Definition dependent properties of the cortical silent period in upper-extremity muscles, a methodological study

Downward adjustment of rehabilitation goals may facilitate post-stroke arm motor recovery

Objective: Patients starting with physical rehabilitation often hold unrealistically high expectations for their recovery. Because of a lower-than-expected rate of recovery, such unrealistic goals have been linked to adverse effects on mental health. Additionally, overtraining due to overly ambitious goals can lead to suboptimal recovery. We investigated the effectiveness of adjusting rehabilitation goals to a more realistic level as a strategy to select appropriate exercise intensity and achieve better recovery outcomes. Design: Patients with arm paralysis from recent stroke were recruited and went through 6-8 weeks of telerehabilitation and in-clinic rehabilitation programme conducted at 11 US sites (N = 124). Main Outcome Measures: Adjustment of recovery goal was assessed in two timepoints during the rehabilitation programme and arm motor function was assessed before and after the clinical trial. Results: Greater use of goal adjustment strategies predicted better recovery of arm motor function, independent from therapy compliance. This pattern was observed only when the choice of exercises is patient-regulated rather than directed by a physical therapist. Conclusion: Benefits from goal adjustment were more pronounced among patients who entered the programme with poorer motor functions, suggesting that goal adjustment is the most beneficial when goals of complete recovery are most unrealistic.

Temporal localization of upper extremity bilateral synergistic coordination using wearable accelerometers

Background

The human upper extremity is characterized by inherent motor abundance, allowing a diverse array of tasks with agility and adaptability. Upper extremity functional limitations are a common sequela to Stroke, resulting in pronounced motor and sensory impairments in the contralesional arm. While many therapeutic interventions focus on rehabilitating the weaker arm, it is increasingly evident that it is necessary to consider bimanual coordination and motor control.

Methods

Participants were recruited to two groups differing in age (Group 1 (n = 10): 23.4 ± 2.9 years, Group 2 (n = 10): 55.9 ± 10.6 years) for an exploratory study on the use of accelerometry to quantify bilateral coordination. Three tasks featuring coordinated reaching were selected to investigate the acceleration of the upper arm, forearm, and hand during activities of daily living (ADLs). Subjects were equipped with acceleration and inclination sensors on each upper arm, each forearm, and each hand. Data was segmented in MATLAB to assess inter-limb and intra-limb coordination. Inter-limb coordination was indicated through dissimilarity indices and temporal locations of congruous movement between upper arm, forearm, or hand segments of the right and left limbs. Intra-limb coordination was likewise assessed between upper arm-forearm, upper arm-hand, and forearm-hand segment pairs of the dominant limb.

Findings

Acceleration data revealed task-specific movement features during the three distinct tasks. Groups demonstrated diminished similarity as task complexity increased. Groups differed significantly in the hand segments during the buttoning task, with Group 1 showing no coordination in the hand segments during buttoning, and strong coordination in reaching each button with the upper arm and forearm guiding extension. Group 2's dissimilarity scores and percentages of similarity indicated longer periods of inter-limb coordination, particularly towards movement completion. Group 1's dissimilarity scores and percentages of similarity indicated longer periods of intra-limb coordination, particularly in the coordination of the upper arm and forearm segments.

Interpretation

The Expanding Procrustes methodology can be applied to compute objective coordination scores using accessible and highly accurate wearable acceleration sensors. The findings of task duration, angular velocity, and peak roll angle are supported by previous studies finding older individuals to present with slower movements, reduced movement stability, and a reduction of laterality between the limbs. The theory of a shift towards ambidexterity with age is supported by the finding of greater inter-limb coordination in the group of subjects above the age of thirty-five. The group below the age of thirty was found to demonstrate longer periods of intra-limb coordination, with upper arm and forearm coordination emerging as a possible explanation for the demonstrated greater stability.

Corporate social responsibility: A key driver of sustainable development in China's post-COVID economy

The first goal of this research was to measure the impact of corporate social responsibility (CSR) on the sustainable development of an organization. However, the second objective examines the moderating influence of government policies, cultural norms, and stakeholder expectations on the relationship between CSR and an organization's sustainable development. This research primarily focused on the enterprises operating in the energy industry in Beijing. A sample of 498 individuals holding management positions within these enterprises was collected. The study's results established that CSR significantly influences the sustainable development of firms. Moreover, the results revealed that governmental regulations, cultural norms, and stakeholder expectations play a significant and positive role in moderating the impact of corporate social responsibility on the sustainable development of companies. The results of this study make a valuable contribution to the existing body of literature on CSR and its impact on the sustainable performance of enterprises in China.

Physical activity and self-efficacy in college students: the mediating role of grit and the moderating role of gender

Background

There is a paucity of knowledge concerning the psychological variables that serve to facilitate the connection between physical activity and self-efficacy, and the factors capable of moderating these pathways. This study aimed to examine the relationship between physical activity and self-efficacy among college students, with a focus on the mediating effect of grit and the moderating effect of gender.

Methods

This study recruited 3,228 undergraduate students from a university in Shanghai, China. They completed the General Self-Efficacy Scale, the Short Grit Scale, and the International Physical Activity Questionnaire. Statistical analysis was conducted using SPSS 26.0 and the Process v4.0 plugin.

Results

Physical activity had both a direct effect on self-efficacy (β = 0.07, 95% CI [0.04-0.11]) and an indirect effect through the two dimensions of grit: perseverance of effort (β = 0.06, 95% CI [0.04-0.07]) and consistency of interest (β = 0.03, 95% CI [0.02-0.04]). The mediating effect explained 53.27% of the total effect. Furthermore, gender moderated the relationship between perseverance of effort and self-efficacy, with a stronger effect observed in males (β = 0.08, t = 3.27, p < 0.01).

Conclusion

The results revealed that grit is an underlying psychological mechanism that links physical activity and self-efficacy. Moreover, gender moderates the effect of perseverance of effort on self-efficacy, with a stronger effect observed in males. These findings have practical implications for educators to design tailored physical activity interventions that foster grit and self-efficacy among college students.

Assessing the role of ankle and hip joint proprioceptive information in balance recovery using vibratory stimulation

Background

Previous work suggests that proprioceptive information from ankle and hip are crucial in maintaining balance during upright standing; however, the contribution of these proprioceptive information during stepping balance recovery in not clear. The goal of the current study was to assess the role of ankle and hip proprioceptive information on balance recovery performance by manipulating type 1a afferent in muscle spindles using vibratory stimulation.

Methods

Twenty healthy young participants were recruited (age = 22.2 ± 2.7 years) and were randomly assigned to balance recovery sessions with either ankle or hip stimulation. Trip-like perturbations were imposed using a modified treadmill setup with a protecting harness. Vibratory stimulation was imposed bilaterally on ankle and hip muscles to expose participants to three condition of no-vibration, 40Hz vibration, and 80Hz vibration. Kinematics of the trunk and lower-extremities were measured using wearable sensors to characterize balance recovery performance. Outcomes were response time, recovery step length, trunk angle during toe-off and heel-strike of recovery stepping, and required time for full recovery.

