Classification of gait variation under mental workload in big five personalities.

BACKGROUND: Human behavior patterns involve mutual interactions among psychology, physiology, and stress, which are all associated with gait at different grades. RESEARCH QUESTIONS: The study aims to reveal the interrelationship among personality, mental workload, and gait patterns by capturing gait variations using inertial sensors. It also assesses individual personality traits and simulates stress to construct a gait classification model. METHODS: Sixty participants were instructed to perform regular, low, and high mental workload walking on the corridor to simulate a natural setting walking. Meanwhile inertial measurement units (IMUs) were placed on eight body parts. Mental workload was induced using the auditory n-back task, and their Big Five personality traits were evaluated. Gait data from IMUs were categorized into nine classifications of average, low, and high Big Five Inventory scores with three levels of mental workload walking. Subsequently, the segmentation gait data were used as input features for classifications in deep learning models, employing a sliding window long short-term memory network for nine classifications for different personality dimensions. RESULTS: The results indicated average accuracies of nine classifications were 83.6 % for Openness, 84.4 % for Conscientiousness, 82.0 % for Extraversion, 85.2 % for Agreeableness, and 84.5 % for Neuroticism across all IMU placements. Remarkably, gait data from the lower back IMU achieved the highest model performance, with an average accuracy of 92.7 %, in classifying the different levels of personality and mental workload walking. In contrast, the left wrist and chest showed several misclassifications among regular, low, and high mental workload walking across personality traits. SIGNIFICANCE: Successful classification can help monitor an individual's mental state in real time and analyze personality dimensions, providing feedback and suggestions. The present study demonstrated that gait characteristics can contribute to more profound and personalized health information.

The effect of a contralateral foot touch on stability of one-leg stance in young adults: an exploratory study.

PURPOSE: Previous studies demonstrated that providing light finger touch to a stationary object leads to reduced body sway. The focus of the current exploratory study was on the investigation of postural sway during one-leg stance when light touch is provided by the contralateral foot. METHODS: Eleven healthy young adults participated in the study. They stood on the top of the force platform with eyes open and on their dominant leg with no touch and with a touch from the contralateral foot applied to the stance leg. Medial arch, heel, and big toe of the contralateral foot were used to touch the medial malleolus or mid shank of the stance leg. The excursion, velocity, and sway area of the centre of pressure were obtained and analysed. RESULTS: Standing with light touch from the contralateral foot to the medial malleolus resulted in significantly smaller postural sway as compared to standing with no touch (p < 0.05). There was no difference in the study outcomes between conditions of standing with a touch applied by the medial arch, heel, or big toe to the stance leg. CONCLUSIONS: The results of the study suggest that the application of light touch provided by a contralateral foot could be an effective strategy for enhancing body stability when no external support is available. The study outcome provides a foundation for future studies exploring ways to enhance balance control during one-leg stance.

Robust 2D layered MXene matrix-boron carbide hybrid films for neutron radiation shielding.

Large-scale fabrication of neutron-shielding films with flexible or complex shapes is challenging. Uniform and high boron carbide (B4C) filler loads with sufficient workability are needed to achieve good neutron-absorption capacity. Here, we show that a two-dimensional (2D) Ti3C2Tx MXene hybrid film with homogeneously distributed B4C particles exhibits high mechanical flexibility and anomalous neutron-shielding properties. Layered and solution-processable 2D Ti3C2Tx MXene flakes serve as an ideal robust and flexible matrix for high-content B4C fillers (60 wt.%). In addition, the preparation of a scalable neutron shielding MXene/B4C hybrid paint is demonstrated. This composite can be directly integrated with various large-scale surfaces (e.g., stainless steel, glass, and nylon). Because of their low thickness, simple and scalable preparation method, and an absorption capacity of 39.8% for neutrons emitted from a 241Am-9Be source, the 2D Ti3C2Tx MXene hybrid films are promising candidates for use in wearable and lightweight applications.

Recognition of walking directional intention employed ground reaction forces and center of pressure during gait initiation.

