Eye Closure Research Articles

Sex-based electroclinical differences and prognostic factors in epilepsy with eyelid myoclonia.

Although a striking female preponderance has been consistently reported in epilepsy with eyelid myoclonia (EEM), no study has specifically explored the variability of clinical presentation according to sex in this syndrome. Here, we aimed to investigate sex-specific electroclinical differences and prognostic determinants in EEM. Data from 267 EEM patients were retrospectively analyzed by the EEM Study Group, and a dedicated multivariable logistic regression analysis was developed separately for each sex. We found that females with EEM showed a significantly higher rate of persistence of photosensitivity and eye closure sensitivity at the last visit, along with a higher prevalence of migraine with/without aura, whereas males with EEM presented a higher rate of borderline intellectual functioning/intellectual disability. In female patients, multivariable logistic regression analysis revealed age at epilepsy onset, eyelid myoclonia status epilepticus, psychiatric comorbidities, and catamenial seizures as significant predictors of drug resistance. In male patients, a history of febrile seizures was the only predictor of drug resistance. Hence, our study reveals sex-specific differences in terms of both electroclinical features and prognostic factors. Our findings support the importance of a sex-based personalized approach in epilepsy care and research, especially in genetic generalized epilepsies.

Does the patellar tendon reflex affect the postural stability in stroke patients with blocked vision?

Stroke patients often show postural instability. The patellar tendon reflex is a basic physical examination for stroke patients. This study aimed to explore the correlation between patellar tendon reflex grade and postural stability among stroke patients. A total of 37 elderly stroke patients, each with the same quadriceps muscle strength but different patellar tendon reflex levels, were tested on a force platform under eyes-open (EO) and eyes-closed (EC) conditions. Parametric analysis, detrended fluctuation analysis (DFA), and power spectral density (PSD) analysis were used in centre of pressure (COP) signal processing. The correlation between the results of measured data processing and the level of patellar tendon reflex was analysed. All three parameters of COP (the length of the sway trajectory, the mean range of the sway trajectory in the mediolateral [ML] direction [R x ], and the mean range of the sway trajectory in the anterior-posterior [AP] directions [R y ]) were negatively correlated with the patient's patellar tendon reflex grade under the EC condition. The DFA results showed that a higher grade of patellar tendon reflex was associated with a smaller value of the crossover point in the AP direction. Only the PSD values of each frequency band in the AP direction were negatively correlated with patellar tendon reflex grade with EO and became negatively correlated in both AP and ML directions with EC. Overall, the results showed a strong correlation between patellar tendon reflex and postural stability in stroke patients when vision was blocked. The strong correlation with EC may provide insights into clinic evaluation and treatment for rehabilitation or fall risks of stroke patients.

Drowsiness Detection System using ML

The number of automobile accidents due to driver drowsiness is increasing at an alarming rate. If you have driven before, you’ve been drowsy at the wheel at some point. It’s not something we like to admit but it’s an important problem with serious consequences that needs to be addressed. The scariest part is that drowsy driving isn’t just falling asleep while driving. Drowsy driving can be as small as a brief state of inattentiveness when the driver is not paying full attention to the road. An automated non-contact system that can identify driver drowsiness early is the need of the hour. Our project describes a machine learning approach for drowsiness detection. Face detection is employed to locate the regions of the driver’s eyes, which are used as the templates for eye tracking in subsequent frames. Finally, the tracked eye’s images are used for drowsiness detection in order to generate warning alarms. This proposed approach has three stages: detecting Face, detecting Eyes and detecting drowsiness. Thus, we propose a system to locate, track, and analyse both the drivers face and eyes to measure PERCLOS, a scientifically supported measure of drowsiness associated with slow eye closure

ETSNet: A deep neural network for EEG-based temporal–spatial pattern recognition in psychiatric disorder and emotional distress classification

The use of EEG for evaluating and diagnosing neurological abnormalities related to psychiatric diseases and identifying human emotions has been improved by deep learning advancements. This research aims to categorize individuals with schizophrenia (SZ), their biological relatives (REL), and healthy controls (HC) using resting EEG brain source signal data defined by regions of interest (ROIs). The proposed solution is a deep neural network for the cortical source signals of the ROIs, incorporating a Squeeze-and-Excitation Block and multiple CNNs designed for eyes-open and closed resting states. The model, called EEG Temporal Spatial Network (ETSNet), has two variants: ETSNets and ETSNetf. Two evaluations were conducted to show the effectiveness of the proposed model. The average accuracy for the classification of SZ, REL, and HC using EEG resting data was 99.57% (ETSNetf), and the average accuracy for the classification of eyes-open (EO) and eyes-closed (EC) resting states was 93.15% (ETSNets). An ablation study was also conducted using two public datasets for intellectual and developmental disorders and emotional states, showing improved classification accuracy compared to advanced EEG classification algorithms when using ETSNets.

