Testicular histopathology in rats co-exposed to heat and psychological stressors.

Objectives: The present study aimed to investigate the effect of co-exposure to heat and psychological stressors on testicular tissue as one of the major male reproductive organs in rats. Methods: Forty adult male Wistar rats were divided into four groups of 10 animals each. The first group was exposed to heat stress (Temperature Humidity Index: 57.75 ± 3), the second group was exposed to three psychological stressors including strobe light ultrasonic sound, and tilting cage, and the third group was co-exposed to both heat and psychological stress daily. The order of exposure to various psychological stressors was randomized. Following the last day of the 40 -day exposure, the rats were euthanized and their testicular tissues were fixed in Bouin's solution. Moreover, a tissue processor, a microtome as well as hematoxylin, and eosin staining were used for tissue preparation. Results: The co-exposure to psychological and heat stress can cause negative testis histopathological changes including spermatid retention, degeneration of round spermatids and spermatocytes, degeneration and depletion of elongated Spermatid, Sertoli cell status, tubular degeneration/atrophy, Leydig cell atrophy, tubular dilatation, re-tubular dilation, and sclerosis status in a number of rats. Moreover, the histopathological changes were higher in the group exposed to heat stress compared with those exposed to psychological stress. Conclusions: Although exposure to either stressor alone can affect testicular tissue as part of the reproductive system, co-exposure to both stressors may result in an increased risk of adverse effects on testicular tissue.

Effect of Co-exposure to Heat and Psychological Stressors on Sperm DNA and Semen Parameters.

The present study aims to investigate the effects of co-exposure to heat and psychological stress on sperm DNA and semen parameters among male rats. The study was conducted on 40 healthy adult male Wistar rats. The rats were randomly categorized into four groups of same size consisting of a control group, a heat stress, psychological and co-exposure groups. The heat stress group was exposed to a temperature of 36 °C at 20% relative humidity. The psychological stress exposure group was subjected to three stressors including exposure to strobe light, noise and tilting cage. According the results,the co-exposure group had lower mean sperm parameters including sperm count (17.22 ± 4.22 106/ml), motility (42.63 ± 12.95 %), viability (48.50 ± 23.25 %), normal morphology (56 ± 7.5%), progressive motility (11.61 ± 7.81%), non-progressive motility (31.18 ± 7.77%), curvilinear velocity (24.11 ± 3.81 µm/s) and straight-line velocity (3.2 ± 1.4 µm/s) when compared with those of the other groups (P = 0.001). Mean sperm immobility (57.36 ± 12.95%) and non-progressive motility (37.93 ± 11.15%) in the co-exposure group was higher compared to the other groups (P = 0.001 and P = 0.333, respectively). Assessment of damage to sperm DNA revealed that the heat exposure group had a higher percentage of sperm DNA damage (9.44 ± 6.80 %) compared to others (P = 0.185). In case of all of exposure scenario, the chance that the semen quality decreased compared to the control group has been increased. In general the combined stress had a greater significant effect on sperm parameters compared to other exposure groups, except for DNA damage.

Error-augmented bimanual therapy for stroke survivors.

BACKGROUND: Stroke recovery studies have shown the efficacy of bimanual training on upper limb functional recovery and others have shown the efficacy of feedback technology that augments error. OBJECTIVE: In a double-blinded randomized controlled study (N = 26), we evaluated the short-term effects of bilateral arm training to foster functional recovery of a hemiparetic arm, with half of our subjects unknowingly also receiving error augmentation (where errors were visually and haptically enhanced by a robot). METHODS: Twenty-six individuals with chronic stroke were randomly assigned to practice an equivalent amount of bimanual reaching either with or without error augmentation. Participants were instructed to coordinate both arms while reaching to two targets (one for each arm) in three 45-minute treatments per week for two weeks, with a follow-up visit after one week without treatment. RESULTS: Subjects' 2-week gains in Fugl-Meyer score averaged 2.92, and we also observed improvements Wolf Motor Functional Ability Scale average 0.21, and Motor Activity Log of 0.58 for quantity and 0.63 for quality of life scores. The extra benefit of error augmentation over the three weeks became apparent in Fugl-Meyer score only after removing an outlier from consideration. CONCLUSIONS: This modest advantage of error augmentation was detectable over a short interval encouraging further research in interactive self-rehabilitation systems that can enhance error motor recovery.

