Journal of NeuroEngineering and Rehabilitation最新文献

Background: Brain synergy and redundancy are emerging as pivotal aspects to understand neural functions, providing insights into high-order information that traditional functional connectivity (FC) methods cannot access. Despite their significance, these aspects have not been investigated in Parkinson's disease (PD). This paper advances the understanding of synergy and redundancy by integrating them with dynamic analysis, which is essential in the investigation of PD.

Methods: Dynamic brain synergy and redundancy were developed and quantified by the constructed dynamic information decomposition framework, and was applied to walking-state functional near-infrared spectroscopy (fNIRS) signals of 63 PD patients undergoing dopaminergic treatment and 36 healthy controls.

Results: Dynamic brain synergy was restored to normal levels following dopaminergic treatment. Dynamic FC could not access high-order neural information and had insignificant variations in dopaminergic modulation among PD patients, and dynamic brain redundancy also exhibited insignificant treatment-induced variations.

Conclusion: Dynamic brain synergy offers an advancing perspective on neural dynamics and promises to uncover high-order functional biomarkers for PD early diagnosis and individualized treatment.

Trial registration: This study has been registered in Chinese Clinical Trial Registry (ChiCTR1900022655).

Background: Botulinum toxin type A (BoNT/A) is first-line treatment for muscle spasticity but the dose can be limited by side effects depending on the treated muscle mass and location. Stimulation of peripheral motor nerves upon BoNT/A injection into the innervated muscles may be a technique to increase the BoNT/A effect without increasing the dose. Our goal was to study the augmentation of the BoNT/A effect by transcutaneous electrical (TENS) or magnetic nerve stimulation (MS) in a mouse model.

Methods: The paralytic effect of BoNT/A with or without TENS was evaluated with the mouse digit abduction score (DAS) at 20, 30, and 40 U/kg. The paralytic effect of BoNT/A with or without peripheral MS was evaluated with the mouse DAS at 20 or 30 U/kg.

Results: After 20 U/kg BoNT/A treatment combined with TENS the DAS was higher and showed a longer duration of paralysis than without TENS. After 30 U/kg BoNT/A treatment combined with magnetic stimulation the DAS was higher than without magnetic stimulation.

Conclusion: We established an electrical and a magnetic nerve stimulation protocol combined with BoNT/A treatment in mice. Combination of i.m. BoNT/A injection with TENS or MS demonstrated an enhanced BoNT/A effect as compared to non-stimulated groups. Despite limitations of the magnetic stimulation method in the mouse our data revives the discussion of BoNT/A effect augmentation by stimulating the injected muscles' efferent nerves during the BoNT/A uptake phase.

Background: Prosthetic feet are essential for restoring independent mobility in individuals with lower-limb loss. However, most commercial prosthetic feet rely on elastic elements and rigid, flat soles, limiting adaptability to uneven terrain and compromising user stability. Originally developed for robotic applications, the SoftFoot introduced an adaptive sole architecture inspired by the biomechanics of the human plantar fascia to improve ground conformity and gait stability. Building on this concept, we introduced the SoftFoot Pro at Cybathlon 2024 - a prosthetic counterpart that integrates a compliant adaptive sole with energy storage capabilities at the ankle joint through an agonist-antagonist mechanism. This design emulates the synergistic action of muscles, tendons, and the plantar fascia in the human shank-ankle-foot complex. This study evaluates the kinematic and metabolic performance of the SoftFoot Pro.

Method: During a dedicated pre-competition training session, the official SoftFoot Pro team pilot completed the Cybathlon Leg Race track twice using three prosthetic feet: (i) the Triton foot (energy storage only), (ii) the original SoftFoot (adaptive sole only), and (iii) the SoftFoot Pro. Kinematic and metabolic data were collected using the Xsens MVN Awinda and Cosmed K5 system. The evaluation was complemented by questionnaires assessing locomotor performance, usability, cognitive load, and user experience.

Results: The SoftFoot Pro demonstrated greater ankle mobility than the original SoftFoot and the Triton across various tasks. Stride length and gait velocity were comparable to the Triton and higher than with the original SoftFoot. The SoftFoot Pro revealed the fastest circuit completion time, with a metabolic cost of transport comparable to the Triton and lower than the original SoftFoot. Questionnaires reported higher perceived mobility and lower cognitive and physical effort with the SoftFoot Pro, compared to both the original SoftFoot and the Triton, highlighting its functional and user experience advantages.

