Journal of NeuroEngineering and Rehabilitation最新文献

Background: Clinical gait analysis plays a pivotal role in diagnosing and treating walking impairments. Inertial measurement units (IMUs) offer a low-cost, portable, and practical alternative to traditional gait analysis equipment, making these techniques more accessible beyond specialized clinics. Previous work and algorithms developed for specific clinical populations, like in individuals with Parkinson's disease, often do not translate effectively to other groups, such as stroke survivors, who exhibit significant variability in their gait patterns. The Salarian gait segmentation algorithm (SGSA) has demonstrated the potential to detect gait events and subsequently estimate clinical measures of gait speed, stride time, and other temporal parameters using two leg-worn IMUs in individuals with Parkinson's disease. However, the distinct gait impairments in stroke survivors, including hemiparesis, spasticity, and muscle weakness, can interfere with SGSA performance. Thus, the objective of this study was to develop and test an enhanced gait segmentation algorithm (EGSA) to capture temporal gait parameters in individuals with stroke.

Methods: Forty-one individuals with stroke were recruited from two acute rehabilitation settings and completed brief walking bouts with two leg-worn IMUs. We compared foot-off (FO), foot contact (FC), and temporal gait parameters computed from the SGSA and EGSA against ground truth measurements from an instrumented mat.

Results: The EGSA demonstrated greater accuracy than the SGSA when detecting gait events within one second, for both FO (96% vs. 90%) and FC (94% vs. 91%). The EGSA also demonstrated lower error than the SGSA when detecting paretic FC, and FO events in slow, asymmetrical, and non-paretic footfalls. Temporal gait parameters from the EGSA had high reliability (ICC > 0.90) for stride time, step time, stance time, and double support time across gait speeds and levels of asymmetry.

Conclusion: This approach has the potential to enhance the accuracy and validity of IMU-based gait analysis in individuals with stroke, thereby enhancing clinicians' ability to monitor and intervene for gait impairments in a rehabilitation setting and beyond.

Background: Wearable technology offers objective and remote quantification of disease progression in neurological diseases such as amyotrophic lateral sclerosis (ALS). Large population studies are needed to determine generalization and reproducibility of findings from pilot studies.

Methods: A large cohort of patients with ALS (N = 202) wore wearable accelerometers on their dominant and non-dominant wrists for a week every two to four weeks and self-entered the ALS Functional Rating Scale-Revised (ALSFRS-RSE) in similar time intervals. Wearable device data were processed to quantify digital biomarkers on four upper limb movements: flexion, extension, supination, and pronation using previously developed and validated open-source methodology. In this study, we determined the association between digital biomarkers and disease progression, studied the impact of study design in terms of required sensor wear-time and sensor position, and determined the impact of self-reported disease onset location on upper limb movements.

Results: The main investigation considered data from a sensor placed on the non-dominant wrist. Participants with higher ALSFRS-RSE scores performed more frequent and faster upper limb movements compared to participants with more advanced disease status. Digital biomarkers exhibited statistically significant change over time while their rate of change was more profound compared to survey responses. Using data from the dominant wrist and changing data inclusion criteria did not alter our findings. ALS disease onset location significantly impacted use of upper limbs. Results presented here were comparable to an earlier study on twenty patients with ALS.

Discussion: Digital health technologies provide sensitive and objective means to quantify ALS disease progression. Interpretable approaches, such as the one used in this paper, can improve patient evaluation and hasten therapeutic development.

Background: This study aimed to investigate the therapeutic effects of vibration therapy for improving upper extremity motor impairment, function, and disability recovery in people with stroke.

Design: We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. PubMed, EMBASE, the Cochrane Library Database, Physiotherapy Evidence Database (PEDro), China Knowledge Resource Integrated Database, and Google Scholar were searched from inception to May 31, 2024. Randomized controlled trials (RCTs) that evaluated the effects of vibration therapy on upper extremity motor impairment, function, and disability recovery post-stroke were analyzed.

Setting and participants: Participants with a diagnosis of stroke with hemiplegia (or hemiparesis) were recruited.

Methods: Methodological quality assessment was performed using the PEDro quality score. Upper extremity motor impairment, function, and disability were the primary outcomes. Upper extremity motor impairment was measured using the Fugl-Meyer Assessment scale and other methods. Upper extremity functions were evaluated using the Wolf Motor Function test or other tools assessing manipulative activities. Disability was assessed using the Functional Independence Measure, Barthel index, and other methods.