Learning new movements after paralysis: Results from a home-based study.

Body-machine interfaces (BMIs) decode upper-body motion for operating devices, such as computers and wheelchairs. We developed a low-cost portable BMI for survivors of cervical spinal cord injury and investigated it as a means to support personalized assistance and therapy within the home environment. Depending on the specific impairment of each participant, we modified the interface gains to restore a higher level of upper body mobility. The use of the BMI over one month led to increased range of motion and force at the shoulders in chronic survivors. Concurrently, subjects learned to reorganize their body motions as they practiced the control of a computer cursor to perform different tasks and games. The BMI allowed subjects to generate any movement of the cursor with different motions of their body. Through practice subjects demonstrated a tendency to increase the similarity between the body motions used to control the cursor in distinct tasks. Nevertheless, by the end of learning, some significant and persistent differences appeared to persist. This suggests the ability of the central nervous system to concurrently learn operating the BMI while exploiting the possibility to adapt the available mobility to the specific spatio-temporal requirements of each task.

Body-Machine Interface Enables People With Cervical Spinal Cord Injury to Control Devices With Available Body Movements: Proof of Concept.

This study tested the use of a customized body-machine interface (BoMI) for enhancing functional capabilities in persons with cervical spinal cord injury (cSCI). The interface allows people with cSCI to operate external devices by reorganizing their residual movements. This was a proof-of-concept phase 0 interventional nonrandomized clinical trial. Eight cSCI participants wore a custom-made garment with motion sensors placed on the shoulders. Signals derived from the sensors controlled a computer cursor. A standard algorithm extracted the combinations of sensor signals that best captured each participant's capacity for controlling a computer cursor. Participants practiced with the BoMI for 24 sessions over 12 weeks performing 3 tasks: reaching, typing, and game playing. Learning and performance were evaluated by the evolution of movement time, errors, smoothness, and performance metrics specific to each task. Through practice, participants were able to reduce the movement time and the distance from the target at the 1-second mark in the reaching task. They also made straighter and smoother movements while reaching to different targets. All participants became faster in the typing task and more skilled in game playing, as the pong hit rate increased significantly with practice. The results provide proof-of-concept for the customized BoMI as a means for people with absent or severely impaired hand movements to control assistive devices that otherwise would be manually operated.

Static Versus Dynamic Decoding Algorithms in a Non-Invasive Body-Machine Interface.

In this study, we consider a non-invasive body-machine interface that captures body motions still available to people with spinal cord injury (SCI) and maps them into a set of signals for controlling a computer user interface while engaging in a sustained level of mobility and exercise. We compare the effectiveness of two decoding algorithms that transform a high-dimensional body-signal vector into a lower dimensional control vector on six subjects with high-level SCI and eight controls. One algorithm is based on a static map from current body signals to the current value of the control vector set through principal component analysis (PCA), the other on dynamic mapping a segment of body signals to the value and the temporal derivatives of the control vector set through a Kalman filter. SCI and control participants performed straighter and smoother cursor movements with the Kalman algorithm during center-out reaching, but their movements were faster and more precise when using PCA. All participants were able to use the BMI's continuous, two-dimensional control to type on a virtual keyboard and play pong, and performance with both algorithms was comparable. However, seven of eight control participants preferred PCA as their method of virtual wheelchair control. The unsupervised PCA algorithm was easier to train and seemed sufficient to achieve a higher degree of learnability and perceived ease of use.

The Statistical Determinants of the Speed of Motor Learning.

