Trajectory Following Control of an Unmanned Vehicle for Marine Environment Sensing.

An autonomous surface vehicle is indispensable for sensing of marine environments owing to its challenging and dynamic conditions. To accomplish this task, the vehicle has to navigate through a desired trajectory. However, due to the complexity and dynamic nature of a marine environment affected by factors such as ocean currents, waves, and wind, a robust controller is of paramount importance for maintaining the vehicle along the desired trajectory by minimizing the trajectory error. To this end, in this study, we propose a robust discrete-time super-twisting second-order sliding mode controller (DSTA). Besides, this control method effectively suppresses the chattering effect. To start with, the vehicle's model is discretized using an integral approximation with nonlinear terms including environmental disturbances treated as perturbation terms. Then, the perturbation is estimated using a time delay estimator (TDE), which further enhances the robustness of the proposed method and allows us to choose smaller controller gains. Moreover, we employ a genetic algorithm (GA) to tune the controller gains based on a quadratic cost function that considers the tracking error and control energy. The stability of the proposed sliding mode controller (SMC) is rigorously demonstrated using a Lyapunov approach. The controller is implemented using the Simulink® software. Finally, a conventional discrete-time SMC based on the reaching law (DSMR) and a heuristically tuned DSTA controller are used as benchmarks to compare the tracking accuracy and chattering attenuation capability of the proposed GA based DSTA (GA-DSTA). Simulation results are presented both with or without external disturbances. The simulation results demonstrate that the proposed controller drives the vehicle along the desired trajectory successfully and outperforms the other two controllers.

Comparative Effects of 4 Single-Leg Squat Exercises in Subjects With Gluteus Medius Weakness.

CONTEXT: Of the weight-bearing exercises, single-leg squats (SLSs) represent one of the most commonly used hip-strengthening exercises that require more gluteus medius (GMED) activity. To date, no studies have investigated how the 4 SLS exercises affect muscle imbalance of GMED, tensor fasciae latae (TFL), and adductor longus (AL), and kinematics of hip. OBJECTIVE: To investigate the hip muscle activities, onset time, and kinematics during 4 different SLS exercises (unilateral squat, unilateral wall-squat [UWS], lateral step-down, and front step-down) in subjects with GMED weakness. DESIGN: Repeated-measures experimental design. SETTING: Research laboratory. PARTICIPANTS: Twenty-two subjects (11 males and 11 females) participated in this study and were compared using 1-way repeated-measures analysis of variance. MAIN OUTCOME MEASURES: Surface electromyography was used to measure the muscle activities and onset time of the GMED, TFL, and AL, and 3-dimensional motion tracking system was used to measure the hip adduction and internal/external rotation angles during SLS exercises. One-way repeated-measures analysis of variance was used at a significance level of P < .05. RESULTS: The UWS produced higher GMED/TFL activity ratio and lower GMED/TFL onset time ratio than in the other 3 exercises (P < .05). No difference in GMED/AL activity ratio and GMED/AL onset time ratio was observed. The hip adduction angle was greater in UWS than in the other 3 exercises (P < .05). As for the hip internal/external rotation, lateral step-down exhibited higher hip internal rotation angle than front step-down (P < .05). CONCLUSION: The UWS may be recommended as an effective exercise for the subjects with GMED weakness, but they should take care to avoid excessive hip adduction during the exercise.

Block and Random Practice: A Wii Fit Dynamic Balance Training in Older Adults.

Purpose: To compare the effectiveness of blocked and random practice schedules of balance training in dynamic balance abilities of older adults using Wii Fit balance game tasks. Method: Forty-one participants who were not receiving hospice care or living in a nursing home participated. Three Wii Fit balance tasks (tasks A, B, and C) were selected for training, and one task (task D) was selected as the transfer test among the nine tasks in the Wii Fit balance game software. Scores for tasks A and D were evaluated. Completion times for tasks B and C were evaluated. Moved distance for the functional reach test (FRT), completion time for the timed up and go test (TUG), and performance score for the Tinetti performance-oriented mobility assessment (POMA) were also tested as clinical balance assessment outcomes. Results: The training significantly improved the performance outcomes of clinical balance assessments and task D. There were no significant group × time interaction effects and no significant main effects by group during the acquisition and retention periods of tasks A, B, and C. However, significant main effects by time were observed for tasks A, B, and C. Conclusions: When dynamic balance training such as the Wii Fit balance system is administered to older adults in a clinical setting, either a block or a random practice schedule can be effectively used to improve the dynamic balance skills. Wii Fit-based balance training is clinically effective for improving the dynamic balance ability.