Findings

Ankle vibratory stimulation elicited main effects on reaction time and recovery step length (p < 0.002); reaction time and recovery step length increased by 23.0% and 21.2%, respectively, on average across the conditions. Hip vibratory stimulation elicited significant increase in the full recovery time (p = 0.019), with 55.3% increase on average across the conditions.

Interpretation

Current findings provided evidence that vibratory stimulation can affect the balance recovery performance, causing a delayed recovery initiation and an impaired balance refinement after the recovery stepping when applied to ankle and hip muscles, respectively.

Upper limb modeling and motion extraction based on multi-space-fusion

Modeling and motion extraction of human upper limbs are essential for interpreting the natural behavior of upper limb. Owing to the high degrees of freedom (DOF) and highly dynamic nature, existing upper limb modeling methods have limited applications. This study proposes a generic modeling and motion extraction method, named Primitive-Based triangular body segment method (P-BTBS), which follows the physiology of upper limbs, allows high accuracy of motion angles, and describes upper-limb motions with high accuracy. For utilizing the upper-limb modular motion model, the motion angles and bones can be selected as per the research topics (The generic nature of the study targets). Additionally, P-BTBS is suitable in most scenarios for estimating spatial coordinates (The generic nature of equipment and technology). Experiments in continuous motions with seven DOFs and upper-limb motion description validated the excellent performance and robustness of P-BTBS in extracting motion information and describing upper-limb motions, respectively. P-BTBS provides a new perspective and mathematical tool for human understanding and exploration of upper-limb motions, which theoretically supports upper-limb research.

Perspectives from research and practice: A survey on external load monitoring and bone in sport

Introduction

There is limited information regarding the association between external load and estimated bone load in sport, which may be important due to the influence exercise can have on bone accrual and injury risk. The aim of this study was to identify external load measuring tools used by support staff to estimate bone load and assess if these methodologies were supported in research.

Methods

A survey was comprised of 19 multiple choice questions and the option to elaborate on if/how they monitor external load and if/how they used them to estimate bone load. A narrative review was performed to assess how external load is associated to bone in research.

Results

Participants were required to be working as support staff in applied sport. Support staff (n = 71) were recruited worldwide with the majority (85%) working with professional elite athletes. 92% of support staff monitored external load in their organisation, but only 28% used it to estimate bone load.

Discussion

GPS is the most commonly used method to estimate bone load, but there is a lack of research assessing GPS metrics with bone load. Accelerometry and force plates were among the most prevalent methods used to assess external load, but a lack of bone specific measurements were reported by support staff. Further research exploring how external load relates to bone is needed as there is no consensus on which method of external load is best to estimate bone load in an applied setting.

Instrumented Timed Up and Go Test (iTUG)-More Than Assessing Time to Predict Falls: A Systematic Review

The Timed Up and Go (TUG) test is a widely used tool for assessing the risk of falls in older adults. However, to increase the test's predictive value, the instrumented Timed Up and Go (iTUG) test has been developed, incorporating different technological approaches. This systematic review aims to explore the evidence of the technological proposal for the segmentation and analysis of iTUG in elderlies with or without pathologies. A search was conducted in five major databases, following PRISMA guidelines. The review included 40 studies that met the eligibility criteria. The most used technology was inertial sensors (75% of the studies), with healthy elderlies (35%) and elderlies with Parkinson's disease (32.5%) being the most analyzed participants. In total, 97.5% of the studies applied automatic segmentation using rule-based algorithms. The iTUG test offers an economical and accessible alternative to increase the predictive value of TUG, identifying different variables, and can be used in clinical, community, and home settings.

A Systematic Review of Low-Cost Actuator Implementations for Lower-Limb Exoskeletons: a Technical and Financial Perspective

A common issue with many commercial rehabilitative exoskeletons and orthoses are that they can be prohibitively expensive for an average individual to afford without additional financial support. Due to this a user may have limited to the usage of such devices within set rehabilitation sessions as opposed to a continual usage. The purpose of this review is therefore to find which actuator implementations would be most suitable for a simplistic, low-cost powered orthoses capable of assisting those with pathologic gait disorders by collating literature from Web of Science, Scopus, and Grey Literature. In this systematic review paper 127 papers were selected from these databases via the PRISMA guidelines, with the financial costs of 25 actuators discovered with 11 distinct actuator groups identified. The review paper will consider a variety of actuator implementations used in existing lower-limb exoskeletons that are specifically designed for the purpose of rehabilitating or aiding those with conditions inhibiting natural movement abilities, such as electric motors, hydraulics, pneumatics, cable-driven actuators, and compliant actuators. Key attributes such as technical simplicity, financial cost, power efficiency, size limitations, accuracy, and reliability are compared for all actuator groups. Statistical findings show that rotary electric motors (which are the most common actuator type within collated literature) and compliant actuators (such as elastic and springs) would be the most suitable actuators for a low-cost implementation. From these results, a possible actuator design will be proposed making use of both rotary electric motors and compliant actuators.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10846-022-01695-0.

Competitive motivation increased home use and improved prosthesis self-perception after Cybathlon 2020 for neuromusculoskeletal prosthesis user

Background

Assistive technologies, such as arm prostheses, are intended to improve the quality of life of individuals with physical disabilities. However, certain training and learning is usually required from the user to make these technologies more effective. Moreover, some people can be encouraged to train more through competitive motivation.

Methods

In this study, we investigated if the training for and participation in a competitive event (Cybathlon 2020) could promote behavioral changes in an individual with upper limb amputation (the pilot). We defined behavioral changes as the active time while his prosthesis was actuated, ratio of opposing and simultaneous movements, and the pilot’s ability to finely modulate his movement speeds. The investigation was based on extensive home-use data from the period before, during and after the Cybathlon 2020 competition.

Results

Relevant behavioral changes were found from both quantitative and qualitative analyses. The pilot’s home use of his prosthesis nearly doubled in the period before the Cybathlon, and remained 66% higher than baseline after the competition. Moreover, he improved his speed modulation when controlling his prosthesis, and he learned and routinely operated new movements in the prosthesis (wrist rotation) at home. Additionally, as confirmed by semi-structured interviews, his self-perception of the prosthetic arm and its functionality also improved.

Conclusions

An event like the Cybathlon may indeed promote behavioral changes in how competitive individuals with amputation use their prostheses. Provided that the prosthesis is suitable in terms of form and function for both competition and at-home daily use, daily activities can become opportunities for training, which in turn can improve prosthesis function and create further opportunities for daily use. Moreover, these changes appeared to remain even well after the event, albeit relevant only for individuals who continue using the technology employed in the competition.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-022-01024-4.

Performance Analysis of Conventional Machine Learning Algorithms for Diabetic Sensorimotor Polyneuropathy Severity Classification Using Nerve Conduction Studies

Background

Diabetic sensorimotor polyneuropathy (DSPN) is a major form of complication that arises in long-term diabetic patients. Even though the application of machine learning (ML) in disease diagnosis is very common and well-established in the field of research, its application in DSPN diagnosis using nerve conduction studies (NCS), is very limited in the existing literature.