It has recently been suggested that movement variability directly increases the speed of motor learning. Here we use computational modeling of motor adaptation to show that variability can have a broad range of effects on learning, both negative and positive. Experimentally, we also find contributing and decelerating effects. Lastly, through a meta-analysis of published papers, we verify that across a wide range of experiments, movement variability has no statistical relation with learning rate. While motor learning is a complex process that can be modeled, further research is needed to understand the relative importance of the involved factors.

Upper Body-Based Power Wheelchair Control Interface for Individuals With Tetraplegia.

Many power wheelchair control interfaces are not sufficient for individuals with severely limited upper limb mobility. The majority of controllers that do not rely on coordinated arm and hand movements provide users a limited vocabulary of commands and often do not take advantage of the user's residual motion. We developed a body-machine interface (BMI) that leverages the flexibility and customizability of redundant control by using high dimensional changes in shoulder kinematics to generate proportional control commands for a power wheelchair. In this study, three individuals with cervical spinal cord injuries were able to control a power wheelchair safely and accurately using only small shoulder movements. With the BMI, participants were able to achieve their desired trajectories and, after five sessions driving, were able to achieve smoothness that was similar to the smoothness with their current joystick. All participants were twice as slow using the BMI however improved with practice. Importantly, users were able to generalize training controlling a computer to driving a power wheelchair, and employed similar strategies when controlling both devices. Overall, this work suggests that the BMI can be an effective wheelchair control interface for individuals with high-level spinal cord injuries who have limited arm and hand control.

Remapping residual coordination for controlling assistive devices and recovering motor functions.

The concept of human motor redundancy attracted much attention since the early studies of motor control, as it highlights the ability of the motor system to generate a great variety of movements to achieve any well-defined goal. The abundance of degrees of freedom in the human body may be a fundamental resource in the learning and remapping problems that are encountered in human-machine interfaces (HMIs) developments. The HMI can act at different levels decoding brain signals or body signals to control an external device. The transformation from neural signals to device commands is the core of research on brain-machine interfaces (BMIs). However, while BMIs bypass completely the final path of the motor system, body-machine interfaces (BoMIs) take advantage of motor skills that are still available to the user and have the potential to enhance these skills through their consistent use. BoMIs empower people with severe motor disabilities with the possibility to control external devices, and they concurrently offer the opportunity to focus on achieving rehabilitative goals. In this study we describe a theoretical paradigm for the use of a BoMI in rehabilitation. The proposed BoMI remaps the user's residual upper body mobility to the two coordinates of a cursor on a computer screen. This mapping is obtained by principal component analysis (PCA). We hypothesize that the BoMI can be specifically programmed to engage the users in functional exercises aimed at partial recovery of motor skills, while simultaneously controlling the cursor and carrying out functional tasks, e.g. playing games. Specifically, PCA allows us to select not only the subspace that is most comfortable for the user to act upon, but also the degrees of freedom and coordination patterns that the user has more difficulty engaging. In this article, we describe a family of map modifications that can be made to change the motor behavior of the user. Depending on the characteristics of the impairment of each high-level spinal cord injury (SCI) survivor, we can make modifications to restore a higher level of symmetric mobility (left versus right), or to increase the strength and range of motion of the upper body that was spared by the injury. Results showed that this approach restored symmetry between left and right side of the body, with an increase of mobility and strength of all the degrees of freedom in the participants involved in the control of the interface. This is a proof of concept that our BoMI may be used concurrently to control assistive devices and reach specific rehabilitative goals. Engaging the users in functional and entertaining tasks while practicing the interface and changing the map in the proposed ways is a novel approach to rehabilitation treatments facilitated by portable and low-cost technologies.

Assistive Robotic Manipulation through Shared Autonomy and a Body-Machine Interface.

