Journal of NeuroEngineering and Rehabilitation最新文献

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.

Background: Ankle-foot orthoses (AFOs) are commonly prescribed to improve gait after stroke; however, their effectiveness varies among individuals. Limited evidence exists on how AFOs specifically influence ground reaction force (GRF) patterns during gait. This study investigated how baseline anterior-posterior GRF (A-P GRF) patterns, reflecting braking and propulsive abilities, influence the immediate effects of distinct AFO designs.

Methods: This retrospective cross-sectional study included 66 community-dwelling individuals with hemiparesis who underwent gait analysis under three conditions: without AFO (noAFO), with oil-damper AFO (odAFO), and with plastic AFO (pAFO). A-P GRF impulse and mean were assessed across four stance phase bins (Bin 1: initial double support following heel contact, Bin 2: first half of the single support, Bin 3: second half of the single support, Bin 4: terminal double support preceding toe-off), alongside gait speed and limb kinematics. Hierarchical cluster analysis identified distinct A-P GRF patterns based on the impulse from Bins 1-4 during the baseline noAFO condition; immediate AFO effects were compared across clusters.

Results: Both AFO types significantly but modestly increased gait speed overall, with variable responses across clusters. Three baseline A-P GRF patterns were identified: favorable propulsion (Cluster 1, n = 19), moderate impairment (Cluster 2, n = 27), and poor propulsion with excessive braking (Cluster 3, n = 20). Participants with the poorest gait function (Cluster 3) demonstrated the most significant improvements in gait speed with both AFO types (odAFO: p < 0.001; pAFO: p = 0.006), through different biomechanical mechanisms: odAFO improved propulsive forces in Bin 4 (impulse: p < 0.001; mean: p = 0.012), whereas pAFO reduced excessive braking forces in Bin 1 (impulse: p < 0.001; mean: p = 0.048). Participants with favorable baseline A-P GRF patterns showed minimal immediate effects.

Conclusion: AFO effectiveness depends on baseline A-P GRF patterns, with the greatest benefits observed in participants exhibiting poor propulsive forces and excessive braking, through different biomechanical mechanisms. These findings highlight the importance of considering individual A-P GRF patterns when prescribing orthotic interventions in post-stroke rehabilitation.

Background: Digital health technologies (DHTs) can quantify movements in daily routines but rely heavily on participant adherence over prolonged wear times.

Methods: We analyzed accelerometry data from wrist-worn devices during short at-home episodes of prescribed exercises performed by 329 individuals living with amyotrophic lateral sclerosis (ALS) in a longitudinal study. We developed an automated and interpretable signal processing method to estimate four metrics describing exercise repetitions, i.e., their count, duration, intensity, and similarity. We examined their associations with time elapsed from enrollment and ALS Functional Rating Scale-Revised (ALSFRS-R) using linear mixed effect models. We also compared them with previously validated free-living metrics that require substantial sensor wear-time. Finally, we studied how many repetitions are sufficient to determine participants' upper limb functioning.

Results: Three out of four exercise metrics (all but count) demonstrated significant association with ALSFRS-R outcomes. The duration of exercise repetitions increased, while intensity and similarity of movement decreased over time (all p-value < 0.001), indicating longer but less vigorous and less consistent upper limb movements over time. Exercise intensity was determined as the most robust exercise-based predictor of changes in upper limb function, and it was comparable to free-living metrics, which required at 21 h of sensor wear time (R-squared 0.899 vs. 0.860, respectively). Sensitivity analysis indicated that as few as five exercise repetitions were sufficient to yield statistically significant associations with ALSFRS-R.

Conclusions: These results suggest that prescribed exercise can effectively quantify upper limb function and track longitudinal decline comparably to free-living observation. The proposed method may serve as an alternative that decreases participation burden, increases study adherence, and extends diagnostic accessibility.