Locomotor imagery training improves gait performance in people with chronic hemiparetic stroke: a controlled clinical trial.

OBJECTIVE: The purpose of this study was to evaluate whether locomotor imagery training leads to clinical improvements in gait after stroke. DESIGN: Pretest-posttest matched control design. PARTICIPANTS: A total of 24 people with chronic hemiparetic stroke (13 for experimental and 11 for control) were recruited in this study. INTERVENTIONS: The subjects in the experimental group participated in videotape-based locomotor imagery training five days a week for four weeks. They also conducted regular physical therapy. OUTCOME MEASURES: Kinematic gait parameters were collected using a three-dimensional motion analysis system. Functional gait performance was assessed using clinical measures: Activities-specific Balance Confidence Scale, Berg Balance Test, Dynamic Gait Index and modified Emory Functional Ambulation Profile. RESULTS: After training, walking velocity increased 0.07 +/- 0.06 m/s in the experimental group and 0.01 +/- 0.07 m/s in the control group. In the experimental group, the affected and less affected limb stride lengths increased by 0.09 +/- 0.12 m and 0.10 +/- 0.07 m respectively, whereas in the control group they decreased by 0.00 +/- 0.04 m and increased by 0.02 +/- 0.06 m, respectively. Kinematic parameters in the lower extremity joints during walking were more improved after the training in the experimental group. Confidence in balance, postural control, dynamic balance and performance time for different environmental walking situations were also improved more in the experimental group. CONCLUSION: Locomotor imagery training can be considered as a useful option for restoration of ambulation for individuals with chronic hemiparetic stroke who are unable to participate in physical gait training.

Novel vehicle detection system based on stacked DoG kernel and AdaBoost.

This paper proposes a novel vehicle detection system that can overcome some limitations of typical vehicle detection systems using AdaBoost-based methods. The performance of the AdaBoost-based vehicle detection system is dependent on its training data. Thus, its performance decreases when the shape of a target differs from its training data, or the pattern of a preceding vehicle is not visible in the image due to the light conditions. A stacked Difference of Gaussian (DoG)-based feature extraction algorithm is proposed to address this issue by recognizing common characteristics, such as the shadow and rear wheels beneath vehicles-of vehicles under various conditions. The common characteristics of vehicles are extracted by applying the stacked DoG shaped kernel obtained from the 3D plot of an image through a convolution method and investigating only certain regions that have a similar patterns. A new vehicle detection system is constructed by combining the novel stacked DoG feature extraction algorithm with the AdaBoost method. Experiments are provided to demonstrate the effectiveness of the proposed vehicle detection system under different conditions.

Augmented effects of EMG biofeedback interfaced with virtual reality on neuromuscular control and movement coordination during reaching in children with cerebral palsy.

BACKGROUND: The purpose of the present study was to compare therapeutic effects of an electromyography (EMG) biofeedback augmented by virtual reality (VR) and EMG biofeedback alone on the triceps and biceps (T:B) muscle activity imbalance and elbow joint movement coordination during a reaching motor taskOBJECTIVE: To compare therapeutic effects of an electromyography (EMG) biofeedback augmented by virtual reality (VR) and EMG biofeedback alone on the triceps and biceps muscle activity imbalance and elbow joint movement coordination during a reaching motor task in normal children and children with spastic cerebral palsy (CP). METHODS: 18 children with spastic CP (2 females; mean±standard deviation = 9.5 ± 1.96 years) and 8 normal children (3 females; mean ± standard deviation = 9.75 ± 2.55 years) were recruited from a local community center. All children with CP first underwent one intensive session of EMG feedback (30 minutes), followed by one session of the EMG-VR feedback (30 minutes) after a 1-week washout period. Clinical tests included elbow extension range of motion (ROM), biceps muscle strength, and box and block test. EMG triceps and biceps (T:B) muscle activity imbalance and reaching movement acceleration coordination were concurrently determined by EMG and 3-axis accelerometer measurements respectively. Independent t-test and one-way repeated analysis of variance (ANOVA) were performed at p < 0.05. RESULTS: The one-way repeated ANOVA was revealed to be significantly effective in elbow extension ROM (p = 0.01), biceps muscle strength (p = 0.01), and box and block test (p = 0.03). The one-way repeated ANOVA also revealed to be significantly effective in the peak triceps muscle activity (p = 0.01). However, one-way repeated ANOVA produced no statistical significance in the composite 3-dimensional movement acceleration coordination data (p = 0.12). CONCLUSIONS: The present study is a first clinical trial that demonstrated the superior benefits of the EMG biofeedback when augmented by virtual reality exercise games in children with spastic CP. The augmented EMG and VR feedback produced better neuromuscular balance control in the elbow joint than the EMG biofeedback alone.

