Journal of NeuroEngineering and Rehabilitation最新文献

Background: Following upper limb amputation, surgeries such as arm transplantation or replantation might be an option to restore function. After such surgeries, rehabilitation of the arm is needed. However, conventional rehabilitation is dependent on some volitional movement of the arm. If there is no or minimal movement of the arm, conventional rehabilitation might not be successful. The purpose of this study is to evaluate a novel combination of myoelectric motor execution (MME) and sensory training (ST) to reduce pain and improve upper limb function in a person with a highly impaired replanted arm.

Methods: The participant, a 72-year-old male, had his right arm replanted after a traumatic accident. No functional recovery was achieved following conventional rehabilitation and chronic neuropathic pain developed post-surgery. The participant then received 18 sessions of MME in which intended movements were decoded from the replanted arm's myoelectric signals using machine learning and real-time feedback was provided on a screen. Nine sessions included ST using tactile grids where the participant discriminated different sensations.

Results: The participant regained active extension of the thumb (4 degrees) and regained active wrist movement (flex: 6 degrees, extend: 10 degrees), both of which had no active movement prior the MME interventions. He also perceived an increase in sensation in the thumb and fingers. Pain levels fluctuated throughout the study and no consistent change could be concluded.

Conclusion: MME is a novel virtual rehabilitation treatment which provides feedback using virtual limbs and serious games. MME combined with ST is a potential rehabilitation treatment for individuals with highly impaired arms and hands which might ameliorate chronic neuropathic pain.

Background: Kilohertz high-frequency alternating current (KHFAC) stimulation has demonstrated to induce rapid and reversible nerve blocks without causing nerve damage. Previous studies have explored frequency-dependent effects using a transcutaneous approach in humans from 5 to 20 kHz. Nevertheless, its application in humans is limited by the lack of stimulators approved for frequencies above 20 kHz. Therefore, this study aimed to assess the effects and safety of transcutaneous KHFAC stimulation using a novel prototype stimulator, comparing interventions at 30, 40, and 50 kHz to sham stimulation on experimental pain, sensory, motor, and neurophysiological outcomes.

Methods: A randomized, double-blind, sham-controlled crossover study involving 34 healthy participants was conducted. Four interventions (30, 40, 50 kHz, and sham) were administered, and stimulation was applied for 20 min to the median nerve of the non-dominant hand. A prototype stimulator capable of delivering frequencies between 1 and 50 kHz, with a maximum peak-to-peak output current intensity of 400 mA was designed. The intensity applied during the stimulation was below motor threshold, evoking a 'strong but comfortable' tingling sensation. Primary outcomes included heat pain threshold (HPT), pressure pain threshold (PPT), and adverse effects. The secondary outcomes included static two-point discrimination sensitivity, isometric pinch strength, and median sensory nerve action potential (SNAP).

Results: Compared with the sham stimulation, all the active interventions exhibited a significantly greater increase in the PPT during and immediately after the stimulation, while only a significant increase was observed at 40 kHz (4.1 N/cm²; 95%CI 0.3 to 7.9) at 15 min post-intervention. Compared to sham stimulation, the 40 kHz intervention had a significantly greater effect on the HPT at all time points, with the greatest difference (1.4 °C; 0.6 to 2.1) occurring immediately post-intervention. Adverse effects during active interventions included petechiae, erythema, and itching, which resolved at 24 h post-intervention. For secondary outcomes, only a significant reduction in the median SNAP velocity was observed in the sham stimulation group compared to the 50 kHz group.

Conclusions: Active KHFAC stimulation, particularly at 40 kHz, delivered through a novel stimulator, effectively increased the PPT and HPT without affecting tactile or motor outcomes, inducing mild skin-related adverse effects. These findings have potential implications for people with pain-related pathologies.

Trial registration: NCT05230836.

Background and purpose: Working memory is critical for individuals and has been found to be improved by electrical stimulation of the left dorsolateral prefrontal cortex (DLPFC). However, the effects of different types of transcranial electrical stimulation on working memory are controversial, and the underlying mechanism remains uncertain. In this study, high-definition transcranial direct current stimulation (HD-tDCS) and high-definition transcranial random noise stimulation (HD-tRNS) were applied to the DLPFC to observe the different effects on visual working memory (VWM). The aim was to explore the causal relationship between the electrical activity of the DLPFC and the posterior parietal cortex (PPC) electrical activity and the contralateral delayed activity (CDA).