Results: Overall, 30 RCTs including 1621 people with stroke were selected. Compared with the control, vibration therapy exerted significant effects on upper extremity motor impairment [standardized mean difference (SMD) = 1.19; p < 0.00001)], function (SMD = 0.62; p < 0.00001), and disability recovery (SMD = 1.01; p < 0.00001). The subgroup analysis revealed that focal vibration therapy (SMD = 2.14) had favorable effects on disability recovery compared with whole-body vibration therapy (SMD = 2.0). Interventions lasting 4-8 weeks showed significant improvements in motor impairment (SMD = 1.19), motor function (SMD = 0.57), and disability (SMD = 0.84); additionally, the effects of vibration therapy combined with conventional rehabilitation (SMD = 1.03) were superior to those of vibration therapy alone (SMD = 0.21).

Conclusions: Vibration therapy may be a reliable rehabilitation program to improve upper extremity motor functions and disabilities. Furthermore, vibration therapy should be performed at the earliest possibility after stroke for at least 4-8 weeks. Trial registration The protocol of this study was registered with PROSPERO (Registration number: CRD42022301119).

Background: An age-related decline in motor flexibility, which is the ability to synergistically control the degrees of freedom of the body to ensure stable performance of a task, is a factor that contributes to falls. We investigated whether providing environmental constraints to increase the movement repertoire (i.e., the motor solution that works to achieve one's goal), in combination with aiming at precise control of the performance, would be effective for improving motor flexibility, and whether the effect on the leading limb would extend to the trailing limb.

Methods: Fifteen older adults (75.1 ± 6.2 years and 14 younger adults (34.6 ± 5.0 years) performed under three walking conditions: walking normally and crossing the obstacle (normal), walking and crossing the obstacle with constraints of foot placement after stepping over it (constrained), and walking and crossing the obstacle with constraints as in the constrained condition, in addition to aiming for maintaining a constant clearance height at the moment of obstacle crossing (precision). An uncontrolled manifold analysis was used to quantify motor flexibility as the synergy index. The foot height at the moment of obstacle crossing was used as the performance variable and seven segmental angles were used as the elemental variables. A higher synergy index indicates greater motor flexibility.

Results: For the leading limb, the synergy index was significantly higher under the precision condition than those under the other conditions. This suggests that not only providing environmental constraints but also keeping constant the performance variable is critical to improving motor flexibility. Moreover, the effects of an increase in the synergy index in the leading limb extended to the trailing limb.

Conclusions: Providing environmental constraints to increase the movement repertoire while also aiming for precision in the performance variable was an effective method of improving motor flexibility during obstacle crossing for older adults.

Background: Compensatory movements frequently emerge in the process of motor recovery after a stroke. Given their potential for unfavorable long-term effects, it is crucial to assess and document compensatory movements throughout rehabilitation. However, clinically applicable assessment tools are currently limited. Deep learning methods have shown promising potential for assessing movement quality and addressing this gap. A crucial prerequisite for developing an accurate measurement tool is ensuring reliability in assessing compensatory movements, which is essential for establishing a valid ground truth.

Objective: The study aimed to assess inter- and intra-rater reliability of occupational and physical therapists' visual assessment of compensatory movements based on video analysis.

Methods: Experienced therapists evaluated video-recorded performances of a standardized drinking task through an online labeling system. The standardized drinking task was performed by seven individuals with mild to moderate upper limb motor impairments after a stroke. The therapists rated compensatory movements in predetermined body segments and movement phases using a slider with a continuous scale ranging from 0 (no compensation) to 100 (maximum compensation). The collected data were analyzed using a generalized-linear mixed effects model with zero-inflated beta regression to estimate variance components. Intraclass correlation coefficients (ICC) were calculated to assess inter- and intra-rater reliability.

Results: Twenty-two therapists participated in this study. Inter-rater reliability was good for the phases of reaching, drinking, and returning (ICC ≥ .0.75), and moderate for both phases of transporting. Intra-rater reliability was excellent for the drinking phase (ICC > 0.9) and moderate to good for the phases of reaching, transporting, and returning of our cohort. ICCs for smoothness and interjoint coordination were poor for both inter- and intra-rater reliability. The data analysis unveiled a wide range of credible intervals for the ICCs across all domains examined in this study.