Eye movements disrupt EEG alpha-band coding of behaviorally relevant and irrelevant spatial locations held in working memory.

Oscillations in the alpha frequency band (∼8-12 Hz) of the human electroencephalogram play an important role in supporting selective attention to visual items and maintaining their spatial locations in working memory (WM). Recent findings suggest that spatial information maintained in alpha is modulated by interruptions to continuous visual input, such that attention shifts, eye closure, and backward masking of the encoded item cause reconstructed representations of remembered locations to become degraded. Here, we investigated how another common visual disruption-eye movements-modulates reconstructions of behaviorally relevant and irrelevant item locations held in WM. Participants completed a delayed estimation task, where they encoded and recalled either the location or color of an object after a brief retention period. During retention, participants either fixated at the center or executed a sequence of eye movements. Electroencephalography (EEG) was recorded at the scalp and eye position was monitored with an eye tracker. Inverted encoding modeling (IEM) was applied to reconstruct location-selective responses across multiple frequency bands during encoding and retention. Location-selective responses were successfully reconstructed from alpha activity during retention where participants fixated at the center, but these reconstructions were disrupted during eye movements. Recall performance decreased during eye-movements conditions but remained largely intact, and further analyses revealed that under specific task conditions, it was possible to reconstruct retained location information from lower frequency bands (1-4 Hz) during eye movements. These results suggest that eye movements disrupt maintained spatial information in alpha in a manner consistent with other acute interruptions to continuous visual input, but this information may be represented in other frequency bands.NEW & NOTEWORTHY Neural oscillations in the alpha frequency band support selective attention to visual items and maintenance of their spatial locations in human working memory. Here, we investigate how eye movements disrupt representations of item locations held in working memory. Although it was not possible to recover item locations from alpha during eye movements, retained location information could be recovered from select lower frequency bands. This suggests that during eye movements, stored spatial information may be represented in other frequencies.

A robotic arm control system with simultaneous and sequential modes combining eye-tracking with steady-state visual evoked potential in virtual reality environment.

At present, single-modal brain-computer interface (BCI) still has limitations in practical application, such as low flexibility, poor autonomy, and easy fatigue for subjects. This study developed an asynchronous robotic arm control system based on steady-state visual evoked potentials (SSVEP) and eye-tracking in virtual reality (VR) environment, including simultaneous and sequential modes. For simultaneous mode, target classification was realized by decision-level fusion of electroencephalography (EEG) and eye-gaze. The stimulus duration for each subject was non-fixed, which was determined by an adjustable window method. Subjects could autonomously control the start and stop of the system using triple blink and eye closure, respectively. For sequential mode, no calibration was conducted before operation. First, subjects' gaze area was obtained through eye-gaze, and then only few stimulus blocks began to flicker. Next, target classification was determined using EEG. Additionally, subjects could reject false triggering commands using eye closure. In this study, the system effectiveness was verified through offline experiment and online robotic-arm grasping experiment. Twenty subjects participated in offline experiment. For simultaneous mode, average ACC and ITR at the stimulus duration of 0.9 s were 90.50% and 60.02 bits/min, respectively. For sequential mode, average ACC and ITR at the stimulus duration of 1.4 s were 90.47% and 45.38 bits/min, respectively. Fifteen subjects successfully completed the online tasks of grabbing balls in both modes, and most subjects preferred the sequential mode. The proposed hybrid brain-computer interface (h-BCI) system could increase autonomy, reduce visual fatigue, meet individual needs, and improve the efficiency of the system.

Predicting Driving Behaviour Using Deep Learning

In recent years, the rise in automobiles and drowsiness has been a significant cause of accidents, leading to numerous injuries and even deaths. To combat this issue, computerization has been implemented in various areas, promoting uniformity and enhancing the quality of life for users. However, despite the creation of drowsiness-finding systems over the past decade, these systems still require improvement in terms of efficiency, cost, speed, and accuracy, among other factors. This paper proposes an integrated approach that incorporates various parameters, including the PERCLOS eye and mouth check status, the computation of a new vector called the Facial Aspect Ratio (FAR), as well as EAR and MAR, to detect drowsiness. The system detects uncontrolled eye movements, an open mouth, and other actions such as nodding and hand motions to control drowsiness. Additionally, the system includes styles and textural-based grade patterns to detect sunglasses on the driver's face and locate the driver's face in different directions. The proposed study demonstrated, improved precision and tested on datasets similar to NTHU-DDD, YawDD, and EMOCDS (Eye and Mouth Open Close Data Set). An android application utilizing the device's camera can detect drowsiness by observing the user's eyes and face, which can be helpful while driving, working, or studying. In conclusion, this integrated approach offers promising results for detecting drowsiness and enhancing user safety.