Assistive robotic manipulators have the potential to improve the lives of people with motor impairments. They can enable individuals to perform activities such as pick-and-place tasks, opening doors, pushing buttons, and can even provide assistance in personal hygiene and feeding. However, robotic arms often have more degrees of freedom (DoF) than the dimensionality of their control interface, making them challenging to use-especially for those with impaired motor abilities. Our research focuses on enabling the control of high-DoF manipulators to motor-impaired individuals for performing daily tasks. We make use of an individual's residual motion capabilities, captured through a Body-Machine Interface (BMI), to generate control signals for the robotic arm. These low-dimensional controls are then utilized in a shared-control framework that shares control between the human user and robot autonomy. We evaluated the system by conducting a user study in which 6 participants performed 144 trials of a manipulation task using the BMI interface and the proposed shared-control framework. The 100% success rate on task performance demonstrates the effectiveness of the proposed system for individuals with motor impairments to control assistive robotic manipulators.

Multivariate outcomes in a three week bimanual self-telerehabilitation with error augmentation post-stroke.

We present the outcomes of a study on stroke patients in a 3-week intervention of bimanual self-telerehabilitation. This training is similar to an upper-extremity treadmill in that patients can make use of their healthy arm to provide a cue for the more impaired arm. We further inspected a cohort that covertly received error augmentation training while they practiced. Finally, we focused here on the many quantitative measures available from the robotic device, testing if these measures collectively can predict outcome on the final day. We found in a cross-validation study that predictions are possible, yielding median r-squared values over 99%. Several particular measures were found to dominate their contribution to the prediction of recoverability. These results show that interactive self-rehabilitation may be a viable method for motor restoration, and the quantitative metrics available can be used to predict the eventual state of recovery.

Error augmentation enhancing arm recovery in individuals with chronic stroke: a randomized crossover design.

BACKGROUND: Neurorehabilitation studies suggest that manipulation of error signals during practice can stimulate improvement in coordination after stroke. OBJECTIVE: To test visual display and robotic technology that delivers augmented error signals during training, in participants with stroke. METHODS: A total of 26 participants with chronic hemiparesis were trained with haptic (via robot-rendered forces) and graphic (via a virtual environment) distortions to amplify upper-extremity (UE) tracking error. In a randomized crossover design, the intervention was compared with an equivalent amount of practice without error augmentation (EA). Interventions involved three 45-minute sessions per week for 2 weeks, then 1 week of no treatment, and then 2 additional weeks of the alternate treatment. A therapist provided a visual cursor using a tracking device, and participants were instructed to match it with their hand. Haptic and visual EA was used with blinding of participant, therapist, technician-operator, and evaluator. Clinical measures of impairment were obtained at the beginning and end of each 2-week treatment phase as well as at 1 week and at 45 days after the last treatment. RESULTS: Outcomes showed a small, but significant benefit to EA training over simple repetitive practice, with a mean 2-week improvement in Fugl-Meyer UE motor score of 2.08 and Wolf Motor Function Test of timed tasks of 1.48 s. CONCLUSIONS: This interactive technology may improve UE motor recovery of stroke-related hemiparesis.

Body machine interfaces for neuromotor rehabilitation: a case study.

High-level spinal cord injury (SCI) survivors face every day two related problems: recovering motor skills and regaining functional independence. Body machine interfaces (BoMIs) empower people with sever motor disabilities with the ability to control an external device, but they also offer the opportunity to focus concurrently on achieving rehabilitative goals. In this study we developed a portable, and low-cost BoMI that addresses both problems. The BoMI remaps the user's residual upper body mobility to the two coordinates of a cursor on a computer monitor. By controlling the cursor, the user can perform functional tasks, such as entering text and playing games. This framework also allows the mapping between the body and the cursor space to be modified, gradually challenging the user to exercise more impaired movements. With this approach, we were able to change the behavior of our SCI subject, who initially used almost exclusively his less impaired degrees of freedom - on the left side - for controlling the BoMI. At the end of the few practice sessions he had restored symmetry between left and right side of the body, with an increase of mobility and strength of all the degrees of freedom involved in the control of the interface. This is the first proof of concept that our BoMI can be used to control assistive devices and reach specific rehabilitative goals simultaneously.