BACKGROUND: Movement intentions are generally classified by Electroencephalogram (EEG) and have been used in gait initiation prediction. However, it is not easy to collect EEG data and practical in reality. Alternatively, ground reaction force (GRF) and the center of pressure (COP) is produced by the contact between the foot and the ground during a specific period of walking, which are the characteristics of evaluating gait performance RESEARCH QUESTION: The study aims to use a deep learning technique to recognize the data of the COP and GRF to classify straight walking and right turn. Second, the study aims to reveal gait characteristics that could replace EEG to predict walking directional intentions METHODS: Ten healthy male adults were instructed to stand on the force platform and self-selected to perform three conditions: standstill, straight walking, and right turn. The onset of gait initiation was evaluated by muscle activation of the right tibialis anterior, and EEG and the COP displacement evaluated the onset of gait intention. Subsequently, GRF and COP would be treated as features to classify the gait intention in the Long Short-Term Memory (LSTM) model. RESULTS: The results revealed that the onset of EEG and the COP displacement initiation were statistically significant differences between straight walking and right turn. For the classification, the average accuracy of the LSTM model with GRF and COP as features reached the highest one, 94.79 %, depending on the heel- or toe-off of the swing leg. The results indicated that gait intentions could be classified based on the GRF and COP. SIGNIFICANCE: The machine learning technique of LSTM with gait parameters can recognize the gait intention of changing walking orientation. Our model and approach would be expected to provide advanced predictions, such as exoskeleton control or pedestrian traffic flow.

Robotic Ankle Training Improves Sensorimotor Functions in Children with Cerebral Palsy-A Pilot Study.

Children with cerebral palsy (CP) have sensorimotor impairments including weakness, spasticity, reduced motor control and sensory deficits. Proprioceptive dysfunction compounds the decreased motor control and mobility. The aims of this paper were to (1) examine proprioceptive deficit of lower extremities of children with CP; (2) study improvement in proprioception and clinical impairments through robotic ankle training (RAT). Eight children with CP participated in a 6-week RAT with pre and post ankle proprioception, clinical, biomechanical assessment compared to the assessment of eight typically developing children (TDC). The children with CP participated in passive stretching (20 min/session) and active movement training (20 to 30 min/session) using an ankle rehabilitation robot (3 sessions/week over 6 weeks, total of 18 sessions). Proprioceptive acuity measured as the plantar and dorsi-flexion motion at which the children recognized the movement was 3.60 ± 2.28° in dorsiflexion and -3.72 ± 2.38° in plantar flexion for the CP group, inferior to that of the TDC group's 0.94 ± 0.43° in dorsiflexion (p = 0.027) and -0.86 ± 0.48° in plantar flexion (p = 0.012). After training, ankle motor and sensory functions were improved in children with CP, with the dorsiflexion strength increased from 3.61 ± 3.75 Nm to 7.48 ± 2.75 Nm (p = 0.018) and plantar flexion strength increased from -11.89 ± 7.04 Nm to -17.61 ± 6.81 Nm after training (p = 0.043). The dorsiflexion AROM increased from 5.58 ± 13.18° to 15.97 ± 11.21° (p = 0.028). The proprioceptive acuity showed a trend of decline to 3.08 ± 2.07° in dorsiflexion and to -2.59 ± 1.94° in plantar flexion (p > 0.05). The RAT is a promising intervention for children with CP to improve sensorimotor functions of the lower extremities. It provided an interactive and motivating training to engage children with CP in rehabilitation to improve clinical and sensorimotor performance.

3D Reconstruction Using 3D Registration-Based ToF-Stereo Fusion.

Depth sensing is an important issue in many applications, such as Augmented Reality (AR), eXtended Reality (XR), and Metaverse. For 3D reconstruction, a depth map can be acquired by a stereo camera and a Time-of-Flight (ToF) sensor. We used both sensors complementarily to improve the accuracy of 3D information of the data. First, we applied a generalized multi-camera calibration method that uses both color and depth information. Next, depth maps of two sensors were fused by 3D registration and reprojection approach. Then, hole-filling was applied to refine the new depth map from the ToF-stereo fused data. Finally, the surface reconstruction technique was used to generate mesh data from the ToF-stereo fused pointcloud data. The proposed procedure was implemented and tested with real-world data and compared with various algorithms to validate its efficiency.