Methods: Thirty-three healthy subjects received HD-tDCS, HD-tRNS and sham stimulation in a random order. Stimulation was applied to the left DLPFC for 20 min. The subjects underwent a color change-detection task as our VWM task and an auditory digit span test (DST) immediately after stimulation. Event-related potential (ERP) data were collected during the VWM task.

Results: The results revealed significant differences between the different types of HD-tES. There was a remarkable increase in VWM capacity following HD-tDCS compared with both HD-tRNS (p_a = 0.038) and sham stimulation (p_a = 0.038). Additionally, the CDA from the PPC differed after stimulation of the DLPFC. Both HD-tDCS and HD-tRNS expanded the maximum CDA amplitude from set size of 4 to 6, whereas after sham stimulation, the maximum CDA was maintained at a set size of 4. Compared with the sham condition, only HD-tDCS induced a noteworthy increase in CDA amplitude (p_a = 0.012). Notably, a significant correlation emerged between the mean CDA amplitude and VWM capacity (p < 0.001, r = - 0.402).

Conclusion: These findings underscore the ability of HD-tDCS to target the DLPFC to augment working memory capacity while concurrently amplifying CDA amplitudes in the PPC through the frontoparietal network. Trial registration ChiCTR2300074898.

Understanding the psychophysiological state during robot-aided rehabilitation is crucial for assessing the patient experience during treatments. This paper introduces a psychophysiological estimation approach using a Fuzzy Logic inference model to assess patients' perception of robots during upper-limb robot-aided rehabilitation sessions. The patients were asked to perform nine cycles of 3D point-to-point trajectories toward different targets at varying heights with the assistance of an anthropomorphic robotic arm (i.e. KUKA LWR 4+). Physiological parameters, including galvanic skin response, heart rate, and respiration rate, were monitored across ten out of forty daily sessions. This data enabled the construction of an inference model to estimate patients' perception states. Results expressed in terms of correlation coefficients between the patient state and the increasing number of sessions. Correlation coefficients showed statistically significant strong associations: a state of heightened engagement (formerly described as "Excited") had $\rho =-0.73$ (p-value=0.01), and a more calm and resting state (namely "Relaxed" state) had $\rho =0.70$ (p-value=0.02) with the number of sessions completed. All patients had positive interaction with the robot, initially expressing curiosity and interest that gradually shifted to a more "Relaxed" state over time.

Background: Mild cognitive impairment (MCI) may lead to difficulty maintaining postural stability and balance during locomotion. This heightened susceptibility to falls is particularly evident during tasks such as obstacle negotiation, which demands efficient motor planning and reallocation of attentional resources. This study proposed a multi-objective optimal control (MOOC) technique to assess the changes in motor control strategies during obstacle negotiation in older people affected by amnestic MCI.

Methods: Motion data from 12 older adults with MCI and 12 controls when crossing obstacles were measured using a motion capture system, and used to obtain the control strategy of obstacle-crossing as the best compromise between the conflicting objectives of the MOOC problem, i.e., minimising mechanical energy expenditure and maximising foot-obstacle clearance. Comparisons of the weighting sets between groups and obstacle heights were performed using a two-way analysis of variance with a significance level of 0.05.

Results: Compared to the controls, the MCI group showed significantly lower best-compromise weightings for mechanical energy expenditure but greater best-compromise weightings for both heel- and toe-obstacle clearances. This altered strategy involved a trade-off, prioritising maximising foot-obstacle clearance at the expense of increased mechanical energy expenditure. The MCI group could successfully navigate obstacles with a normal foot-obstacle clearance but at the cost of higher mechanical energy expenditure.

Conclusions: MCI alters the best-compromise strategy between minimising mechanical energy expenditure and maximising foot-obstacle clearances for obstacle-crossing in older people. These findings provide valuable insights into how MCI impacts motor tasks and offer potential strategies for mitigating fall risks in individuals with MCI. Moreover, this approach could serve as an assessment tool for early diagnosis and a more precise evaluation of disease progression. It may also have applications for individuals with impairments in other cognitive domains.

