Single-Trial Mechanisms Underlying Changes in Averaged P300 ERP Amplitude and Latency in Military Service Members After Combat Deployment.

Attenuation in P300 amplitude has been characterized in a wide range of neurological and psychiatric disorders such as dementia, schizophrenia, and posttraumatic stress disorder (PTSD). However, it is unclear whether the attenuation observed in the averaged event-related potential (ERP) is due to the reduction of neural resources available for cognitive processing, the decreased consistency of cognitive resource allocation, or the increased instability of cognitive processing speed. In this study, we investigated this problem by estimating single-trial P300 amplitude and latency using a modified Woody filter and examined the relation between amplitudes and latencies from the single-trial level to the averaged ERP level. ERPs were recorded from 30 military service members returning from combat deployment at two time points separated by 6 or 12 months. A conventional visual oddball task was used to elicit P300. We observed that the extent of changes in the within-subject average P300 amplitude over time was significantly correlated with the amount of change in three single-trial measures: (1) the latency variance of the single-trial P300 (r = -0.440, p = 0.0102); (2) the percentage of P300-absent trials (r = -0.488, p = 0.005); and (3) the consistent variation of the single-trial amplitude (r = 0.571, p = 0.0022). These findings suggest that there are multiple underlying mechanisms on the single-trial level that contribute to the changes in amplitudes seen at the averaged ERP level. The changes between the first and second assessments were quantified with the intraclass correlation coefficient, the standard error of measurement and the minimal detectable difference. The unique population, the small sample size and the large fraction of participants lost to follow up precludes generalizations of these measures of change to other populations.

When Expectancies Are Violated: A Functional Magnetic Resonance Imaging Study.

Positive and negative expectancies drive behavioral and neurobiological placebo and nocebo effects, which in turn can have profound effects on patient improvement or worsening. However, expectations of events and outcomes are often not met in daily life and clinical practice. It is currently unknown how this affects placebo and nocebo effects. We have demonstrated that the violation of expectancies, such as when there is a discrepancy between what is expected and what is actually presented, reduces both placebo and nocebo effects while causing an extinction of placebo effects. The reduction of placebo and nocebo effects was paralleled by an activation of the left inferior parietal cortex, a brain region that redirects attention when discrepancies between sensory and cognitive events occur. Our findings highlight the importance of expectancy violation in shaping placebo and nocebo effects and open up new avenues for managing positive and negative expectations in clinical trials and practices.

Cortical thinning in military blast compared to non-blast persistent mild traumatic brain injuries.

In the military, explosive blasts are a significant cause of mild traumatic brain injuries (mTBIs). The symptoms associated with blast mTBIs causes significant economic burdens and a diminished quality of life for many service members. At present, the distinction of the injury mechanism (blast versus non-blast) may not influence TBI diagnosis. However, using noninvasive imaging, this study reveals significant distinctions between the blast and non-blast TBI mechanisms. A cortical whole-brain thickness analysis was performed using structural high-resolution T1-weighted MRI to identify the effects of blasts in persistent mTBI (pmTBI) subjects. A total of 41 blast pmTBI subjects were individually age- and gender-matched to 41 non-blast pmTBI subjects. Using FreeSurfer, cortical thickness was quantified for the blast group, relative to the non-blast group. Cortical thinning was identified within the blast mTBI group, in two clusters bilaterally. In the left hemisphere, the cluster overlapped with the lateral orbitofrontal, rostral middle frontal, medial orbitofrontal, superior frontal, rostral anterior cingulate and frontal pole cortices (p < 0.02, two-tailed, size = 1680 mm2). In the right hemisphere, the cluster overlapped with the lateral orbitofrontal, rostral middle frontal, medial orbitofrontal, pars orbitalis, pars triangularis and insula cortices (p < 0.002, two-tailed, cluster size = 2453 mm2). Self-report assessments suggest significant differences in the Post-Traumatic Stress Disorder Checklist-Civilian Version (p < 0.05, Bonferroni-corrected) and the Neurobehavioral Symptom Inventory (p < 0.01, uncorrected) between the blast and non-blast mTBI groups. These results suggest that blast may cause a unique injury pattern related to a reduction in cortical thickness within specific brain regions which could affect symptoms. No other study has found cortical thickness difference between blast and non-blast mTBI groups and further replication is needed to confirm these initial observations.

Assessment of Brain Venous Structure in Military Traumatic Brain Injury Patients using Susceptibility Weighted Imaging and Quantitative Susceptibility Mapping.