Method

In this study, the NCS data were collected from the Diabetes Control and Complications Trial (DCCT) and its follow-up Epidemiology of Diabetes Interventions and Complications (EDIC) clinical trials. The NCS variables are median motor velocity (m/sec), median motor amplitude (mV), median motor F-wave (msec), median sensory velocity (m/sec), median sensory amplitude (μV), Peroneal Motor Velocity (m/sec), peroneal motor amplitude (mv), peroneal motor F-wave (msec), sural sensory velocity (m/sec), and sural sensory amplitude (μV). Three different feature ranking techniques were used to analyze the performance of eight different conventional classifiers.

Results

The ensemble classifier outperformed other classifiers for the NCS data ranked when all the NCS features were used and provided an accuracy of 93.40%, sensitivity of 91.77%, and specificity of 98.44%. The random forest model exhibited the second-best performance using all the ten features with an accuracy of 93.26%, sensitivity of 91.95%, and specificity of 98.95%. Both ensemble and random forest showed the kappa value 0.82, which indicates that the models are in good agreement with the data and the variables used and are accurate to identify DSPN using these ML models.

Conclusion

This study suggests that the ensemble classifier using all the ten NCS variables can predict the DSPN severity which can enhance the management of DSPN patients.

Machine Learning-Based Diabetic Neuropathy and Previous Foot Ulceration Patients Detection Using Electromyography and Ground Reaction Forces during Gait

Diabetic neuropathy (DN) is one of the prevalent forms of neuropathy that involves alterations in biomechanical changes in the human gait. Diabetic foot ulceration (DFU) is one of the pervasive types of complications that arise due to DN. In the literature, for the last 50 years, researchers have been trying to observe the biomechanical changes due to DN and DFU by studying muscle electromyography (EMG) and ground reaction forces (GRF). However, the literature is contradictory. In such a scenario, we propose using Machine learning techniques to identify DN and DFU patients by using EMG and GRF data. We collected a dataset from the literature which involves three patient groups: Control (n = 6), DN (n = 6), and previous history of DFU (n = 9) and collected three lower limb muscles EMG (tibialis anterior (TA), vastus lateralis (VL), gastrocnemius lateralis (GL)), and three GRF components (GRFx, GRFy, and GRFz). Raw EMG and GRF signals were preprocessed, and different feature extraction techniques were applied to extract the best features from the signals. The extracted feature list was ranked using four different feature ranking techniques, and highly correlated features were removed. In this study, we considered different combinations of muscles and GRF components to find the best performing feature list for the identification of DN and DFU. We trained eight different conventional ML models: Discriminant analysis classifier (DAC), Ensemble classification model (ECM), Kernel classification model (KCM), k-nearest neighbor model (KNN), Linear classification model (LCM), Naive Bayes classifier (NBC), Support vector machine classifier (SVM), and Binary decision classification tree (BDC), to find the best-performing algorithm and optimized that model. We trained the optimized the ML algorithm for different combinations of muscles and GRF component features, and the performance matrix was evaluated. Our study found the KNN algorithm performed well in identifying DN and DFU, and we optimized it before training. We found the best accuracy of 96.18% for EMG analysis using the top 22 features from the chi-square feature ranking technique for features from GL and VL muscles combined. In the GRF analysis, the model showed 98.68% accuracy using the top 7 features from the Feature selection using neighborhood component analysis for the feature combinations from the GRFx-GRFz signal. In conclusion, our study has shown a potential solution for ML application in DN and DFU patient identification using EMG and GRF parameters. With careful signal preprocessing with strategic feature extraction from the biomechanical parameters, optimization of the ML model can provide a potential solution in the diagnosis and stratification of DN and DFU patients from the EMG and GRF signals.

Balance on different unstable supports: a complementary approach based on linear and non-linear analyses

Maintenance of postural control is a complex task that requires the integration of different sensory-motor processes. To improve postural control, balance training is often implemented using unstable surfaces. Little is known, however, about how different surfaces compare in terms of postural control strategy. Non-linear dynamical system analysis, like recurrent quantification analysis (RQA) applied to the center of pressure (CoP) trajectory, represents a useful tool in this respect. The aim of this study is to investigate the effects of different unstable supports on the CoP trajectory through a complementary approach based on linear and non-linear analyses. Seventeen healthy adults performed barefoot single-leg balance trials on a force plate and on three different balance training devices (soft disc, foam pad, and pillow). Sets of parameters were extracted from the CoP trajectories using classical stabilometric analysis (sway path, mean velocity, root mean square) and RQA (percent recurrence and determinism, maximum line length, entropy). Both classical and RQA analyses highlighted significant differences between stable (force plate) and unstable conditions (p < 0.001). Conversely, only classical stabilometric parameters showed significant differences among the considered balance training devices, indicating that the different characteristics of the devices do not influence the dynamic/temporal structure of the CoP trajectory. Analysis of the center of pressure trajectory during single-leg standing on three different balance training devices and on a rigid surface using both linear and non-linear techniques.

Measurement error and reliability of TMS metrics collected from biceps and triceps in individuals with chronic incomplete tetraplegia

Transcranial magnetic stimulation (TMS) is used to investigate corticomotor neurophysiology associated with functional recovery in individuals with spinal cord injury (SCI). There is insufficient evidence about test-retest measurement properties of TMS in SCI. Therefore, we investigated test-retest agreement and reliability of TMS metrics representing corticomotor excitability, output, gain, map (representation), and inhibition in individuals with cervical SCI. We collected TMS metrics from biceps and triceps muscles because of the relevance of this proximal muscle pair to the cervical SCI population. Twelve individuals with chronic C3-C6 SCI participated in two TMS sessions separated by ≥ 2 weeks. Measurement agreement was evaluated using t tests, Bland-Altman limits of agreement and relative standard error of measurement (SEM%), while reliability was investigated using intra-class correlation coefficient (ICC) and concordance correlation coefficient (CCC). We calculated the smallest detectable change for all TMS metrics. All TMS metrics except antero-posterior map coordinates and corticomotor inhibition were in agreement upon repeated measurement though limits of agreement were generally large. Measures of corticomotor excitability, output and medio-lateral map coordinates had superior agreement (SEM% < 10). Metrics representing corticomotor excitability, output, and inhibition had good-to-excellent reliability (ICC/CCC > 0.75). The smallest detectable change for TMS metrics was generally high for a single individual, but this value reduced substantially with increase in sample size. We recommend use of corticomotor excitability and recruitment curve area owing to their superior measurement properties. A modest group size (20 or above) yields more stable measurements, which may favor use of TMS metrics in group level modulation after SCI.

The need for a paradigm shift in the development of military exoskeletons

An exoskeleton is a body-worn mechanical device designed to work in concert with the user to enhance human capabilities. For the dismounted close combatant, an exoskeleton could be worn whilst performing a variety of complex tasks and duties. As such, there is a requirement for the human and the exoskeleton to readily adapt to different movements in different contexts. There have been many attempts to design an exoskeleton to improve the performance of the complex adaptive human system with limited success. Despite a vast investment in time and resources, exoskeletons have not yet been adopted for operational use by military leadership for use by the dismounted close combatant as they are yet to demonstrate substantive augmentation to individual warfighter and collective team capability. We argue that a major limitation of current exoskeleton systems is their inability to concurrently adapt to the user, task and environment. Unless a device can meet this requirement, it is unlikely to offer a comparative benefit to the dismounted close combatant. This paper will present the state of the art of current exoskeleton technology, and recommend future research necessary to reach an acceptable standard of augmentation and thereby lead to widespread adoption.