A CNN-Based Wearable System for Driver Drowsiness Detection

Drowsiness poses a serious challenge to road safety and various in-cabin sensing technologies have been experimented with to monitor driver alertness. Cameras offer a convenient means for contactless sensing, but they may violate user privacy and require complex algorithms to accommodate user (e.g., sunglasses) and environmental (e.g., lighting conditions) constraints. This paper presents a lightweight convolution neural network that measures eye closure based on eye images captured by a wearable glass prototype, which features a hot mirror-based design that allows the camera to be installed on the glass temples. The experimental results showed that the wearable glass prototype, with the neural network in its core, was highly effective in detecting eye blinks. The blink rate derived from the glass output was highly consistent with an industrial gold standard EyeLink eye-tracker. As eye blink characteristics are sensitive measures of driver drowsiness, the glass prototype and the lightweight neural network presented in this paper would provide a computationally efficient yet viable solution for real-world applications.

A comparison of resting-state eyes-closed and dark-room alpha-band activity in children.

In a relaxed and awake state with the eyes closed, 8-12 Hz neural oscillations are the dominant rhythm, most prominent in parietal-occipital regions. Resting-state (RS) alpha is associated with processing speed and is also thought to be central to how networks process information. Unfortunately, the RS eyes-closed (EC) exam can only be used with individuals who can remain awake with their eyes closed for an extended period. As such, infants, toddlers, and individuals with intellectual disabilities are usually excluded from RS alpha studies. Previous research suggests obtaining RS alpha measures in a dark room with the eyes open as a viable alternative to the traditional RS EC exam. To further explore this, RS EC and RS dark room (DR) eyes-open alpha activity was recorded using magnetoencephalography in children with typical development (TD; N = 37) and children with autism spectrum disorder (ASD; N = 30) 6.9-12.6 years old. Findings showed good reliability for the RS EC and DR peak alpha frequency (frequency with strongest alpha power; interclass correlation (ICC) = 0.83). ICCs for posterior alpha power were slightly lower (ICCs in the 0.70 s), with an ~ 5% reduction in posterior alpha power in the DR than EC condition. No differences in the EC and DR associations were observed between the TD and ASD groups. Finally, age was associated with both EC and DR peak alpha frequency. Findings thus indicate the DR exam as a viable way to obtain RS alpha measures in populations frequently excluded from electrophysiology RS studies.

Electroclinical characteristics of photosensitive epilepsy: A retrospective study of 31 Chinese children and literature review.

The objective of this study was to better understand the clinical features of photosensitive epilepsy (PSE) in Chinese children. Thirty-one children with PSE were screened out of 398 children with epilepsy who were consecutively diagnosed by the video-electroencephalogram (VEEG) monitoring method and by using an intermittent photic stimulation (IPS) test. Their EEGs and clinical features were retrospectively analyzed, and their treatment outcomes were followed up. PSE accounted for 7.79% (31/398) of children with epilepsy during the observation period in our single epilepsy center. The male to female ratio of PSE was 1:3.43, and the average seizure onset age was 7.8 ± 3.28 years. The highest range of frequency sensitivity of the IPS test for the induction of EEG epileptic discharge or electroclinical seizures was within 10-20 Hz. Electroclinical seizures were induced in 41.94% (13/31) of PSE patients by using the IPS test, while EEG discharge without clinical seizures was induced in 58.06% (18/31) of PSE patients. Among all PSE patients, an IPS-positive reaction in the eye-closure state was induced in 83.87% of patients, and this rate was significantly higher than that in the eye-opened state (41.94%) or eye-closed state (35.48%). (Eye-closure IPS stimulation means: make the subjects close their eyes at the beginning of each stimulation, open their eyes at the end of the stimulation, and close their eyes again at the beginning of the next stimulation, and so on. While Eye-closed IPS stimulation means the stimulation is started after 5 s of eye closure, and the subjects are kept closed throughout the whole process.) The common and effective drugs used for single or combined therapy in PSE children were valproic acid and levetiracetam. This study provides some useful information about electroclinical characteristics in a cohort of 31 PSE children. It may be beneficial for pediatric neurologists in terms of paying more attention to PSE and correctly dealing with it.

Dynamic cortical and tractography atlases of proactive and reactive alpha and high-gamma activities.