Brain venous volume above the lateral ventricle in military patients with traumatic brain injury (TBI) was assessed using two segmentation approaches on susceptibility weighted images (SWI) and quantitative susceptibility maps (QSM). This retrospective study included a total of 147 subjects: 14 patients with severe TBI; 38 patients with moderate TBI, 58 patients with mild TBI (28 with blast-related injuries and 30 with non-blast-related injuries), and 37 control subjects without history of TBI. Using the multiscale vessel enhancement filter on SWI images, patients with severe TBI demonstrated significantly higher segmented venous volumes compared with controls. Using a threshold approach on QSM images, TBI patients with different severities all demonstrated increased segmented volumes compared with control subjects: in the whole brain (severe, p = 0.001; moderate, p = 0.008; mild, p = 0.042, compared with controls), in the left hemisphere (severe, p = 0.01; moderate, p = 0.038, compared with controls), in the right hemisphere (severe, p = 0.001; moderate, p = 0.013; mild, p = 0.027, compared with controls). While segmented volumes on SWI appear to overlay directly on the visualized venous structures, the QSM-derived segments also encompass some perivascular and deep white matter areas. This might represent the damage in the perivascular regions associated with iron deposition or astroglial scarring.

Utility of P300 ERP in monitoring post-trauma mental health: A longitudinal study in military personnel returning from combat deployment.

Military service members (SMs) returning from combat are at high risk of developing neuropsychiatric conditions such as posttraumatic stress disorder (PTSD) and major depression. Symptom dynamics following reintegration into civilian life may be magnified over time such that some SMs present with delayed onset and may not reach a diagnostic threshold for months to years. Monitoring the trajectory of mental health in the aftermath of combat trauma can therefore be particularly important in enhancing diagnosis. In this study, we investigated the possible utility of the P300 event-related potential (ERP) as an objective marker for monitoring post-trauma mental health. SMs recently returned from a combat deployment were recruited to undergo a baseline assessment, with subsequent follow-up assessment at 6 or 12 months later. At each assessment, ERPs were recorded using a conventional visual oddball task and a set of psychological scores assessing PTSD, depression, and psychosocial functioning were obtained. We observed that the individuals with overall improved psychological scores at follow-up had increased P300 amplitude and shortened P300 latency, and the individuals with overall worsened psychological scores at follow-up had prolonged P300 latency. The degree of change in aggregate psychological score was significantly correlated with the magnitude of change in P300 amplitude (r = -0.72, p < 0.0001) and latency (r = 0.42, p = 0.0201). These findings suggest that the P300 may be utilized as a quantitative biomarker for tracking the changes of mental health longitudinally. It may offer clinicians an objective tool for the assessment of the dynamics of mental health following trauma, and perhaps also for monitoring recovery during treatment.

Disrupted Gamma Synchrony after Mild Traumatic Brain Injury and Its Correlation with White Matter Abnormality.

Mild traumatic brain injury (mTBI) has been firmly associated with disrupted white matter integrity due to induced white matter damage and degeneration. However, comparatively less is known about the changes of the intrinsic functional connectivity mediated via neural synchronization in the brain after mTBI. Moreover, despite the presumed link between structural and functional connectivity, no existing studies in mTBI have demonstrated clear association between the structural abnormality of white matter axons and the disruption of neural synchronization. To investigate these questions, we recorded resting state EEG and diffusion tensor imaging (DTI) from a cohort of military service members. A newly developed synchronization measure, the weighted phase lag index was applied on the EEG data for estimating neural synchronization. Fractional anisotropy was computed from the DTI data for estimating white matter integrity. Fifteen service members with a history of mTBI within the past 3 years were compared to 22 demographically similar controls who reported no history of head injury. We observed that synchronization at low-gamma frequency band (25-40 Hz) across scalp regions was significantly decreased in mTBI cases compared with controls. The synchronization in theta (4-7 Hz), alpha (8-13 Hz), and beta (15-23 Hz) frequency bands were not significantly different between the two groups. In addition, we found that across mTBI cases, the disrupted synchronization at low-gamma frequency was significantly correlated with the white matter integrity of the inferior cerebellar peduncle, which was also significantly reduced in the mTBI group. These findings demonstrate an initial correlation between the impairment of white matter integrity and alterations in EEG synchronization in the brain after mTBI. The results also suggest that disruption of intrinsic neural synchronization at low-gamma frequency may be a characteristic functional pathology following mTBI and may prove useful for developing better methods of diagnosis and treatment.