A Pilot Investigation of the Influence of a Passive Military Exoskeleton on the Performance of Lab-Simulated Operational Tasks

OCCUPATIONAL APPLICATIONSMilitary load carriage increases musculoskeletal injury risk and reduces performance, but is essential for operational effectiveness. Exoskeletons may play a role in reducing soldier burden. We found that wearing a customized passive exoskeleton during a military obstacle course decreased overall performance compared to a mass-matched control condition. Specifically, the "Stairs and Ladder" and "Hatch and Tunnel" obstacles were performed slower while wearing the exoskeleton. In contrast, similar mean completion times in the "Casualty Drag," "Sprint" and "Agility Run" obstacles were found in both the exoskeleton and control conditions. Acceptability of equipment weight and torso stiffness were rated similarly across conditions, whereas the acceptability of overall performance was rated lowest while wearing the exoskeleton. The results of this preliminary investigation suggest that the time to complete operationally-relevant military obstacles was not improved by wearing a passive exoskeleton.

Investigating the effects of chronic perinatal alcohol and combined nicotine and alcohol exposure on dopaminergic and non-dopaminergic neurons in the VTA

The ventral tegmental area (VTA) is the origin of dopaminergic neurons and the dopamine (DA) reward pathway. This pathway has been widely studied in addiction and drug reinforcement studies and is believed to be the central processing component of the reward circuit. In this study, we used a well-established rat model to expose mother dams to alcohol, nicotine-alcohol, and saline perinatally. DA and non-DA neurons collected from the VTA of the rat pups were used to study expression profiles of miRNAs and mRNAs. miRNA pathway interactions, putative miRNA-mRNA target pairs, and downstream modulated biological pathways were analyzed. In the DA neurons, 4607 genes were differentially upregulated and 4682 were differentially downregulated following nicotine-alcohol exposure. However, in the non-DA neurons, only 543 genes were differentially upregulated and 506 were differentially downregulated. Cell proliferation, differentiation, and survival pathways were enriched after the treatments. Specifically, in the PI3K/AKT signaling pathway, there were 41 miRNAs and 136 mRNAs differentially expressed in the DA neurons while only 16 miRNAs and 20 mRNAs were differentially expressed in the non-DA neurons after the nicotine-alcohol exposure. These results depicted that chronic nicotine and alcohol exposures during pregnancy differentially affect both miRNA and gene expression profiles more in DA than the non-DA neurons in the VTA. Understanding how the expression signatures representing specific neuronal subpopulations become enriched in the VTA after addictive substance administration helps us to identify how neuronal functions may be altered in the brain.

Postural control strategy after incomplete spinal cord injury: effect of sensory inputs on trunk-leg movement coordination

BACKGROUND

Postural control is affected after incomplete spinal cord injury (iSCI) due to sensory and motor impairments. Any alteration in the availability of sensory information can challenge postural stability in this population and may lead to a variety of adaptive movement coordination patterns. Hence, identifying the underlying impairments and changes to movement coordination patterns is necessary for effective rehabilitation post-iSCI. This study aims to compare the postural control strategy between iSCI and able-bodied populations by quantifying the trunk-leg movement coordination under conditions that affects sensory information.

METHODS

13 individuals with iSCI and 14 aged-matched able-bodied individuals performed quiet standing on hard and foam surfaces with eyes open and closed. We used mean Magnitude-Squared Coherence between trunk-leg accelerations measured by accelerometers placed over the sacrum and tibia.

RESULTS

We observed a similar ankle strategy at lower frequencies (f ≤ 1.0 Hz) between populations. However, we observed a decreased ability post-iSCI in adapting inter-segment coordination changing from ankle strategy to ankle-hip strategy at higher frequencies (f > 1.0 Hz). Moreover, utilizing the ankle-hip strategy at higher frequencies was challenged when somatosensory input was distorted, whereas depriving visual information did not affect balance strategy.

CONCLUSION

Trunk-leg movement coordination assessment showed sensitivity, discriminatory ability, and excellent test-retest reliability to identify changes in balance control strategy post-iSCI and due to altered sensory inputs. Trunk-leg movement coordination assessment using wearable sensors can be used for objective outcome evaluation of rehabilitative interventions on postural control post-iSCI.

Investigating the influence of perinatal nicotine exposure on genetic profiles of neurons in the sub-regions of the VTA

Chronic nicotine exposure during pregnancy has been shown to induce physiological and anatomical alterations in offspring. Previously, we investigated the complexity of dopamine (DA) neuron firing in the sub-regions of the ventral tegmental area (VTA) following perinatal nicotine exposure. Using approximate entropy, we found that within the middle sub-region, the parainterfascicular nucleus (PIF), there was higher complexity indicating more random neural firing and a less homogeneous neuron population. Therefore, we sought to investigate the neuron populations within the sub-regions of the VTA following perinatal nicotine exposure. We used real time PCR in order to find the relative quantity of glutamate to γ-aminobutyric acid (GABA), DA, and glutamate neurons within three sub-regions: the parabrachial pigmented nucleus (PBP), parainterfascicular nucleus (PIF), and paranigral nucleus (PN). Our results showed that the PIF region of the VTA contained a more diverse population of neurons resulting in a more complex system. In addition, we found that DA neurons are more activated in PN sub-region of the VTA, which mediates the rewarding effects of drugs including nicotine. Lastly, using immunohistochemistry, we observed an overall decrease in DA neurons following perinatal nicotine exposure.

Electrical stimulation-induced SSSEP as an objective index to evaluate the difference of tactile acuity between the left and right hand

OBJECTIVE

The objective of this study is to propose an objective index to evaluate the difference of tactile acuity between the left and right hand based on steady-state somatosensory evoked potential (SSSEP).

APPROACH

Two kinds of tactile sensations (vibration and pressure) with three levels of intensities (low/medium/high) were evoked on two finger areas of the left or right hand (thumb and index for healthy hands, thumb and index-projected areas for disabled hands) via transcutaneous electrical nerve stimulation (TENS). Three forearm amputees and 13 able-bodied subjects were recruited to discriminate the specific level and area of the applied stimulation. Electroencephalography was adopted to simultaneously record the somatosensory cortex response to TENS. We assessed the discrimination performance (discrimination accuracy rate (AR) and response time (RT)) to quantify the tactile acuity, while the evoked SSSEP was synchronously analyzed. Linear regression analyses were performed between the difference of SSSEP amplitudes and the difference of discrimination performance for the left and right hand stimulation.