Targeted next-generation sequencing for comprehensive genetic analysis of external apical root resorption during orthodontic treatment with premolar extraction in the Korean population.

INTRODUCTION: External apical root resorption (EARR) is one of the most common unfavorable consequences of orthodontic treatment and causes loss of tooth structure. The present study aimed to investigate the genetics of EARR using next-generation sequencing comprehensively. METHODS: Targeted next-generation sequencing was performed for comprehensive genetic analysis of 118 Korean orthodontic patients. The patients were divided into 2 groups on the basis of their EARR value. The association of clinical and genetic parameters with EARR was assessed using the χ2 test or t test for matched pairs, followed by Bonferroni correction and linear regression analysis. In addition, haplotype analysis and in silico prediction were conducted to evaluate functional effects. RESULTS: No statistically significant difference was observed between clinical and treatment-related parameters and EARR. The single nucleotide polymorphisms SPP1 rs9138 (P = 0.001) and SFRP2 rs3810765 (P = 0.04) showed only nominal significance between EARR groups. However, these 2 SNPs were not significant after Bonferroni correction for multiple testing (cutoff P = 0.05/142 = 3.52 × 10-4). Variations in SPP1 rs9138 and SFRP2 rs3810765 may be related to EARR during orthodontic treatment. In summary, not only genes related to inflammatory reactions but also those related to Wnt signaling to affect the degree of EARR during orthodontic teeth movement.

Multiple inertial measurement unit combination and location for recognizing general, fatigue, and simulated-fatigue gait.

BACKGROUND: Muscle fatigue of the lower limbs results in dynamic imbalance and gait instability, increasing the risk of falling. However, people might slow walk without physical muscle fatigue due to mental fatigue. Wearable inertial measurement units (IMU) and machine learning approaches have been well employed for recognizing human activities. RESEARCH QUESTION: The study aims to use a machine learning technique to recognize the data collected from IMUs for physically fatigued or slow-walking gaits. Second, the study aims to reveal the location or the number of IMUs can have the best performance. METHODS: Sixteen healthy adults with six IMUs attached to their heels, toes, sacrum, and head participated in the experiment. On the first day, the participants were instructed to walk along a hallway before and after the fatigue protocol as the Pre- and Post-fatigue gait. On the second day, the participants were instructed to walk along a hallway following the beat of their fatigue gait cadence measured on the first day as the simulated cadence (SC) gait. Gait cycles of each condition were segmented as the inputs of the Long Short-Term Memory (LSTM) model for recognization. RESULTS: The result revealed that the LSTM model could recognize the gait of simulated cadence with the highest accuracy among these three gaits. For the signal body part, the highest accuracy was 93.20 % observed at the IMUs of toes. For the best combination, the IMUs of toes and sacrum achieved the highest accuracy of 95.71 %. SIGNIFICANCE: The machine learning technique of LSTM with one or more IMUs can recognize the gait under normal, physical fatigue, or simulated cadence without muscle fatigue. Our model and approach would be expected to provide conditional warning in multiple fields, such as industrial safety for potential applications.

Automatic real-time occupational posture evaluation and select corresponding ergonomic assessments.

The objective is to develop a system to automatically select the corresponding assessment scales and calculate the score of the risk based on the joint angle information obtained from the imaged process (OpenPose) via image-based motion capture technology. Current occupational assessments, for example, REBA, RULA, and OWAS were used to evaluate the risk of musculoskeletal disorders. However, the assessment result would not be reported immediately. Introducing real-time occupational assessments in different working environments will be helpful for occupational injury prevention. In this study, the decision tree was developed to select the most appropriate assessment method according to the joint angles derived by OpenPose image process. Fifteen operation videos were tested and these videos can be classified into six types including maintenance, handling, assembly, cleaning, office work, and driving. The selected ergonomic assessment method by our developed decision tree in each condition are consistent with the recommendation of the Labour Research Institute. Moreover, the high-risk posture could be identified immediately and provide to the inspector for further evaluation on this posture rather than the whole operation period. This approach provides a quick inspection of the operation movements to prevent musculoskeletal injuries and enhances the application of the scale assessment method in different industrial environments.