The study examined whether lateral perturbation training could improve stepping performance and balance in individuals post-stroke. Thirty-one participants with hemiparesis were randomly allocated to PERT (external perturbation) or VOL (voluntary stepping) step training. The PERT and VOL group consisted of 80 step trials predominantly in the lateral direction, with a small proportion of steps in the anterior/posterior direction. Outcome measures based on step type (medial and lateral) included step initiation time, step length, step clearance, step velocity during an induced waist pull perturbation and voluntary step, and clinical balance assessments. The PERT group initiated a lateral step faster with the non-paretic leg during the induced waist pull perturbation step (P = 0.044) than the VOL group after training. Both groups improved the non-paretic step length and step velocity during lateral steps. During the voluntary steps, the PERT group significantly initiated a voluntary step faster. No significant changes were observed in the paretic leg. Both groups significantly improved on the Community Balance & Mobility Scale and Activities Specific Balance Confidence Scale. Overall, we demonstrated that an exercise to improve stepping performance with external perturbations might provide more benefits in protective stepping responses than training with voluntary steps for individuals with a stroke.

Background: Restriction of movement at a joint due to disease or dysfunction can alter the range of motion (ROM) at other joints due to joint interactions. In this paper, we quantify the extent to which joint restrictions impact upper limb joint movements by conducting a disability simulation study that used wearable inertial sensors for three-dimensional (3D) motion capture.

Methods: We employed the Wearable Inertial Sensors for Exergames (WISE) system for assessing the ROM at the shoulder (flexion-extension, abduction-adduction, and internal-external rotation), elbow (flexion-extension), and forearm (pronation-supination). We recruited 20 healthy individuals to first perform instructed shoulder, elbow, and forearm movements without any external restrictions, and then perform the same movements with restriction braces placed to limit movement at the shoulder, elbow, and forearm, separately, to simulate disability. To quantify the extent to which a restriction at a non-instructed joint affected movement at an instructed joint, we computed average percentage reduction in ROM in the restricted versus unrestricted conditions. Moreover, we performed analysis of variance and post hoc Tukey tests (q statistic) to determine the statistical significance (p < 0.05 denoted using ^*) of the differences in ROM of an instructed joint in the unrestricted versus restricted conditions.

Results: Restricting movement at the shoulder led to a large reduction in the average ROM for elbow flexion-extension (21.93%, q = 9.34^*) and restricting elbow movement significantly reduced the average ROM for shoulder flexion-extension (17.77%, q = 8.05^*), shoulder abduction-adduction (19.80%, q = 7.60^*), and forearm pronation-supination (14.04%, q = 4.96^*). Finally, restricting the forearm significantly reduced the average ROM for shoulder internal-external rotation (16.71%, q = 3.81^*) and elbow flexion-extension (10.01%, q = 4.27^*).

Conclusions: Joint interactions across non-instructed joints can reduce the ROM of instructed movements. Assessment of ROM in the real-world using 3D motion capture, for example using the WISE system, can aid in understanding movement limitations, informing interventions, and monitoring progress with rehabilitation.

Background: Recently, magnetic and inertial measurement units (MIMU) based systems have been applied in the spine mobility assessment; this evaluation is essential in the clinical practice for diagnosis and treatment evaluation. The available systems are limited in the number of sensors, and neither develops a methodology for the correct placement of the sensors, seeking the relevant mobility information of the spine.

Methods: This work presents a methodology for analyzing a system consisting of sixteen MIMUs to reduce the amount of information and obtain an optimal configuration that allows distinguishing between different body postures in a movement. Four machine learning algorithms were trained and assessed using data from the range of motion in three movements (Mov.1-Anterior hip flexion; Mov.2-Lateral trunk flexion; Mov.3-Axial trunk rotation) obtained from 12 patients with Ankylosing Spondylitis.

Results: The methodology identified the optimal minimal configuration for different movements. The configuration showed good accuracy in discriminating between different body postures. Specifically, it had an accuracy of 0.963 ± 0.021 for detecting when the subject is upright or bending in Mov.1, 0.944 ± 0.038 for identifying when the subject is flexed to the left or right in Mov.2, and 0.852 ± 0.097 for recognizing when the subject is rotated to the right or left in Mov.3.