Alpha waves-posterior dominant rhythms at 8-12 Hz reactive to eye opening and closure-are among the most fundamental EEG findings in clinical practice and research since Hans Berger first documented them in the early 20th century. Yet, the exact network dynamics of alpha waves in regard to eye movements remains unknown. High-gamma activity at 70-110 Hz is also reactive to eye movements and a summary measure of local cortical activation supporting sensorimotor or cognitive function. We aimed to build the first-ever brain atlases directly visualizing the network dynamics of eye movement-related alpha and high-gamma modulations, at cortical and white matter levels. We studied 28 patients (age: 5-20 years) who underwent intracranial EEG and electro-oculography recordings. We measured alpha and high-gamma modulations at 2167 electrode sites outside the seizure onset zone, interictal spike-generating areas and MRI-visible structural lesions. Dynamic tractography animated white matter streamlines modulated significantly and simultaneously beyond chance, on a millisecond scale. Before eye-closure onset, significant alpha augmentation occurred at the occipital and frontal cortices. After eye-closure onset, alpha-based functional connectivity was strengthened, while high gamma-based connectivity was weakened extensively in both intra-hemispheric and inter-hemispheric pathways involving the central visual areas. The inferior fronto-occipital fasciculus supported the strengthened alpha co-augmentation-based functional connectivity between occipital and frontal lobe regions, whereas the posterior corpus callosum supported the inter-hemispheric functional connectivity between the occipital lobes. After eye-opening offset, significant high-gamma augmentation and alpha attenuation occurred at occipital, fusiform and inferior parietal cortices. High gamma co-augmentation-based functional connectivity was strengthened, whereas alpha-based connectivity was weakened in the posterior inter-hemispheric and intra-hemispheric white matter pathways involving central and peripheral visual areas. Our results do not support the notion that eye closure-related alpha augmentation uniformly reflects feedforward or feedback rhythms propagating from lower to higher order visual cortex, or vice versa. Rather, proactive and reactive alpha waves involve extensive, distinct white matter networks that include the frontal lobe cortices, along with low- and high-order visual areas. High-gamma co-attenuation coupled to alpha co-augmentation in shared brain circuitry after eye closure supports the notion of an idling role for alpha waves during eye closure. These normative dynamic tractography atlases may improve understanding of the significance of EEG alpha waves in assessing the functional integrity of brain networks in clinical practice; they also may help elucidate the effects of eye movements on task-related brain network measures observed in cognitive neuroscience research.

Postural stability in blepharospasm: the effects of dual-tasking and botulinum toxin therapy

BackgroundBlepharospasm is a focal dystonia that presents as involuntary, intermittent, continuous contractions of the eyelids. Abnormal eyelid contractions in blepharospasm are expected to cause balance problems, but there is no...

Morphofunctional regeneration by mesenchymal stem cell and IGF-1 inoculation in a model of facial nerve crush injury in rats.

To analyze the morphofunctional regeneration process of facial nerve injury in the presence of insulin-like growth factor-1 and mesenchymal stem cells. Fourteen Wistar rats suffered unilateral facial nerve crushing and were randomly divided into two groups. All received insulin-like growth factor-1 inoculation, but only half of the animals received an additional inoculation of mesenchymal stem cells. The animals were followed for 90 days and facial nerve regeneration was analyzed via spontaneous facial motor function tests and immunohistochemistry in the nerve motor nucleus. The group that received the growth factor and stem cells showed a statistically superior mean in vibrissae movements (p < 0.01), touch reflex (p = 0.05) and eye closure (p < 0.01), in addition to better immunohistochemistry reactivity. There was a statistically significant difference in the mean number of cells in the facial nerve nucleus between the experimental groups (p = 0.025), with the group that received the growth factor and stem cells showing the highest mean. The association between growth factor and stem cells potentiates the morphofunctional regeneration of the facial nerve, occurring faster and more effectively. 4, degree of recommendation C.

The Effect of Fatigue on Postural Control and Biomechanical Characteristic of Lunge in Badminton Players.