Integrated Physiological, Biomechanical, and Subjective Responses for the Selection of Assistive Level in Pedelec Cycling.

In recent decade, pedelec has become one of the most popular transportation modes due to its effectiveness in reducing physical effort. The effects of using pedelec as an alternative mode of exercise were explored in previous studies. However, the effects of pedelec parameters were not quantified for the self-selected gear ratio, random riding speed, and varied road slopes, which restricted its application. Hence, this study aimed to evaluate the effects of gear ratio and assistive torque and to determine the optimum riding condition regarding physiological, biomechanical, and subjective responses of the rider. The riding tests consisted of simulated slope (1.0 vs. 2.5% grade), gear ratio (light vs. heavy), and assistive levels (0.5, 1, 1.5, and 2), and the tests were conducted in a randomized order. A total of 19 non-athletes completed the riding tests to evaluate physiological [metabolic equivalent of task (MET), heart rate, and gross efficiency (GE)], biomechanical [muscle activity (expressed as reference voluntary contraction, RVC) and power output], and subjective responses [rating of perceived exertion (RPE) and sense of comfort (SC)]. The test conditions induced moderate to vigorous intensities (3.7-7.4 METs, 58.5-80.3% of maximal heart rate, 11.1-29.5% of RVC rectus femoris activity, and 9.4-14.2 RPEs). The effects of gear ratio and assistive level on the physiological responses were significant. Riding with the heavy gear ratio showed advantages in METs and GE. For the optimum assistive level selection, low GE and limited improvement in subjective responses suggested the impact of low-power output conditions. Overall, for the health pedelec commuters, riding with 0.75 W/kg power output with 50 rpm cadence is recommended to obtain the moderate intensity (4.7 METs) and the advantages in GE and subjective feelings. Moreover, the findings can be applied to exercise intensity control and save battery energy effectively in varying riding conditions.

Comparative Study of Markerless Vision-Based Gait Analyses for Person Re-Identification.

The model-based gait analysis of kinematic characteristics of the human body has been used to identify individuals. To extract gait features, spatiotemporal changes of anatomical landmarks of the human body in 3D were preferable. Without special lab settings, 2D images were easily acquired by monocular video cameras in real-world settings. The 2D and 3D locations of key joint positions were estimated by the 2D and 3D pose estimators. Then, the 3D joint positions can be estimated from the 2D image sequences in human gait. Yet, it has been challenging to have the exact gait features of a person due to viewpoint variance and occlusion of body parts in the 2D images. In the study, we conducted a comparative study of two different approaches: feature-based and spatiotemporal-based viewpoint invariant person re-identification using gait patterns. The first method is to use gait features extracted from time-series 3D joint positions to identify an individual. The second method uses a neural network, a Siamese Long Short Term Memory (LSTM) network with the 3D spatiotemporal changes of key joint positions in a gait cycle to classify an individual without extracting gait features. To validate and compare these two methods, we conducted experiments with two open datasets of the MARS and CASIA-A datasets. The results show that the Siamese LSTM outperforms the gait feature-based approaches on the MARS dataset by 20% and 55% on the CASIA-A dataset. The results show that feature-based gait analysis using 2D and 3D pose estimators is premature. As a future study, we suggest developing large-scale human gait datasets and designing accurate 2D and 3D joint position estimators specifically for gait patterns. We expect that the current comparative study and the future work could contribute to rehabilitation study, forensic gait analysis and early detection of neurological disorders.

Effects of assistive devices on postural control following a balance disturbance along the anterior-posterior direction.