A body machine interface based on inertial sensors.

Spinal cord injury (SCI) survivors generally retain residual motor and sensory functions, which provide them with the means to control assistive devices. A body-machine interface (BoMI) establishes a mapping from these residual body movements to control commands for an external device. In this study, we designed a BoMI to smooth the way for operating computers, powered wheelchairs and other assistive technologies after cervical spinal cord injuries. The interface design included a comprehensive training paradigm with a range of diverse functional activities to enhance motor learning and retention. Two groups of SCI survivors and healthy control subjects participated in the study. The results indicate the effectiveness of the developed system as an alternative pathway for individuals with motor disabilities to control assistive devices while engaging in functional motor activity.

Mirror versus parallel bimanual reaching.

BACKGROUND: In spite of their importance to everyday function, tasks that require both hands to work together such as lifting and carrying large objects have not been well studied and the full potential of how new technology might facilitate recovery remains unknown. METHODS: To help identify the best modes for self-teleoperated bimanual training, we used an advanced haptic/graphic environment to compare several modes of practice. In a 2-by-2 study, we compared mirror vs. parallel reaching movements, and also compared veridical display to one that transforms the right hand's cursor to the opposite side, reducing the area that the visual system has to monitor. Twenty healthy, right-handed subjects (5 in each group) practiced 200 movements. We hypothesized that parallel reaching movements would be the best performing, and attending to one visual area would reduce the task difficulty. RESULTS: The two-way comparison revealed that mirror movement times took an average 1.24 s longer to complete than parallel. Surprisingly, subjects' movement times moving to one target (attending to one visual area) also took an average of 1.66 s longer than subjects moving to two targets. For both hands, there was also a significant interaction effect, revealing the lowest errors for parallel movements moving to two targets (p < 0.001). This was the only group that began and maintained low errors throughout training. CONCLUSION: Combined with other evidence, these results suggest that the most intuitive reaching performance can be observed with parallel movements with a veridical display (moving to two separate targets). These results point to the expected levels of challenge for these bimanual training modes, which could be used to advise therapy choices in self-neurorehabilitation.

Arm control recovery enhanced by error augmentation.

Here we present results where nineteen stroke survivors with chronic hemiparesis simultaneously employed the trio of patient, therapist, and machine. Massed practice combined with error augmentation, where haptic (robotic forces) and graphic (visual display) distortions are used to enhance the feedback of error, was compared to massed practice alone. The 6-week randomized crossover design involved approximately 60 minutes of daily treatment three times per week for two weeks, followed by one week of rest, and then repeated using the alternate treatment protocol. A therapist provided a visual target using a tracking device that moved a cursor in front of the patient, who was instructed to maintain the cursor on the target. The patient, therapist, technician-operator, and rater were blinded to treatment type. Several clinical measures gauged outcomes at the beginning and end of each 2-week period and one week post training. Results showed incremental benefit across most but not all days, abrupt gains in performance, and a benefit to error augmentation training in final evaluations. This application of interactive technology may be a compelling new method for enhancing a therapist's productivity in stroke-rehabilitation.

Combination of frequency bands in EEG for feature reduction in mental task classification.

Brain-computer interfaces require online processing of electroencephalogram (EEG) measurements. Therefore, speed of signal processing is of great importance in BCI systems. We present a method of feature reduction by combining frequency band powers of EEG, in order to speed up processing and meanwhile avoid classifier overfitting. As a result a linear combination of power spectrum of EEG frequency bands (alpha, beta, gamma, delta & theta) was found that reduces the dimension of feature vector by a factor of 5. This method gives a total correct classification rate of 91.71% comparing to 87.96% achieved from direct use of frequency band powers and 85.54% achieved from PCA feature reduction method applied to the same feature vector with 14 components.