MAIN RESULTS

Frequency domain analysis revealed that SSSEP amplitude increased with the increase of the stimulation intensity. There were positive correlations between the difference of SSSEP amplitudes and the difference of ARs for the left and right hand stimulation in the sensations of vibration (R ²  =  0.6389 for able-bodied subjects, R ²  =  0.5328 for amputees) and pressure (R ²  =  0.6102 for able-bodied subjects, R ²  =  0.5452 for amputees), respectively. Significance The SSSEP amplitude could be used as an objective index to evaluate the difference of the tactile acuity between the left and right hand and has the potential to be applied in sensory rehabilitation for amputees or stroke patients.

Transcranial magnetic stimulation induced early silent period and rebound activity re-examined

Despite being widely studied, the underlying mechanisms of transcranial magnetic brain stimulation (TMS) induced motor evoked potential (MEP), early cortical silent period (CSP) and rebound activity are not fully understood. Our aim is to better characterize these phenomena by combining various analysis tools on firing motor units. Responses of 29 tibialis anterior (TA) and 8 abductor pollicis brevis (APB) motor units to TMS pulses were studied using discharge rate and probability-based tools to illustrate the profile of the synaptic potentials as they develop on motoneurons in 24 healthy volunteers. According to probability-based methods, TMS pulse produces a short-latency MEP which is immediately followed by CSP that terminates at rebound activity. Discharge rate analysis, however, revealed not three, but just two events with distinct time courses; a long-lasting excitatory period (71.2 ± 9.0 ms for TA and 42.1 ± 11.2 ms for APB) and a long-latency inhibitory period with duration of 57.9 ± 9.5 ms for TA and 67.3 ± 13.8 ms for APB. We propose that part of the CSP may relate to the falling phase of net excitatory postsynaptic potential induced by TMS. Rebound activity, on the other hand, may represent tendon organ inhibition induced by MEP activated soleus contraction and/or long-latency intracortical inhibition. Due to generation of field potentials when high intensity TMS is used, this study is limited to investigate the events evoked by low intensity TMS only and does not provide information about later parts of much longer CSPs induced by high intensity TMS. Adding discharge rate analysis contributes to obtain a more accurate picture about the characteristics of TMS-induced events. These results have implications for interpreting motor responses following TMS for diagnosis and overseeing recovery from various neurological conditions.

Continuous 2D control via state-machine triggered by endogenous sensory discrimination and a fast brain switch

OBJECTIVE

Brain computer interfacing (BCI) is a promising method to control assistive systems for patients with severe disabilities. Recently, we have presented a novel BCI approach that combines an electrotactile menu and a brain switch, which allows the user to trigger many commands robustly and efficiently. However, the commands are timed to periodic tactile cues and this may challenge online control. In the present study, therefore, we implemented and evaluated a novel approach for online closed-loop control using the proposed BCI.

APPROACH

Eleven healthy subjects used the novel method to move a cursor in a 2D space. To assure robust control with properly timed commands, the BCI was integrated within a state machine allowing the subject to start the cursor movement in the selected direction and asynchronously stop the cursor. The brain switch was controlled using motor execution (ME) or imagery (MI) and the menu implemented four (straight movements) or eight commands (straight and diagonal movements).

MAIN RESULTS

The results showed a high completion rate of a target hitting task (~97% and ~92% for ME and MI, respectively), with a small number of collisions, when four-channel control was used. There was no significant difference in outcome measures between MI and ME, and performance was similar for four and eight commands.

SIGNIFICANCE

These results demonstrate that the novel state-based scheme driven by a robust BCI can be successfully utilized for online control. Therefore, it can be an attractive solution for providing the user an online-control interface with many commands, which is difficult to achieve using classic BCI solutions.

Transcranial direct current stimulation for the treatment of motor impairment following traumatic brain injury

After traumatic brain injury (TBI), motor impairment is less common than neurocognitive or behavioral problems. However, about 30% of TBI survivors have reported motor deficits limiting the activities of daily living or participation. After acute primary and secondary injuries, there are subsequent changes including increased GABA-mediated inhibition during the subacute stage and neuroplastic alterations that are adaptive or maladaptive during the chronic stage. Therefore, timely and appropriate neuromodulation by transcranial direct current stimulation (tDCS) may be beneficial to patients with TBI for neuroprotection or restoration of maladaptive changes.Technologically, combination of imaging-based modelling or simultaneous brain signal monitoring with tDCS could result in greater individualized optimal targeting allowing a more favorable neuroplasticity after TBI. Moreover, a combination of task-oriented training using virtual reality with tDCS can be considered as a potent tele-rehabilitation tool in the home setting, increasing the dose of rehabilitation and neuromodulation, resulting in better motor recovery.This review summarizes the pathophysiology and possible neuroplastic changes in TBI, as well as provides the general concepts and current evidence with respect to the applicability of tDCS in motor recovery. Through its endeavors, it aims to provide insights on further successful development and clinical application of tDCS in motor rehabilitation after TBI.

A Systematic Review for Human EEG Brain Signals Based Emotion Classification, Feature Extraction, Brain Condition, Group Comparison

The study of electroencephalography (EEG) signals is not a new topic. However, the analysis of human emotions upon exposure to music considered as important direction. Although distributed in various academic databases, research on this concept is limited. To extend research in this area, the researchers explored and analysed the academic articles published within the mentioned scope. Thus, in this paper a systematic review is carried out to map and draw the research scenery for EEG human emotion into a taxonomy. Systematically searched all articles about the, EEG human emotion based music in three main databases: ScienceDirect, Web of Science and IEEE Xplore from 1999 to 2016. These databases feature academic studies that used EEG to measure brain signals, with a focus on the effects of music on human emotions. The screening and filtering of articles were performed in three iterations. In the first iteration, duplicate articles were excluded. In the second iteration, the articles were filtered according to their titles and abstracts, and articles outside of the scope of our domain were excluded. In the third iteration, the articles were filtered by reading the full text and excluding articles outside of the scope of our domain and which do not meet our criteria. Based on inclusion and exclusion criteria, 100 articles were selected and separated into five classes. The first class includes 39 articles (39%) consists of emotion, wherein various emotions are classified using artificial intelligence (AI). The second class includes 21 articles (21%) is composed of studies that use EEG techniques. This class is named 'brain condition'. The third class includes eight articles (8%) is related to feature extraction, which is a step before emotion classification. That this process makes use of classifiers should be noted. However, these articles are not listed under the first class because these eight articles focus on feature extraction rather than classifier accuracy. The fourth class includes 26 articles (26%) comprises studies that compare between or among two or more groups to identify and discover human emotion-based EEG. The final class includes six articles (6%) represents articles that study music as a stimulus and its impact on brain signals. Then, discussed the five main categories which are action types, age of the participants, and number size of the participants, duration of recording and listening to music and lastly countries or authors' nationality that published these previous studies. it afterward recognizes the main characteristics of this promising area of science in: motivation of using EEG process for measuring human brain signals, open challenges obstructing employment and recommendations to improve the utilization of EEG process.

Classification of different reaching movements from the same limb using EEG

OBJECTIVE

Brain-computer-interfaces (BCIs) have been proposed not only as assistive technologies but also as rehabilitation tools for lost functions. However, due to the stochastic nature, poor spatial resolution and signal to noise ratio from electroencephalography (EEG), multidimensional decoding has been the main obstacle to implement non-invasive BCIs in real-live rehabilitation scenarios. This study explores the classification of several functional reaching movements from the same limb using EEG oscillations in order to create a more versatile BCI for rehabilitation.