Identifying Electrophysiological Prodromes of Post-traumatic Stress Disorder: Results from a Pilot Study.

The objective of this research project is the identification of a physiological prodrome of post-traumatic stress disorder (PTSD) that has a reliability that could justify preemptive treatment in the sub-syndromal state. Because abnormalities in event-related potentials (ERPs) have been observed in fully expressed PTSD, the possible utility of abnormal ERPs in predicting delayed-onset PTSD was investigated. ERPs were recorded from military service members recently returned from Iraq or Afghanistan who did not meet PTSD diagnostic criteria at the time of ERP acquisition. Participants (n = 65) were followed for up to 1 year, and 7.7% of the cohorts (n = 5) were PTSD-positive at follow-up. The initial analysis of the receiver operating characteristic (ROC) curve constructed using ERP metrics was encouraging. The average amplitude to target stimuli gave an area under the ROC curve of greater than 0.8. Classification based on the Youden index, which is determined from the ROC, gave positive results. Using average target amplitude at electrode Cz yielded Sensitivity = 0.80 and Specificity = 0.87. A more systematic statistical analysis of the ERP data indicated that the ROC results may simply represent a fortuitous consequence of small sample size. Predicted error rates based on the distribution of target ERP amplitudes approached those of random classification. A leave-one-out cross validation using a Gaussian likelihood classifier with Bayesian priors gave lower values of sensitivity and specificity. In contrast with the ROC results, the leave-one-out classification at Cz gave Sensitivity = 0.65 and Specificity = 0.60. A bootstrap calculation, again using the Gaussian likelihood classifier at Cz, gave Sensitivity = 0.59 and Specificity = 0.68. Two provisional conclusions can be offered. First, the results can only be considered preliminary due to the small sample size, and a much larger study will be required to assess definitively the utility of ERP prodromes of PTSD. Second, it may be necessary to combine ERPs with other biomarkers in a multivariate metric to produce a prodrome that can justify preemptive treatment.

Assessing the Impact of Post-Traumatic Stress Symptoms on the Resting-State Default Mode Network in a Military Chronic Mild Traumatic Brain Injury Sample.

The relationship between post-traumatic stress disorder (PTSD) and chronic symptoms of mild traumatic brain injury (mTBI) is difficult to discern and poorly understood. An accurate differential diagnosis, assessment, and treatment of mTBI and PTSD are challenging due to significant symptom overlap and the absence of clearly established biomarkers. The objective of this work is to examine how post-traumatic stress influences task-free default mode network in chronic mTBI subjects. Control subjects (N = 44) were compared with chronic mTBI subjects with low (N = 58, PTSD Checklist-Civilian Version [PCL-C] total < 30), medium (N = 124, PCL-C total = 31-49), and high (N = 105, PCL-C total ≥ 60) post-traumatic stress symptoms (PTSS). The results indicate significant differences in Brodmann area 10 for all mTBI subject groups, indicating potential mTBI-related disruptions with regulation of emotions and decision-making. The effects of PTSS were observed in the anterior cingulate and parahippocampus, suggesting possible disruptions pertaining to memory regulation, encoding, and retrieval. The overall results indicate the presence of aberrant connectivity patterns between controls and chronic mTBI subjects with low, medium, and high PTSS. Furthermore, the findings suggest a disruption in attention relating to a network of brain regions involved with emotional regulation and memory coding, rather than a fear-related response. Taken together, the results suggest these regions form a network that could be a target for future research pertaining to PTSD and chronic mTBI. Furthermore, the use of clinical measures, task-based imaging studies, or multimodal imaging could help further elucidate specific neural correlates of PTSS and mTBI.

Assessing Quantitative Changes in Intrinsic Thalamic Networks in Blast and Nonblast Mild Traumatic Brain Injury: Implications for Mechanisms of Injury.

In the global war on terror, the increased use of improvised explosive devices has resulted in increased incidence of blast-related mild traumatic brain injury (mTBI). Diagnosing mTBI is both challenging and controversial due to heterogeneity of injury location, trauma intensity, transient symptoms, and absence of focal biomarkers on standard clinical imaging modalities. The goal of this study is to identify a brain biomarker that is sensitive to mTBI injury. Research suggests the thalamus may be sensitive to changes induced by mTBI. A significant number of connections to and from various brain regions converge at the thalamus. In addition, the thalamus is involved in information processing, integration, and regulation of specific behaviors and mood. In this study, changes in task-free thalamic networks as quantified by graph theory measures in mTBI blast (N = 186), mTBI nonblast (N = 80), and controls (N = 21) were compared. Results show that the blast mTBI group had significant hyper-connectivity compared with the controls and nonblast mTBI group. However, after controlling for post-traumatic stress symptoms (PTSS), the blast mTBI group was not different from the controls, but the nonblast mTBI group showed significant hypo-connectivity. The results suggest that there are differences in the mechanisms of injury related to mTBI as reflected in the architecture of the thalamic networks. However, the effect of PTSS and its relationship to mTBI is difficult to distinguish and warrants more research.