BACKGROUND: Assistive devices provide balance and stability to those who require a greater base of support, especially during ambulation or in tasks essential to functional daily living. In ambulatory assistive device use, center of pressure (COP) movement as one of the measurements of postural control is a factor when assessing fall risk, with an overall goal of maintaining postural equilibrium. There is a lack of research on assistive devices, such as walkers, regarding measurable outcome variables related to fall risk. The purpose of this study was to determine how much the postural control in single limb stance during a balance perturbance is affected by utilizing three different walker types designed to promote stability: the standard walker, the front-wheeled walker with straight wheels and the front-wheeled walker with caster wheels. RESEARCH QUESTION: Is postural sway control in single limb stance during a balance perturbance affected by walker type? METHODS: Twenty-three healthy adults participated and gave consent. The NeuroCom® SMART EquiTest® system was utilized to simulate forward falls. Subjects stood on the system's force plate, which was tipped backwards quickly, forcing subjects to attempt to maintain balance. Each participant experienced 18 simulated perturbations, during which they were asked to maintain balance while using one of three walkers in single-limb stance. Each trial was completed using random assignment of three different walker types. Leg dominance of the stance leg was also randomized for each trial. RESULTS: The type of walker and the leg dominance in the standing limb significantly affected postural control in a balance perturbance in the A-P direction. The walker type significantly affected the COP maximum displacement in anterior-posterior (AP) direction. However, the leg dominance significantly affected COP maximum displacement in AP and medio-lateral (ML) directions and COP velocity in AP direction. SIGNIFICANCE: The findings suggest that when fully grounded, a standard walker is more stable than the front-wheeled walker. However, this does not indicate that the standard walker is more stable than other types of walkers when it is being picked up and moved forward during normal use.

High prevalence nasal carriage of methicillin-resistant Staphylococcus aureus among long term care facility healthcare workers in relation to patient contact.

BACKGROUND: Methicillin-resistant Staphylococcus aureus (MRSA) is a major public health concern worldwide. Healthcare workers (HCWs) are an important source of transmission of MRSA. We conducted a prospective study to define the frequency of S. aureus nasal colonization with emphasis on the carriage of MRSA in HCWs in relation to the intensity of patient contact. METHODS: Out-of-hospital care emergency medical technicians and students, and HCWs in the emergency department, intensive care unit and a long-term care facility (LTCF) were enrolled to compare the prevalence of MRSA and methicillin-susceptible S. aureus (MSSA) nasal colonization. The MRSA isolates were further identified by their microbiological and molecular characteristics. FINDINGS: S. aureus was isolated from 63 of 248 HCWs (25.4%). The overall MRSA nasal carriage rate was 15/248, 6%, and the prevalence was higher in the HCWs who had worked for 5-10 years (12.8%), and among female HCWs (10.3%) than male HCWs (0.9%). LTCFs had the highest prevalence (12%). In contrast, the overall carriage of MSSA was 48/248, 19.4%, and most carriers worked for ≥5 years (52.1%). Hospital nurses had the highest rate of MSSA carriage (21.4%). Most of the MRSA isolates were SCCmec IV/ST59 or ST45 (60%), and were resistant to erythromycin and clindamycin (53%). CONCLUSIONS: Hospital nurses have highest S. aureus nasal carriage, whereas HCWs in the LTCFs comprise a significant reservoir of MRSA colonization. The differences in the characteristics of MRSA and MSSA nasal carriage among HCWs highlights the importance on long-term nasal screening of S. aureus in healthcare facilities.

Utilization of Inertial Measurement Units for Determining the Sequential Chain of Baseball Strike Posture.

The purpose of this study was to employ inertial measurement units (IMU) with an eye-tracking device to investigate different swing strategies between two levels of batters. The participants were 20 healthy males aged 20 to 30 years old, with ten professional and ten amateur batters. Eye gaze position, head, shoulder, trunk, and pelvis angular velocity, and ground reaction forces were recorded. The results showed that professional batters rotated segments more rhythmically and efficiently than the amateur group. Firstly, the professional group spent less time in the preparation stages. Secondly, the maximum angular velocity timing of each segment of the professional group was centralized in the swing cycle. Thirdly, the amateur group had significantly earlier gaze timing of the maximum angular velocity than the professional group. Moreover, the maximum angular velocity timing of the gaze was the earliest parameter among the five segments, and significantly earlier (at least 16.32% of cycle time) than the maximum angular velocity of the head, shoulder, trunk, and pelvis within the amateur group. The visual-motor coordination strategies were different between the two groups, which could successfully be determined by wearable instruments of IMU.

Slow Walking in Individuals with Chronic Post-Stroke Hemiparesis: Speed Mediated Effects of Gait Kinetics and Ankle Kinematics.