APPROACH

Nine healthy participants performed four 3D center-out reaching tasks in four different sessions while wearing a passive robotic exoskeleton at their right upper limb. Kinematics data were acquired from the robotic exoskeleton. Multiclass extensions of Filter Bank Common Spatial Patterns (FBCSP) and a linear discriminant analysis (LDA) classifier were used to classify the EEG activity into four forward reaching movements (from a starting position towards four target positions), a backward movement (from any of the targets to the starting position and rest). Recalibrating the classifier using data from previous or the same session was also investigated and compared.

MAIN RESULTS

Average EEG decoding accuracy were significantly above chance with 67%, 62.75%, and 50.3% when decoding three, four and six tasks from the same limb, respectively. Furthermore, classification accuracy could be increased when using data from the beginning of each session as training data to recalibrate the classifier.

SIGNIFICANCE

Our results demonstrate that classification from several functional movements performed by the same limb is possible with acceptable accuracy using EEG oscillations, especially if data from the same session are used to recalibrate the classifier. Therefore, an ecologically valid decoding could be used to control assistive or rehabilitation mutli-degrees of freedom (DoF) robotic devices using EEG data. These results have important implications towards assistive and rehabilitative neuroprostheses control in paralyzed patients.

Bipedal gait model for precise gait recognition and optimal triggering in foot drop stimulator: a proof of concept

Electrical stimulators are often prescribed to correct foot drop walking. However, commercial foot drop stimulators trigger inappropriately under certain non-gait scenarios. Past researches addressed this limitation by defining stimulation control based on automaton of a gait cycle executed by foot drop of affected limb/foot only. Since gait is a collaborative activity of both feet, this research highlights the role of normal foot for robust gait detection and stimulation triggering. A novel bipedal gait model is proposed where gait cycle is realized as an automaton based on concurrent gait sub-phases (states) from each foot. The input for state transition is fused information from feet-worn pressure and inertial sensors. Thereafter, a bipedal gait model-based stimulation control algorithm is developed. As a feasibility study, bipedal gait model and stimulation control are evaluated in real-time simulation manner on normal and simulated foot drop gait measurements from 16 able-bodied participants with three speed variations, under inappropriate triggering scenarios and with foot drop rehabilitation exercises. Also, the stimulation control employed in commercial foot drop stimulators and single foot gait-based foot drop stimulators are compared alongside. Gait detection accuracy (98.9%) and precise triggering under all investigations prove bipedal gait model reliability. This infers that gait detection leveraging bipedal periodicity is a promising strategy to rectify prevalent stimulation triggering deficiencies in commercial foot drop stimulators. Graphical abstract Bipedal information-based gait recognition and stimulation triggering.

Varying negative work assistance at the ankle with a soft exosuit during loaded walking

BACKGROUND

Only very recently, studies have shown that it is possible to reduce the metabolic rate of unloaded and loaded walking using robotic ankle exoskeletons. Some studies obtained this result by means of high positive work assistance while others combined negative and positive work assistance. There is no consensus about the isolated contribution of negative work assistance. Therefore, the aim of the present study is to examine the effect of varying negative work assistance at the ankle joint while maintaining a fixed level of positive work assistance with a multi-articular soft exosuit.

METHODS

We tested eight participants during walking at 1.5 ms-1 with a 23-kg backpack. Participants wore a version of the exosuit that assisted plantarflexion via Bowden cables tethered to an off-board actuation platform. In four active conditions we provided different rates of exosuit bilateral ankle negative work assistance ranging from 0.015 to 0.037 W kg-1 and a fixed rate of positive work assistance of 0.19 W kg-1.

RESULTS

All active conditions significantly reduced metabolic rate by 11 to 15% compared to a reference condition, where the participants wore the exosuit but no assistance was provided. We found no significant effect of negative work assistance. However, there was a trend (p = .08) toward greater reduction in metabolic rate with increasing negative work assistance, which could be explained by observed reductions in biological ankle and hip joint power and moment.

CONCLUSIONS

The non-significant trend of increasing negative work assistance with increasing reductions in metabolic rate motivates the value in further studies on the relative effects of negative and positive work assistance. There may be benefit in varying negative work over a greater range or in isolation from positive work assistance.

Do ground reaction forces during unilateral and bilateral movements exhibit compensation strategies following ACL reconstruction?

PURPOSE

The aims of the study were (1) to evaluate the leg asymmetry assessed with ground reaction forces (GRFs) during unilateral and bilateral movements of different knee loads in anterior cruciate ligament (ACL) reconstructed patients and (2) to investigate differences in leg asymmetry depending on the International Knee Documentation Committee Subjective Form (IKDC) in order to identify potential compensation strategies.

METHODS

The knee function of 50 ACL reconstructed (patella tendon) patients was examined at 31 ± 7 months after the surgery. GRFs were quantified during the sit-to-stand and stand-to-sit test, the step-up and step-down test, and the two- and one-leg vertical jump. Further, the IKDC score, the anterior-posterior knee laxity, and the concentric torque of the quadriceps and hamstring muscles were evaluated.

RESULTS

Differences between the operated and non-operated leg were found in the knee laxity, the quadriceps torque, and GRFs. The patients with low IKDC scores demonstrated greater leg asymmetries in GRFs compared to the patients with high IKDC scores.

CONCLUSIONS

ACL reconstructed patients showed GRF asymmetries during unilateral and bilateral movements of different knee loads. Three compensation strategies were found in patients with low subjective knee function: (1) a reduced eccentric load, (2) an inter-limb compensation during bilateral movements, and (3) the avoidance of high vertical impact forces. These compensation strategies may be indicative of a protective adaptation to avoid excessive ACL strain. GRF measurements are practicable and efficient tools to identify individual compensation strategies during early rehabilitation.

The hybrid BCI system for movement control by combining motor imagery and moving onset visual evoked potential

OBJECTIVE

Movement control is an important application for EEG-BCI (EEG-based brain-computer interface) systems. A single-modality BCI cannot provide an efficient and natural control strategy, but a hybrid BCI system that combines two or more different tasks can effectively overcome the drawbacks encountered in single-modality BCI control.

APPROACH

In the current paper, we developed a new hybrid BCI system by combining MI (motor imagery) and mVEP (motion-onset visual evoked potential), aiming to realize the more efficient 2D movement control of a cursor.

MAIN RESULT

The offline analysis demonstrates that the hybrid BCI system proposed in this paper could evoke the desired MI and mVEP signal features simultaneously, and both are very close to those evoked in the single-modality BCI task. Furthermore, the online 2D movement control experiment reveals that the proposed hybrid BCI system could provide more efficient and natural control commands.

SIGNIFICANCE

The proposed hybrid BCI system is compensative to realize efficient 2D movement control for a practical online system, especially for those situations in which P300 stimuli are not suitable to be applied.