Exploring variations in functional connectivity of the resting state default mode network in mild traumatic brain injury.

A definitive diagnosis of mild traumatic brain injury (mTBI) is difficult due to the absence of biomarkers in standard clinical imaging. The brain is a complex network of interconnected neurons and subtle changes can modulate key networks of cognitive function. The resting state default mode network (DMN) has been shown to be sensitive to changes induced by pathology. This study seeks to determine whether quantitative measures of the DMN are sensitive in distinguishing mTBI subjects. Resting state functional magnetic resonance imaging data were obtained for healthy (n=12) and mTBI subjects (n=15). DMN maps were computed using dual-regression Independent Component Analysis (ICA). A goodness-of-fit (GOF) index was calculated to assess the degree of spatial specificity and sensitivity between healthy controls and mTBI subjects. DMN regions and neuropsychological assessments were examined to identify potential relationships. The resting state DMN maps indicate an increase in spatial coactivity in mTBI subjects within key regions of the DMN. Significant coactivity within the cerebellum and supplementary motor areas of mTBI subjects were also observed. This has not been previously reported in seed-based resting state network analysis. The GOF suggested the presence of high variability within the mTBI subject group, with poor sensitivity and specificity. The neuropsychological data showed correlations between areas of coactivity within the resting state network in the brain with a number of measures of emotion and cognitive functioning. The poor performance of the GOF highlights the key challenge associated with mTBI injury: the high variability in injury mechanisms and subsequent recovery. However, the quantification of the DMN using dual-regression ICA has potential to distinguish mTBI from healthy subjects, and provide information on the relationship of aspects of cognitive and emotional functioning with their potential neural correlates.

Connecting combat-related mild traumatic brain injury with posttraumatic stress disorder symptoms through brain imaging.

Mild traumatic brain injury (mTBI) and posttraumatic stress disorder (PTSD) may share common symptom and neuropsychological profiles in military service members (SMs) following deployment; while a connection between the two conditions is plausible, the relationship between them has been difficult to discern. The intent of this report is to enhance our understanding of the relationship between findings on structural and functional brain imaging and symptoms of PTSD. Within a cohort of SMs who did not meet criteria for PTSD but were willing to complete a comprehensive assessment within 2 months of their return from combat deployment, we conducted a nested case-control analysis comparing those with combat-related mTBI to age/gender-matched controls with diffusion tensor imaging, resting state functional magnetic resonance imaging and a range of psychological measures. We report degraded white matter integrity in those with a history of combat mTBI, and a positive correlation between the white matter microstructure and default mode network (DMN) connectivity. Higher clinician-administered and self-reported subthreshold PTSD symptoms were reported in those with combat mTBI. Our findings offer a potential mechanism through which mTBI may alter brain function, and in turn, contribute to PTSD symptoms.

Understanding the importance of natural neuromotor strategy in upper extremity neuroprosthetic control.

A key challenge in upper extremity neuroprosthetics is variable levels of skill and inconsistent functional recovery. We examine the feasibility and benefits of using natural neuromotor strategies through the design and development of a proof-of-concept model for a feed-forward upper extremity neuroprosthetic controller. Developed using Artificial Neural Networks, the model is able to extract and classify neural correlates of movement intention from multiple brain regions that correspond to functional movements. This is unique compared to contemporary controllers that record from limited physiological sources or require learning of new strategies. Functional MRI (fMRI) data from healthy subjects (N = 13) were used to develop the model, and a separate group (N = 4) of subjects were used for validation. Results indicate that the model is able to accurately (81%) predict hand movement strictly from the neural correlates of movement intention. Information from this study is applicable to the development of upper extremity technology aided interventions.

Perfusion deficits in patients with mild traumatic brain injury characterized by dynamic susceptibility contrast MRI.