Post-stroke rehabilitation often aims to increase walking speeds, as faster walking is associated with improved functional status and quality of life. However, for successful community ambulation, ability to modulate (increase and decrease) walking speeds is more important than walking continuously at constant speeds. Increasing paretic propulsive forces to increase walking speed has been extensively examined; however, little is known about the mechanics of slow walking post-stroke. The primary purpose of this study was to identify the effects of increased and decreased walking speeds on post-stroke kinetics and ankle kinematics. Fifteen individuals with chronic post-stroke hemiparesis and 15 non-neurologically impaired controls walked over an instrumented treadmill under: slow, self-selected, and fast walking speeds. We examined the peak propulsive forces, propulsive impulse, peak braking forces, braking impulse, and ankle kinematics under each condition. When walking at slow walking speeds, paretic limbs were unable to reduce braking impulse and peak propulsive force or modulate ankle kinematics. Impaired modulation of paretic gait kinetics during slow walking places people post-stroke at high risks for slip-related falls. These findings suggest the need for developing gait retraining paradigms for slow walking in individuals chronically post-stroke that target the ability of the paretic limb to modulate braking forces.

Effects of augmented somatosensory input using vibratory insoles to improve walking in individuals with chronic post-stroke hemiparesis.

BACKGROUND: Stroke survivors suffer from hemiparesis and somatosensory impairments, which adversely impact walking performance, placing them at higher risks for trips and falls. Post-stroke, somatosensory deficits are commonly observed as impaired interpretation of afferent input and increased threshold. Diminishing or augmenting somatosensory inputs via various techniques have been demonstrated to be able to modify static and dynamic balance, postural and locomotor control in non-neurologically impaired as well as neurologically impaired individuals. RESEARCH QUESTION: We sought to investigate whether enhancing somatosensory input using vibratory insoles, can improve post-stroke gait. We hypothesized that with augmentation of somatosensory input at the soles via vibratory insoles would improve post-stroke gait via increased propulsive forces, decreased braking forces and increased ankle angle movements in the paretic legs of individuals with chronic post-stroke hemiparesis. METHODS: Fifteen individuals with chronic post-stroke hemiparesis and 15 age-similar non-neurologically impaired controls participated in this cross-sectional study. Enhanced somatosensory stimulation was delivered using a pair of tactor-embedded insoles, providing suprathreshold vibratory stimulation to the bottom of the feet. Participants walked over an instrumented treadmill with self-selected speeds, under 5 conditions: no insole in shoe (NT), insoles in shoe with no vibration (BOFF), vibration under both feet (BON), vibration under one foot only (ION, CON). Kinetics and kinematics during walking were recorded and analyzed offline. RESULTS: Suprathreshold vibratory stimulations did not alter gait kinetics under any stimulation conditions. We observed increased paretic ankle dorsiflexions in the paretic legs, when vibratory stimuli were applied unilaterally. SIGNIFICANCE: Vibratory stimulations applied at suprathreshold intensity to the bottom of the feet to augment somatosensory feedback can potentially be used as a low-cost solution to address the inadequate toe clearance during walking in people post-stroke, which is an important goal in post-stroke rehabilitation.

Effect of Light Finger Touch, a Cognitive Task, and Vision on Standing Balance in Stroke.

The aim of the exploratory study was to investigate the individual and combined effects of light finger touch, a cognitive task, and vision on postural sway in individuals with stroke. Nine older adults with stroke stood on the force platform with eyes open and eyes closed, with and without a light finger touch contact with the stationary frame, and when counting backward from a randomly chosen three-digit number or without it. The center of pressure (COP) excursion, velocity, range and sway area was calculated. Participants demonstrated significantly larger postural sway when vision was not available (p < 0.05), smaller postural sway when using a finger touch contact (p < 0.05), and increased postural sway while performing the cognitive task (p < 0.05). When finger touch and a cognitive task was performed simultaneously, body sway decreased as compared to standing and performing a cognitive task in eyes open (p < 0.05) and eyes closed conditions. Results indicate that light touch in individuals with stroke mitigates the impact of cognitive load. The findings contribute to the understanding of the role of sensory integration in balance control of individuals with neurological impairments and older adults.

Multiple Inertial Measurement Unit Combination and Location for Center of Pressure Prediction in Gait.