A motion-classification strategy based on sEMG-EEG signal combination for upper-limb amputees

Background

Most of the modern motorized prostheses are controlled with the surface electromyography (sEMG) recorded on the residual muscles of amputated limbs. However, the residual muscles are usually limited, especially after above-elbow amputations, which would not provide enough sEMG for the control of prostheses with multiple degrees of freedom. Signal fusion is a possible approach to solve the problem of insufficient control commands, where some non-EMG signals are combined with sEMG signals to provide sufficient information for motion intension decoding. In this study, a motion-classification method that combines sEMG and electroencephalography (EEG) signals were proposed and investigated, in order to improve the control performance of upper-limb prostheses.

Methods

Four transhumeral amputees without any form of neurological disease were recruited in the experiments. Five motion classes including hand-open, hand-close, wrist-pronation, wrist-supination, and no-movement were specified. During the motion performances, sEMG and EEG signals were simultaneously acquired from the skin surface and scalp of the amputees, respectively. The two types of signals were independently preprocessed and then combined as a parallel control input. Four time-domain features were extracted and fed into a classifier trained by the Linear Discriminant Analysis (LDA) algorithm for motion recognition. In addition, channel selections were performed by using the Sequential Forward Selection (SFS) algorithm to optimize the performance of the proposed method.

Results

The classification performance achieved by the fusion of sEMG and EEG signals was significantly better than that obtained by single signal source of either sEMG or EEG. An increment of more than 14% in classification accuracy was achieved when using a combination of 32-channel sEMG and 64-channel EEG. Furthermore, based on the SFS algorithm, two optimized electrode arrangements (10-channel sEMG + 10-channel EEG, 10-channel sEMG + 20-channel EEG) were obtained with classification accuracies of 84.2 and 87.0%, respectively, which were about 7.2 and 10% higher than the accuracy by using only 32-channel sEMG input.

Conclusions

This study demonstrated the feasibility of fusing sEMG and EEG signals towards improving motion classification accuracy for above-elbow amputees, which might enhance the control performances of multifunctional myoelectric prostheses in clinical application.

Trial registration

The study was approved by the ethics committee of Institutional Review Board of Shenzhen Institutes of Advanced Technology, and the reference number is SIAT-IRB-150515-H0077.

Neurophysiological Characterization of Subacute Stroke Patients: A Longitudinal Study

Various degrees of neural reorganization may occur in affected and unaffected hemispheres in the early phase after stroke and several months later. Recent literature suggests to apply a stratification based on lesion location and to consider patients with cortico-subcortical and subcortical strokes separately: different lesion location may also influence therapeutic response. In this study we used a longitudinal approach to perform TMS assessment (Motor Evoked Potentials, MEP, and Silent Period, SP) and clinical evaluations (Barthel Index, Fugl-Meyer Assessment for upper limb motor function and Wolf Motor Function Test) in 10 cortical-subcortical and 10 subcortical ischemic stroke patients. Evaluations were performed in a window between 10 and 45 days (t0) and at 3 months after the acute event (t1). Our main finding is that 3 months after the acute event patients affected by subcortical stroke presented a reduction in contralateral SP duration in the unaffected hemisphere; this trend is related to clinical improvement of upper limb motor function. In conclusion, SP proved to be a valid parameter to characterize cortical reorganization patterns in stroke survivors and provided useful information about motor recovery within 3 months in subcortical patients.

Independent Long Fingers are not Essential for a Grasping Hand

The human hand is a complex integrated system with motor and sensory components that provides individuals with high functionality and elegant behaviour. In direct connection with the brain, the hand is capable of performing countless actions ranging from fine digit manipulation to the handling of heavy objects. However the question of which movements mostly contribute to the manipulation skills of the hand, and thus should be included in prosthetic hands, is yet to be answered. Building from our previous work, and assuming that a hand with independent long fingers allowed performance comparable to a hand with coupled fingers, here we explored the actual contribution of independent fingers while performing activities of daily living using custom built orthoses. Our findings show that, when an opposable thumb is present, independent long fingers provide a measureable advantage in performing activities of daily living only when precision grasps are involved. In addition, the results suggest that the remarkable grasping skills of the human hand rely more on the independent abduction/adduction of the fingers than on their independent flexion/extension. These findings are of interest to the designers of artificial hands, including biomimetic prostheses and exoskeletons.

Proportional estimation of finger movements from high-density surface electromyography

BACKGROUND

The importance to restore the hand function following an injury/disease of the nervous system led to the development of novel rehabilitation interventions. Surface electromyography can be used to create a user-driven control of a rehabilitation robot, in which the subject needs to engage actively, by using spared voluntary activation to trigger the assistance of the robot.

METHODS

The study investigated methods for the selective estimation of individual finger movements from high-density surface electromyographic signals (HD-sEMG) with minimal interference between movements of other fingers. Regression was evaluated in online and offline control tests with nine healthy subjects (per test) using a linear discriminant analysis classifier (LDA), a common spatial patterns proportional estimator (CSP-PE), and a thresholding (THR) algorithm. In all tests, the subjects performed an isometric force tracking task guided by a moving visual marker indicating the contraction type (flexion/extension), desired activation level and the finger that should be moved. The outcome measures were mean square error (nMSE) between the reference and generated trajectories normalized to the peak-to-peak value of the reference, the classification accuracy (CA), the mean amplitude of the false activations (MAFA) and, in the offline tests only, the Pearson correlation coefficient (PCORR).

RESULTS

The offline tests demonstrated that, for the reduced number of electrodes (≤24), the CSP-PE outperformed the LDA with higher precision of proportional estimation and less crosstalk between the movement classes (e.g., 8 electrodes, median MAFA ~ 0.6 vs. 1.1 %, median nMSE ~ 4.3 vs. 5.5 %). The LDA and the CSP-PE performed similarly in the online tests (median nMSE < 3.6 %, median MAFA < 0.7 %), but the CSP-PE provided a more stable performance across the tested conditions (less improvement between different sessions). Furthermore, THR, exploiting topographical information about the single finger activity from HD-sEMG, provided in many cases a regression accuracy similar to that of the pattern recognition techniques, but the performance was not consistent across subjects and fingers.

CONCLUSIONS

The CSP-PE is a method of choice for selective individual finger control with the limited number of electrodes (<24), whereas for the higher resolution of the recording, either method (CPS-PA or LDA) can be used with a similar performance. Despite the abundance of detection points, the simple THR showed to be significantly worse compared to both pattern recognition/regression methods. Nevertheless, THR is a simple method to apply (no training), and it could still give satisfactory performance in some subjects and/or simpler scenarios (e.g., control of selected fingers). These conclusions are important for guiding future developments towards the clinical application of the methods for individual finger control in rehabilitation robotics.

cSPider - Evaluation of a Free and Open-Source Automated Tool to Analyze Corticomotor Silent Period

Background

The corticomotor silent period (CSP), as assessed noninvasively by transcranial magnetic stimulation (TMS) in the primary motor cortex, has been found to reflect intracortical inhibitory mechanisms. Analysis of CSP is mostly conducted manually. However, this approach is time-consuming, and comparison of results from different laboratories may be compromised by inter-rater variability in analysis. No open source program for automated analysis is currently available.