Perfusion deficits in patients with mild traumatic brain injury (TBI) from a military population were characterized by dynamic susceptibility contrast perfusion imaging. Relative cerebral blood flow (rCBF) was calculated by a model-independent deconvolution approach from the tracer concentration curves following a bolus injection of gadolinium diethylenetriaminepentaacetate (Gd-DTPA) using both manually and automatically selected arterial input functions (AIFs). Linear regression analysis of the mean values of rCBF from selected regions of interest showed a very good agreement between the two approaches, with a regression coefficient of R = 0.88 and a slope of 0.88. The Bland-Altman plot also illustrated the good agreement between the two approaches, with a mean difference of 0.6 ± 12.4 mL/100 g/min. Voxelwise analysis of rCBF maps from both approaches demonstrated multiple clusters of decreased perfusion (p < 0.01) in the cerebellum, cuneus, cingulate and temporal gyrus in the group with mild TBI relative to the controls. MRI perfusion deficits in the cerebellum and anterior cingulate also correlated (p < 0.01) with neurocognitive results, including the mean reaction time in the Automated Neuropsychological Assessment Metrics and commission error and detection T-scores in the Continuous Performance Test, as well as neurobehavioral scores in the Post-traumatic Stress Disorder Checklist-Civilian Version. In conclusion, rCBF calculated using AIFs selected from an automated approach demonstrated a good agreement with the corresponding results using manually selected AIFs. Group analysis of patients with mild TBI from a military population demonstrated scattered perfusion deficits, which showed significant correlations with measures of verbal memory, speed of reaction time and self-report of stress symptoms.

Investigating the neural correlates of goal-oriented upper extremity movements.

OBJECTIVE: To understand neural correlates of upper extremity task performance (functional vs. non-functional) and to understand their influence on neuromotor control strategies. DESIGN: Cross-sectional descriptive study, with repeated measures. SETTING: Medical center 1.5T MRI clinical imaging facility. PARTICIPANTS: Neurologically intact individuals, (M=14 F=5 mean age=22.94 ± 3.1 years) all right hand dominant as determined by the Edinburgh handedness survey. Subjects performed upper extremity motor tasks of reaching and grasping in a block paradigm. Whole brain fMRI data was acquired using a 1.5T MRI scanner. MAIN OUTCOME MEASURES: Differences in fMRI area of activation and maximum activation intensity for the whole brain were evaluated among the different upper extremity motor tasks. RESULTS: Our results indicate (a) Activations in brain regions are task specific. (b) ANOVA results indicate functional goal oriented movements of reaching and grasping produce higher activation intensity (p < 0.0001) in more regions of the cortex (Somatosensory motor area, primary motor cortex, and parietal region) and cerebellum (p < 0.001) as compared to nonfunctional rhythmic movements of reaching only and grasping only. (c) There is some overlap in cerebellar activations, however areas of activation in the medial cerebellum were observed for reaching-and-grasping, while the grasping-only task produced activation more laterally in the cerebellum. CONCLUSIONS: Our findings suggest that (a) neuromotor strategy for functional goal-oriented movements is different from rhythmic movements such as finger tapping or non-functional movements, (b) This difference can be quantified and mapped using fMRI. (c) There are some overlap with activation of movement execution however the cognitive component that mediates the specific movement is not just the linear combination of simple movements rather it is task and context specific. (d) The results support the concept of using goal-oriented tasks in the applications of rehabilitation and therapy for restoration of function.

Understanding neuromotor strategy during functional upper extremity tasks using symbolic dynamics.

The ability to model and quantify brain activation patterns that pertain to natural neuromotor strategy of the upper extremities during functional task performance is critical to the development of therapeutic interventions such as neuroprosthetic devices. The mechanisms of information flow, activation sequence and patterns, and the interaction between anatomical regions of the brain that are specific to movement planning, intention and execution of voluntary upper extremity motor tasks were investigated here. This paper presents a novel method using symbolic dynamics (orbital decomposition) and nonlinear dynamic tools of entropy, self-organization and chaos to describe the underlying structure of activation shifts in regions of the brain that are involved with the cognitive aspects of functional upper extremity task performance. Several questions were addressed: (a) How is it possible to distinguish deterministic or causal patterns of activity in brain fMRI from those that are really random or non-contributory to the neuromotor control process? (b) Can the complexity of activation patterns over time be quantified? (c) What are the optimal ways of organizing fMRI data to preserve patterns of activation, activation levels, and extract meaningful temporal patterns as they evolve over time? Analysis was performed using data from a custom developed time resolved fMRI paradigm involving human subjects (N=18) who performed functional upper extremity motor tasks with varying time delays between the onset of intention and onset of actual movements. The results indicate that there is structure in the data that can be quantified through entropy and dimensional complexity metrics and statistical inference, and furthermore, orbital decomposition is sensitive in capturing the transition of states that correlate with the cognitive aspects of functional task performance.