Center of pressure (COP) during a gait cycle indicates crucial information with regard to fall risk such as balance capacity. The drawbacks of conventional research instruments include inconvenient use during activities of daily living and expensive costs. The present study illustrates the promising fall-relevant information predicted by acceleration and angular velocity data from different placement sensors with machine learning techniques. This approach is inspired by the emerging machine learning technique, specifically the long short-term memory (LSTM), which is often used in time series data and aims to decrease the burden of the user while using the novel wearable technology. The Jaccard similarity coefficient, which implies the consistency of profile alignment between prediction and real situation, achieved 94% accuracy in the walking direction. Furthermore, the number of sensors used and the placement influenced the feasibility of an application. The outcome revealed that the accuracy could exceed 90% with only one sensor placed on the foot in the walking direction, and the toe would be the best location for sensor placement. To examine the performance of machine learning, the current study employed two parameters from different perspectives. One is a commonly used parameter, which represented the error, and the other investigated the similarity between the prediction and ground truth. From a similarity perspective, the parameter can be used as a metric to assess the consistency of profile alignment.

Immediate Effects of Anodal Transcranial Direct Current Stimulation on Postural Stability Using Computerized Dynamic Posturography in People With Chronic Post-stroke Hemiparesis.

Postural stability is commonly decreased in individuals with chronic post-stroke hemiparesis due to multisystemic deficits. Transcranial direct current stimulation (tDCS) is a non-invasive method to modulate cortical excitability, inducing neuroplastic changes to the targeted cortical areas and has been suggested to potentially improve motor functions in individuals with neurological impairments. The purpose of this double-blinded, sham-controlled study was to examine the acute effects of anodal tDCS over the lesioned motor cortex leg area with concurrent limits of stability training on postural control in individuals with chronic post-stroke hemiparesis. Ten individuals with chronic post-stroke hemiparesis received either anodal or sham tDCS stimulation over the lesioned leg region of the motor cortex while undergoing 20 min of postural training. The type of stimulation to receive during the first session was pseudorandomized, and the two sessions were separated by 14 days. Before and immediately after 20 min of tDCS, the 10 m walk test, the Berg Balance Scale, and dynamic posturography assessments were performed. After a single session of anodal tDCS with concurrent postural training, we observed no changes in clinical measures of balance and walking, assessed using the Berg Balance Scale and 10 m walk test. For dynamic posturography assessments, participants demonstrated improvements in adaptation responses to toes-up and toes-down perturbations, regardless of the type of tDCS received. Additionally, improved performance in the shifting center of gravity was observed during anodal tDCS. Taken together, these preliminary findings suggest that tDCS can potentially be used as a feasible approach be incorporated into the rehabilitation of chronic post-stroke individuals with issues related to postural control and fear of falling, and that multiple sessions of tDCS stimulation may be needed to improve functional measures of postural control and walking.

Global fitness landscapes of the Shine-Dalgarno sequence.

Shine-Dalgarno sequences (SD) in prokaryotic mRNA facilitate protein translation by pairing with rRNA in ribosomes. Although conventionally defined as AG-rich motifs, recent genomic surveys reveal great sequence diversity, questioning how SD functions. Here, we determined the molecular fitness (i.e., translation efficiency) of 49 synthetic 9-nt SD genotypes in three distinct mRNA contexts in Escherichia coli We uncovered generic principles governing the SD fitness landscapes: (1) Guanine contents, rather than canonical SD motifs, best predict the fitness of both synthetic and endogenous SD; (2) the genotype-fitness correlation of SD promotes its evolvability by steadily supplying beneficial mutations across fitness landscapes; and (3) the frequency and magnitude of deleterious mutations increase with background fitness, and adjacent nucleotides in SD show stronger epistasis. Epistasis results from disruption of the continuous base pairing between SD and rRNA. This "chain-breaking" epistasis creates sinkholes in SD fitness landscapes and may profoundly impact the evolution and function of prokaryotic translation initiation and other RNA-mediated processes. Collectively, our work yields functional insights into the SD sequence variation in prokaryotic genomes, identifies a simple design principle to guide bioengineering and bioinformatic analysis of SD, and illuminates the fundamentals of fitness landscapes and molecular evolution.