Methods/Results

Here, we describe cross-validation with the manual analysis of an in-house written automated tool to assess CSP (cSPider). Results from automated routine were compared with results of the manual evaluation. We found high inter-method reliability between automated and manual analysis (p<0.001), and significantly reduced time for CSP analysis (median = 10.3 sec for automated analysis of 10 CSPs vs. median = 270 sec for manual analysis of 10 CSPs). cSPider can be downloaded free of charge.

Conclusion

cSPider allows automated analysis of CSP in a reliable and time-efficient manner. Use of this open-source tool may help to improve comparison of data from different laboratories.

Effects of tibialis anterior vibration on postural control when exposed to support surface translations

The sensory re-weighting theory suggests unreliable inputs may be down-weighted to favor more reliable sensory information and thus maintain proper postural control. This study investigated the effects of tibialis anterior (TA) vibration on center of pressure (COP) motion in healthy individuals exposed to support surface translations to further explore the concept of sensory re-weighting. Twenty healthy young adults stood with eyes closed and arms across their chest while exposed to randomized blocks of five trials. Each trial lasted 8 s, with TA vibration either on or off. After 2 s, a sudden backward or forward translation occurred. Anterior-posterior (A/P) COP data were evaluated during the preparatory (first 2 s), perturbation (next 3 s), and recovery (last 3 s) phases to assess the effect of vibration on perturbation response features. The knowledge of an impending perturbation resulted in reduced anterior COP motion with TA vibration in the preparatory phase relative to the magnitude of anterior motion typically observed during TA vibration. During the perturbation phase, vibration did not influence COP motion. However, during the recovery phase vibration induced greater anterior COP motion than during trials without vibration. The fact that TA vibration produced differing effects on COP motion depending upon the phase of the perturbation response may suggest that the immediate context during which postural control is being regulated affects A/P COP responses to TA vibration. This indicates that proprioceptive information is likely continuously re-weighted according to the context in order to maintain effective postural control.

Biomechanical walking mechanisms underlying the metabolic reduction caused by an autonomous exoskeleton

BACKGROUND

Ankle exoskeletons can now reduce the metabolic cost of walking in humans without leg disability, but the biomechanical mechanisms that underlie this augmentation are not fully understood. In this study, we analyze the energetics and lower limb mechanics of human study participants walking with and without an active autonomous ankle exoskeleton previously shown to reduce the metabolic cost of walking.

METHODS

We measured the metabolic, kinetic and kinematic effects of wearing a battery powered bilateral ankle exoskeleton. Six participants walked on a level treadmill at 1.4 m/s under three conditions: exoskeleton not worn, exoskeleton worn in a powered-on state, and exoskeleton worn in a powered-off state. Metabolic rates were measured with a portable pulmonary gas exchange unit, body marker positions with a motion capture system, and ground reaction forces with a force-plate instrumented treadmill. Inverse dynamics were then used to estimate ankle, knee and hip torques and mechanical powers.

RESULTS

The active ankle exoskeleton provided a mean positive power of 0.105 ± 0.008 W/kg per leg during the push-off region of stance phase. The net metabolic cost of walking with the active exoskeleton (3.28 ± 0.10 W/kg) was an 11 ± 4 % (p = 0.019) reduction compared to the cost of walking without the exoskeleton (3.71 ± 0.14 W/kg). Wearing the ankle exoskeleton significantly reduced the mean positive power of the ankle joint by 0.033 ± 0.006 W/kg (p = 0.007), the knee joint by 0.042 ± 0.015 W/kg (p = 0.020), and the hip joint by 0.034 ± 0.009 W/kg (p = 0.006).

CONCLUSIONS

This study shows that the ankle exoskeleton does not exclusively reduce positive mechanical power at the ankle joint, but also mitigates positive power at the knee and hip. Furthermore, the active ankle exoskeleton did not simply replace biological ankle function in walking, but rather augmented the total (biological + exoskeletal) ankle moment and power. This study underscores the need for comprehensive models of human-exoskeleton interaction and global optimization methods for the discovery of new control strategies that optimize the physiological impact of leg exoskeletons.

Low-Frequency Repetitive Transcranial Magnetic Stimulation Targeted to Premotor Cortex Followed by Primary Motor Cortex Modulates Excitability Differently Than Premotor Cortex or Primary Motor Cortex Stimulation Alone

OBJECTIVES

The excitability of primary motor cortex (M1) can be modulated by applying low-frequency repetitive transcranial magnetic stimulation (rTMS) over M1 or premotor cortex (PMC). A comparison of inhibitory effect between the two locations has been reported with inconsistent results. This study compared the response secondary to rTMS applied over M1, PMC, and a combined PMC + M1 stimulation approach which first targets stimulation over PMC then M1.

MATERIALS AND METHODS

Ten healthy participants were recruited for a randomized, cross-over design with a one-week washout between visits. Each visit consisted of a pretest, an rTMS intervention, and a post-test. Outcome measures included short interval intracortical inhibition (SICI), intracortical facilitation (ICF), and cortical silent period (CSP). Participants received one of the three interventions in random order at each visit including: 1-Hz rTMS at 90% of resting motor threshold to: M1 (1200 pulses), PMC (1200 pulses), and PMC + M1 (600 pulses each, 1200 total).

RESULTS

PMC + M1 stimulation resulted in significantly greater inhibition than the other locations for ICF (P = 0.005) and CSP (P < 0.001); for SICI, increased inhibition (group effect) was not observed after any of the three interventions, and there was no significant difference between the three interventions.

CONCLUSION

The results indicate that PMC + M1 stimulation may modulate brain excitability differently from PMC or M1 alone. CSP was the assessment measure most sensitive to changes in inhibition and was able to distinguish between different inhibitory protocols. This work presents a novel procedure that may have positive implications for therapeutic interventions.

Reducing the energy cost of human walking using an unpowered exoskeleton

With efficiencies derived from evolution, growth and learning, humans are very well-tuned for locomotion. Metabolic energy used during walking can be partly replaced by power input from an exoskeleton, but is it possible to reduce metabolic rate without providing an additional energy source? This would require an improvement in the efficiency of the human-machine system as a whole, and would be remarkable given the apparent optimality of human gait. Here we show that the metabolic rate of human walking can be reduced by an unpowered ankle exoskeleton. We built a lightweight elastic device that acts in parallel with the user's calf muscles, off-loading muscle force and thereby reducing the metabolic energy consumed in contractions. The device uses a mechanical clutch to hold a spring as it is stretched and relaxed by ankle movements when the foot is on the ground, helping to fulfil one function of the calf muscles and Achilles tendon. Unlike muscles, however, the clutch sustains force passively. The exoskeleton consumes no chemical or electrical energy and delivers no net positive mechanical work, yet reduces the metabolic cost of walking by 7.2 ± 2.6% for healthy human users under natural conditions, comparable to savings with powered devices. Improving upon walking economy in this way is analogous to altering the structure of the body such that it is more energy-effective at walking. While strong natural pressures have already shaped human locomotion, improvements in efficiency are still possible. Much remains to be learned about this seemingly simple behaviour.