Conclusions: While this study shows promising inter- and intra-rater reliability for the drinking phases within our sample, the wide credible intervals raise the possibility that these results may have occurred by chance. Consequently, we cannot recommend the establishment of a ground truth for the automatic assessment of compensatory movements during a drinking task based on therapists' ratings alone.

Background: Robot-Assisted Gait Rehabilitation (RAGR) is an established clinical practice to encourage neuroplasticity in patients with neuromotor disorders. Nevertheless, tasks repetition imposed by robots may induce boredom, affecting clinical outcomes. Thus, quantitative assessment of engagement towards rehabilitation using physiological data and subjective evaluations is increasingly becoming vital. This study aimed at methodologically exploring the performance of artificial intelligence (AI) algorithms applied to structured datasets made of heart rate variability (HRV) and electrodermal activity (EDA) features to predict the level of patient engagement during RAGR.

Methods: The study recruited 46 subjects (38 underage, 10.3 ± 4.0 years old; 8 adults, 43.0 ± 19.0 years old) with neuromotor impairments, who underwent 15 to 20 RAGR sessions with Lokomat. During 2 or 3 of these sessions, ad hoc questionnaires were administered to both patients and therapists to investigate their perception of a patient's engagement state. Their outcomes were used to build two engagement classification targets: self-perceived and therapist-perceived, both composed of three levels: "Underchallenged", "Minimally Challenged", and "Challenged". Patient's HRV and EDA physiological signals were processed from raw data collected with the Empatica E4 wristband, and 33 features were extracted from the conditioned signals. Performance outcomes of five different AI classifiers were compared for both classification targets. Nested k-fold cross-validation was used to deal with model selection and optimization. Finally, the effects on classifiers performance of three dataset preparation techniques, such as unimodal or bimodal approach, feature reduction, and data augmentation, were also tested.

Results: The study found that combining HRV and EDA features into a comprehensive dataset improved the synergistic representation of engagement compared to unimodal datasets. Additionally, feature reduction did not yield any advantages, while data augmentation consistently enhanced classifiers performance. Support Vector Machine and Extreme Gradient Boosting models were found to be the most effective architectures for predicting self-perceived engagement and therapist-perceived engagement, with a macro-averaged F1 score of 95.6% and 95.4%, respectively.

Conclusion: The study displayed the effectiveness of psychophysiology-based AI models in predicting rehabilitation engagement, thus promoting their practical application for personalized care and improved clinical health outcomes.

Background: In the context of post-traumatic hand rehabilitation, stiffness of the hand joints limits the range of motion (ROM), grip strength, and the possibility of performing simple grasps. Robotic rehabilitation has been widely adopted for hand treatment with neurological patients, but its application in the orthopaedic scenario remains limited. In this paper, a pilot study targeting this population is presented, where the rehabilitation is performed using a powered finger exoskeleton, namely I-Phlex. The device aims to mobilize the metacarpal-phalangeal joint (MCP) in flexion-extension movements. The objective of the study was to verify the short-term efficacy, experience of use, and safety of I-Phlex in a clinical setting. As a secondary objective, the study verified the device's capability to measure clinically relevant variables.

Methods: Six subjects with trauma-related illnesses of the right hand took part in the experiment. Passive and active range of motion (PROM and AROM) were recorded at the beginning and the end of the session by the therapist and by the exoskeleton. Experience of use was assessed through ad-hoc questionnaires and a numerical pain rate scale (NPRS). Safety was assessed by computing the number of adverse events during the operation.

Results: Median increases in the PROM and AROM of 5.88% and 11.11% respectively were recorded among subjects. The questionnaires reported a median score of 93.83; IQR (85.01-100) and 80.00; IQR (79.79-93.75) respectively. No increase in the median NPRS was recorded among subjects between pre-and post-treatment. No major adverse event or injury to the patients was recorded. Only one malfunction was reported due to the brake of a transmission cable, but the patient reported no injury or discomfort. No statistical significance was observed between the ROM measurement recorded using the exoskeleton and the ones taken by the therapist using the goniometer.

Conclusions: The device and related rehabilitation exercises can be successfully used in the clinical rehabilitation of the MCP joint. The device measurements are in line with the goniometer assessment from the therapist. Future studies will aim to reinforce the results obtained, introducing a control group to conclude on the specific contribution of the technology compared to conventional therapy.

