velocity of 3.5±0.9ms-1. The experiment showed evidence that contracting sarcomeres that were already activated by the action potential (AP) pull on sarcomeres that were not yet reached by the AP, which was corroborated by simulated contractions of a newly developed multisegmental muscle fiber model, consisting of 500 sarcomeres in series. In conclusion, our method can track the electromechanical muscle dynamics with high spatio-temporal resolution. Ultimately, characterizing E-C coupling in patients with neuromuscular diseases (e.g. Duchenne or Becker muscular dystrophy) may assess contraction efficiency, monitor the progression of the disease, and determine the efficacy of new treatment options.ImPhys/Medical ImagingBiomechatronics & Human-Machine Contro

Loss of selective wrist muscle activation in post-stroke patients

Purpose: Loss of selective muscle activation after stroke contributes to impaired arm function, is difficult to quantify and is not systematically assessed yet. The aim of this study was to describe and validate a technique for quantification of selective muscle activation of wrist flexor and extensor muscles in a cohort of post-stroke patients. Patterns of selective muscle activation were compared to healthy volunteers and test-retest reliability was assessed. Materials and methods: Activation Ratios describe selective activation of a muscle during its expected optimal activation as agonist and antagonist. Activation Ratios were calculated from electromyography signals during an isometric maximal torque task in 31 post-stroke patients and 14 healthy volunteers. Participants with insufficient voluntary muscle activation (maximal electromyography signal <3SD higher than baseline) were excluded. Results: Activation Ratios at the wrist were reliably quantified (Intraclass correlation coefficients 0.77–0.78). Activation Ratios were significantly lower in post-stroke patients compared to healthy participants (p < 0.05). Conclusion: Activation Ratios allow for muscle-specific quantification of selective muscle activation at the wrist in post-stroke patients. Loss of selective muscle activation may be a relevant determinant in assigning and evaluating therapy to improve functional outcome.Implications for Rehabilitation Loss of selective muscle activation after stroke contributes to impaired arm function, is difficult to quantify and is not systematically assessed yet. The ability for selective muscle activation is a relevant determinant in assigning and evaluating therapy to improve functional outcome, e.g., botulinum toxin. Activation Ratios allow for reliable and muscle-specific quantification of selective muscle activation in post-stroke patients.Biomechatronics & Human-Machine Contro

Early shortening of wrist flexor muscles coincides with poor recovery after stroke

Background. The mechanism and time course of increased wrist joint stiffness poststroke and clinically observed wrist flexion deformity is still not well understood. The components contributing to increased joint stiffness are of neural reflexive and peripheral tissue origin and quantified by reflexive torque and muscle slack length and stiffness coefficient parameters. Objective. To investigate the time course of the components contributing to wrist joint stiffness during the first 26 weeks poststroke in a group of patients, stratified by prognosis and functional recovery of the upper extremity. Methods. A total of 36 stroke patients were measured on 8 occasions within the first 26 weeks poststroke using ramp-and-hold rotations applied to the wrist joint by a robot manipulator. Neural reflexive and peripheral tissue components were estimated using an electromyography-driven antagonistic wrist model. Outcome was compared between groups cross-sectionally at 26 weeks poststroke and development over time was analyzed longitudinally. Results. At 26 weeks poststroke, patients with poor recovery (Action Research Arm Test [ARAT] ≤9 points) showed a higher predicted reflexive torque of the flexors (P <.001) and reduced predicted slack length (P <.001) indicating shortened muscles contributing to higher peripheral tissue stiffness (P <.001), compared with patients with good recovery (ARAT ≥10 points). Significant differences in peripheral tissue stiffness between groups could be identified around weeks 4 and 5; for neural reflexive stiffness, this was the case around week 12. Conclusions. We found onset of peripheral tissue stiffness to precede neural reflexive stiffness. Temporal identification of components contributing to joint stiffness after stroke may prompt longitudinal interventional studies to further evaluate and eventually prevent these phenomena.Biomechatronics & Human-Machine Contro