Examining intrinsic thalamic resting state networks using graph theory analysis: implications for mTBI detection.

A major challenge associated with understanding mild traumatic brain injury (mTBI) is the absence of biomarkers in standard clinical imaging modalities. Furthermore, the inhomogeneity of mTBI location and intensity, combined with latent symptoms further complicates identification and treatment. A growing body of evidence suggests that the thalamus may be injured or susceptible to change as the result of mTBI. A significant number of connections to and from cortical, subcortical, cerebellar and brain stem regions converge at the thalamus. Furthermore, the thalamus is also involved with information processing, integration and the regulation of specific behaviors. We use graph theory analysis to evaluate intrinsic functional networks of the left and right thalamus in mTBI subjects (N=15) and neurologically intact healthy controls (N=12). We also explore neural correlates of the thalamic network architecture with clinical assessments. Our results suggest the presence of distinct unilateral thalamic differences in mTBI subjects. We also observe correlations of the thalamic changes with clinical assessments. The findings from this study have implications for functional networks in the thalamus and its projections for application as a potential biomarker for mTBI detection.

Design and validation of low-cost assistive glove for hand assessment and therapy during activity of daily living-focused robotic stroke therapy.

Hand and arm impairment is common after stroke. Robotic stroke therapy will be more effective if hand and upper-arm training is integrated to help users practice reaching and grasping tasks. This article presents the design, development, and validation of a low-cost, functional electrical stimulation grasp-assistive glove for use with task-oriented robotic stroke therapy. Our glove measures grasp aperture while a user completes simple-to-complex real-life activities, and when combined with an integrated functional electrical stimulator, it assists in hand opening and closing. A key function is a new grasp-aperture prediction model, which uses the position of the end-effectors of two planar robots to define the distance between the thumb and index finger. We validated the accuracy and repeatability of the glove and its capability to assist in grasping. Results from five nondisabled subjects indicated that the glove is accurate and repeatable for both static hand-open and -closed tasks when compared with goniometric measures and for dynamic reach-to-grasp tasks when compared with motion analysis measures. Results from five subjects with stroke showed that with the glove, they could open their hands but without it could not. We present a glove that is a low-cost solution for in vivo grasp measurement and assistance.

Attractor and Lyapunov models for reach and grasp movements with application to robot-assisted therapy.

The principles of attractors and Lyapunov exponents were used to develop a reaching-to-grasp model for use in a robotic therapy system for stroke patients. Previously known models for these movements, the fifth order minimum jerk and the seventh order polynomial, do not account for the change in grasp aperture of the hand. The Lyapunov model was tested with reaching-to-grasp movements performed by five neurologically intact subjects and produced an average R-square = .97 over 15 replications for 41 different task events, reflecting a notable advantage over the fifth order (average R-square = .58) and seventh order (average R-square = .67) models. A similar level of success was obtained for the Lyapunov model that was specific to grasp aperture. The results indicated that intentional movements can be accurately characterized as attractor trajectories, and as functions of position along two Cartesian coordinates rather than as functions of time. The Lyapunov exponent model requires fewer parameters and provides an efficient platform for real-time implementation.

Should object function matter during modeling of functional reach-to-grasp tasks in robot-assisted therapy?

Recent literature support the idea of using an intense, task-oriented, stroke rehabilitation to promote motor learning and cerebral reorganization. Supporting a task-oriented, robot-assisted therapy approach requires better understanding of the components of real tasks and the limitations and benefits of current trajectory models. We set out to understand natural reach-to-grasp kinematics as it relates to various functional bilateral and unilateral tasks so as to better map this information to a robotic reach-to-grasp therapy systems. To do so, we investigated the influence of arm use and object functionality on four reaching kinematics in reach-to-grasp daily living tasks. We compared our results with the minimum jerk trajectory model used in robot-assisted therapy with the goal of understanding how best to support these real movements in a robotic environment. Eight neurologically intact, right handed subjects participated in the motion analysis study. They completed unilateral and bilateral reaching to objects in the same location with the same orientation, and with handles of the same size and shape. We discuss our results in terms of the minimum jerk model, which is typically used in robot-assisted trajectory planning. Our results showed significant differences in peak velocities, movement time and total displacement across tasks and across arm use conditions.