Trial registration: Hand Motor Rehabilitation Using a Wearable Robotic Device (WRL HX MCP), Clinicaltrials.gov ID NCT05155670, Registration date 13 December 2021, URL https://clinicaltrials.gov/ct2/show/NCT05155670 .

Background: The prefrontal cortex (PFC) is an important node for action planning in the frontoparietal reaching network but its role in reaching in children with cerebral palsy (CP) is unexplored. This case-control study combines a robotic task with functional near-infrared spectroscopy (fNIRS) to concurrently assess reaching accuracy and PFC activity during time-constrained, goal-directed reaching in children with CP. We hypothesized that reaching accuracy in children with CP would be lower than in typically developing children and would be related to PFC activity.

Methods: Fourteen children with spastic CP (5-11 y; Manual Ability Classification System level I-II) and 14 age-, sex- and arm dominance-matched typically developing controls performed seated uniplanar reaches with a robotic arm (KINARM End-Point Lab) to hit visual targets projected onto a screen. Four blocks of 10 reaching trials each were performed for each arm. Time constraint (high, low) was varied across blocks by changing the time participants had to hit the target.

Results: Children with CP displayed lower reaching accuracy compared to controls, with greater deficits observed in the non-preferred arm (d = 1.916, p < 0.001) than the preferred arm (d = 1.033, p = 0.011). Inter-limb differences in accuracy were observed only in children with CP (d = 0.839, p < 0.001). PFC activity differed across groups during preferred arm reaching, with PFC deactivation observed in children with CP under high time constraints compared to PFC activation in controls (d = 1.086, p = 0.006). Children with CP also exhibited lower PFC activity under high time constraint compared to low time constraint in the preferred arm (d = 0.702, p = 0.001). PFC activity was positively related to reaching accuracy across time constraints in both arms in children with CP, but not in controls.

Conclusions: Contrasting patterns of PFC activity observed in children with CP compared to age- and sex-matched controls during a robotic reaching task lends support for the concurrent use of fNIRS and robotics to assess goal-directed reaching in CP.

Trial registration: Data collected as part of a larger randomized controlled trial; https://clinicaltrials.gov/ct2/show/NCT03484078.

Background: Impaired balance and gait in stroke survivors are associated with decreased functional independence. This study aimed to evaluate the effectiveness of unilateral lower-limb exoskeleton robot-assisted overground gait training compared with conventional treatment and to explore the relationship between neuroplastic changes and motor function recovery in subacute stroke patients.

Methods: In this randomized, single-blind clinical trial, 40 patients with subacute stroke were recruited and randomly assigned to either a robot-assisted training (RT) group or a conventional training (CT) group. All outcome measures were assessed at the enrollment baseline (T0), 2nd week (T1) and 4th week (T2) of the treatment. The primary outcome was the between-group difference in the change in the Berg balance scale (BBS) score from baseline to T2. The secondary measures included longitudinal changes in the Fugl-Meyer assessment of the lower limb (FMA-LE), modified Barthel index (mBI), functional ambulation category (FAC), and locomotion assessment with gait analysis. In addition, the cortical activation pattern related to robot-assisted training was measured before and after intervention via functional near-infrared spectroscopy.

Results: A total of 30 patients with complete data were included in this study. Clinical outcomes improved after 4 weeks of training in both groups, with significantly better BBS (F = 6.341, p = 0.018, partial η2 = 0.185), FMA-LE (F = 5.979, p = 0.021, partial η2 = 0.176), FAC (F = 7.692, p = 0.010, partial η2 = 0.216), and mBI scores (F = 7.255, p = 0.042, partial η2 = 0.140) in the RT group than in the CT group. Both groups showed significant improvement in gait speed and stride cadence on the locomotion assessment. Only the RT group presented a significantly increased stride length (F = 4.913, p = 0.015, partial η2 = 0.267), support phase (F = 5.335, p = 0.011, partial η2 = 0.283), and toe-off angle (F = 3.829, p = 0.035, partial η2 = 0.228) on the affected side after the intervention. The RT group also showed increased neural activity response over the ipsilesional motor area and bilateral prefrontal cortex during robot-assisted weight-shift and gait training following 4 weeks of treatment.

Conclusions: Overground gait training with a unilateral exoskeleton robot showed improvements in balance and gait functions, resulting in better gait patterns and increased gait stability for stroke patients. The increased cortical response related to the ipsilesional motor areas and their related functional network is crucial in the rehabilitation of lower limb gait in post-stroke patients.