Conclusions: This explorative, single-subject study quantitatively evaluated adaptive prosthetic feet in Cybathlon tasks simulating daily activities. Integrating an ankle joint with an agonist-antagonist energy recycling system improved mobility and reduced mental and physical effort, matching the performance of commercial carbon fiber feet while preserving the adaptive sole's advantages. The Cybathlon was the catalyst for advancing the innovation and validation of our adaptive prosthesis.

Background: Mechanically ventilated patients may experience respiratory suffering, which is difficult to assess when verbal communication is impaired. We evaluated the performance of a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) designed to enable self-reporting of dyspnoea in this context.

Methods: Forty-nine healthy volunteers were studied under five respiratory conditions: normal breathing (NB), inspiratory resistive loading (IRL), inspiratory threshold loading (ITL), CO₂ inhalation (CO₂), and a return to NB as wash-out (NBWO). Respiratory discomfort was evaluated using a visual analogue scale (VAS). Two BCIs models were tested: a detection BCI (D-BCI), designed to discriminate between 'breathing is OK' and 'breathing is difficult', and a quantification BCI in the form of a LED-based analogue scale (LAS), composed of five light-emitting diodes. Visual stimuli were delivered at different frequency sets: 12-15 Hz, 15-20 Hz, and 20-30 Hz for the D-BCI; low frequencies (13-17-19-23-29 Hz) and high frequencies (41-43-47-53-59 Hz) for the LAS. Performance was assessed using receiver operating characteristic (ROC) curves; the area under the ROC curve (AUC) was the primary outcome.

Results: Participants reported significant respiratory discomfort during IRL, ITL, and CO₂ conditions in the D-BCI groups, and during ITL and CO₂ in the LAS groups, as reflected by higher dyspnoea VAS scores compared to NB. The best-performing frequency sets were 20-30 Hz for the D-BCI (AUC 0.89 [0.89-0.90]) and low frequencies for the LAS (AUC 0.84 [0.83-0.85]).

Conclusions: This study demonstrates that an SSVEP-based BCI can sucessfully detect and quantify experimentally induced dyspnoea in healthy individuals. Further research is needed to evaluate its clinical applicability for assessing dyspnoea in non-communicative patients.

Post-stroke rehabilitation is a complex process influenced by several neurophysiological factors. The recovery is traditionally predicted based on initial impairment using linear models. The Proportional Recovery Rule (PRR), developed on the Fugl-Meyer scale, has even been proposed as a therapeutic target. In this framework, patients are classified as "fitters" or "non-fitters", though this distinction depends on the methodology used. Additionally, issues like mathematical coupling and ceiling effects on clinical scales could raise concerns about the validity of these models. To overcome these issues, Repeated Spectral Clustering (RSC) was used to identify recovery patterns based on NIHSS. We selected 201 patients from the WAKE-UP trail, all moderately impaired at onset and still impaired at 22-36 h. Clustering was performed using a similarity matrix based on pairwise absolute differences between recovery ratios, calculated from 22-36 h to 90 days post-stroke. Cluster differences were tested with prognostic factors, including lesion volume, side, treatment, and the Heidelberg scale. The PRR was fit to the cohort for comparison with clustering results. The linear fit reproduced findings consistent with the literature, such as a correlation of [Formula: see text] and an average recovery ratio of 70% for the "fitters". RSC grouped patients into six recovery clusters: [Formula: see text] (full recovery), [Formula: see text] (above average), [Formula: see text] and [Formula: see text] (average, PRR-aligned), [Formula: see text] (below average), and [Formula: see text] (deterioration). NIHSS scores in most patients declined non-proportionally. Lesion volume was not significantly different across clusters, while left-sided strokes were higher in low recovery clusters. Patients with a recovery ratio [Formula: see text] within two weeks mostly fell into favorable clusters ([Formula: see text]-[Formula: see text]), covering [Formula: see text] of such cases. The identified clusters provide a refined view of stroke recovery following wake-up stroke. Clustering better captures patient similarities, enabling the assessment of neurophysiological differences between groups and supporting tailored interventions.