Effects of Innovative WALKBOT Robotic-Assisted Locomotor Training on Balance and Gait Recovery in Hemiparetic Stroke: A Prospective, Randomized, Experimenter Blinded Case Control Study With a Four-Week Follow-Up.

The present clinical investigation was to ascertain whether the effects of WALKBOT-assisted locomotor training (WLT) on balance, gait, and motor recovery were superior or similar to the conventional locomotor training (CLT) in patients with hemiparetic stroke. Thirty individuals with hemiparetic stroke were randomly assigned to either WLT or CLT. WLT emphasized on a progressive, conventional locomotor retraining practice (40 min) combined with the WALKBOT-assisted, haptic guidance and random variable locomotor training (40 min) whereas CLT involved conventional physical therapy alone (80 min). Both intervention dosages were standardized and provided for 80 min, five days/week for four weeks. Clinical outcomes included function ambulation category (FAC), Berg balance scale (BBS), Korean modified Barthel index (K-MBI), modified Ashworth scale (MAS), and EuroQol-5 dimension (EQ-5D) before and after the four-week program as well as at follow-up four weeks after the intervention. Two-way repeated measure ANOVA showed significant interaction effect (time × group) for FAC (p=0.02), BBS (p=0.03) , and K-MBI (p=0.00) across the pre-training, post-training, and follow-up tests, indicating that WLT was more beneficial for balance, gait and daily activity function than CLT alone. However, no significant difference in other variables was observed. This is the first clinical trial that highlights the superior, augmented effects of the WALKBOT-assisted locomotor training on balance, gait and motor recovery when compared to the conventional locomotor training alone in patients with hemiparetic stroke.

Innovative strength training-induced neuroplasticity and increased muscle size and strength in children with spastic cerebral palsy: an experimenter-blind case study--three-month follow-up.

BACKGROUND: In children with cerebral palsy (CP), the never-learned-to-use (NLTU) effect and underutilization suppress the normal development of cortical plasticity in the paretic limb, which further inhibits its functional use and increases associated muscle weakness. OBJECTIVE: To highlight the effects of a novel comprehensive hand repetitive intensive strengthening training system on neuroplastic changes associated with upper extremity (UE) muscle strength and motor performance in children with spastic hemiplegic CP. METHOD: Two children with spastic hemiplegic CP were recruited. Intervention with the comprehensive hand repetitive intensive strengthening training system was provided for 60 min a day, three times a week, for 10 weeks. Neuroplastic changes, muscle size, strength, and associated motor function were measured using functional magnetic resonance imaging (MRI), ultrasound imaging, and standardized motor tests, respectively. RESULTS: The functional MRI data showed that the comprehensive hand repetitive intensive strengthening training intervention produced measurable neuroplastic changes in the neural substrates associated with motor control and learning. These neuroplastic changes were associated with increased muscle size, strength and motor function. CONCLUSIONS: These results provide compelling evidence of neuroplastic changes and associated improvements in muscle size and motor function following innovative upper extremity strengthening exercise.

Novel algorithm for the hemiplegic gait evaluation using a single 3-axis accelerometer.

This paper suggests the novel algorithm for the estimating gait parameters of the hemiplegic patients using a 3-axis accelerometer. The signal processing for algorithm consists of a bandpass filter and a least square acceleration filter. To evaluate the performance of the algorithm, the correlation coefficients of the stride and the step time between the 3-axis accelerometer and the Vicon motion analysis system are compared. In consequence, correlation coefficient ranged from 0.90 to 0.99 for patients and ranged from 0.92 to 0.99 for normal subjects. The results showed that the novel algorithm is very useful for estimating not only hemiplegic gait but also normal gait.