Conclusions: Our results indicate that the methodology developed results in a feasible configuration for practical clinical studies and paves the way for designing specific IMU-based assessment instruments.

Trial registration: Study approved by the Local Ethics Committee of the General Hospital of Mexico "Dr. Eduardo Liceaga" (protocol code DI/03/17/471).

Background: Physical exercise is an important method for both the physical and mental health of the senior population. However, excessive exertion can lead to increased risks of falls, severe injuries, and diminished quality of life. Therefore, simple and effective methods for fatigue monitoring during exercise are highly desirable, particularly in community settings. The purpose of this study was to explore the possibility of real-time detection of exercise-induced fatigue using surface Electromyogram (sEMG) features, including the kurtosis and skewness of the Probability Density Function (PDF) in the community settings to solve the issues of low sensitivity and high computational complexity of commonly used sEMG features.

Methods: sEMG signals from six forearm muscles were recorded during hand grip tasks at 20% maximal voluntary contraction (MVC) task-to-failure contractions from 30 healthy community-dwelling elders at their respective community centers. PDF shape features of the sEMG, namely kurtosis and skewness, were computed from 25 s of non-fatigue stable phase and 25 s of fatigue data for comparison. Statistical tests were conducted to compare and test for the significance of these features. We further proposed a novel fatigue indicator, Temporal-Mean-Kurtosis (TMK) of channel-averaged kurtosis, to detect fatigue with relatively low computational complexity and adequate sensitivity in community settings. ANOVA and post-hoc analyses were performed to examine the performance of TMK.

Results: Statistically significant differences were found between the non-fatigue period and the fatigue period for both kurtosis and skewness, with increasing values when approaching fatigue. TMK was shown to be sensitive in detecting fatigue with respect to time with lower computational complexity than the Sample Entropy.

Conclusion: This study investigated PDF shape features of sEMG signals during a handgrip exercise to identify muscle fatigue in older adults in community experiments. Results revealed significant changes in kurtosis upon fatigue, indicating that PDF shape features were suitable convenient detectors of muscle fatigue in community experiments. The proposed indicator, TMK, showed potential sensitivity in tracking muscle fatigue over time in community-based settings with limited computational complexity, highlighting the promise of sEMG's PDF features in detecting muscle fatigue among the elderly.

Purpose: Virtual Reality (VR) has proven to be an effective tool for motor (re)learning. Furthermore, with the current commercialization of low-cost head-mounted displays (HMDs), immersive virtual reality (IVR) has become a viable rehabilitation tool. Nonetheless, it is still an open question how immersive virtual environments should be designed to enhance motor learning, especially to support the learning of complex motor tasks. An example of such a complex task is triggering steps while wearing lower-limb exoskeletons as it requires the learning of several sub-tasks, e.g., shifting the weight from one leg to the other, keeping the trunk upright, and initiating steps. This study aims to find the necessary elements in VR to promote motor learning of complex virtual gait tasks.

Methods: In this study, we developed an HMD-IVR-based system for training to control wearable lower-limb exoskeletons for people with sensorimotor disorders. The system simulates a virtual walking task of an avatar resembling the sub-tasks needed to trigger steps with an exoskeleton. We ran an experiment with forty healthy participants to investigate the effects of first- (1PP) vs. third-person perspective (3PP) and the provision (or not) of concurrent visual feedback of participants' movements on the walking performance - namely number of steps, trunk inclination, and stride length -, as well as the effects on embodiment, usability, cybersickness, and perceived workload.

Results: We found that all participants learned to execute the virtual walking task. However, no clear interaction of perspective and visual feedback improved the learning of all sub-tasks concurrently. Instead, the key seems to lie in selecting the appropriate perspective and visual feedback for each sub-task. Notably, participants embodied the avatar across all training modalities with low cybersickness levels. Still, participants' cognitive load remained high, leading to marginally acceptable usability scores.

Conclusions: Our findings suggest that to maximize learning, users should train sub-tasks sequentially using the most suitable combination of person's perspective and visual feedback for each sub-task. This research offers valuable insights for future developments in IVR to support individuals with sensorimotor disorders in improving the learning of walking with wearable exoskeletons.