This study investigated the effects of fatigue on postural control and biomechanical characteristic of lunge. A total of twelve healthy male collegiate badminton players (21.1 ± 2.2 years; 180.8 ± 4.0 cm; 72.5 ± 8.4 kg; 8.9 ± 3.5 years of experience) performed repeating lunges until exhausted. Postural stability was evaluated through a single-leg balance test using the dominant lower limb on a pressure plate with eyes opened (EO) and eyes closed (EC). The center of pressure (CoP) sway in the entire plantar and sub-regions of the plantar was measured. Kinematic and kinetic data of lunge motion were collected. The postural control was impaired after fatigue. In plantar sub-regions, the area, displacement and distance in the medial-lateral (ML) and anterior-posterior directions of CoP increased significantly (p < 0.05), especially the distance in ML. The medial region of the forefoot is the most sensitive to fatigue. Compared to pre-fatigue, participants experienced a significantly longer phase of pre-drive-off (p < 0.01), less peak moment and peak power of the knee and hip for drive-off (p < 0.01) and less peak moment of the ankle during braking phase (p < 0.05). These findings indicate that, within the setting of this investigation, the different responses to fatigue for CoP sway in plantar sub-regions and the consistency between postural control and biomechanical characteristic of lunge may be beneficial for developing and monitoring a training plan.

The Effect of Partial Sleep Deprivation and Time-on-Task on Young Drivers’ Subjective and Objective Sleepiness

Despite sleepiness being considered one of the main factors contributing to road crashes, and even though extensive efforts have been made in the identification of techniques able to detect it, the assessment of fitness-to-drive regarding driving fatigue and sleepiness is still an open issue. In the literature on driver sleepiness, both vehicle-based measures and behavioral measures are used. Concerning the former, the one considered more reliable is the Standard Deviation of Lateral Position (SDLP) while the PERcent of eye CLOSure over a defined period of time (PERCLOS) seems to be the most informative behavioral measure. In the present study, using a within-subject design, we assessed the effect of a single night of partial sleep deprivation (PSD, less than 5 h sleeping time) compared to a control condition (full night of sleep, 8 h sleeping time) on SDLP and PERCLOS, in young adults driving in a dynamic car simulator. Results show that time-on-task and PSD affect both subjective and objective sleepiness measures. Moreover, our data confirm that both objective and subjective sleepiness increase through a monotonous driving scenario. Considering that SDLP and PERCLOS were often used separately in studies on driver sleepiness and fatigue detection, the present results have potential implications for fitness-to-drive assessment in that they provide useful information allowing to combine the advantages of the two measures for drowsiness detection while driving.

The effect of musk incense stick aroma inhalation on different features of electroencephalogram signals and working memory for use in neurofeedback training

Susceptibility of brain activity to the inhalation of different aromas established the idea of inhaling an aroma as an auxiliary factor in neurofeedback training. The present study has focused on investigating the effect of musk incense stick aroma inhalation on various features of EEG signals (power of different frequency bands along with Katz fractal dimension (Katz’s FD), approximate entropy (ApEn) and scaling exponent) and working memory for use in neurofeedback training. To raise this aim, the EEG signals were recorded under eyes-open (EO) and eyes-closed (EC) conditions for 22 healthy subjects before and during the musk incense stick aroma inhalation, followed by performing Wechsler Memory Scale (WMS). The results showed that musk incense stick aroma inhalation under EO condition increased the relative power of delta, theta, sensorimotor rhythm (SMR) and low beta frequency bands along with ApEn and Katz’s FD in most channels, whereas decreased the relative power of alpha, high beta and gamma bands. A decrease was found in the relative power of delta, theta, SMR, low beta, high beta and gamma frequency bands in some channels under EC conditions. ApEn and Katz’s FD values also increased in most channels under EC conditions following musk incense stick aroma inhalation. The scaling exponent also decreased under the same conditions in most channels. However, these changes were not significant in all channels. The WMS score also increased after inhaling aroma, but not significantly. The findings of this research suggest the use of musk incense stick aroma inhalation during neurofeedback training to increase training efficiency.

Identification of Stable Anatomical Landmarks During Facial Expressions.

Background: Identifying stable anatomical landmarks during facial expressions is necessary to register and align three-dimensional (3D) data, determine the common origin and motion axis, and calculate displacement, velocity, and acceleration of relative motion. Objective: Our study aimed to determine the stable anatomical landmarks during facial expressions. Methods: We included 30 volunteers in our study and asked them to perform resting, mouth opening, showing teeth, clenching teeth, eye closure, smiling, whistling, eyebrow raising, and disgusted facial expressions. We recorded the 3D movements of passive reflective markers with optoelectronic cameras, which we attached to 10 bilateral and 8 midline landmarks. Results: We determined that the inner corner of the eye while mouth opening, the hairline superior while showing teeth, the infraorbital rim while clenching teeth, the alare while eye closure, the inner corner of the eye while smiling, the mideyebrow while whistling, corners of the mouth while eyebrow raising, and hairline superior while disgust are the most stable anatomical landmarks. Conclusions: Our study identified immobile soft tissue landmarks specific to facial expression.

Neuromodulatory feasibility of a current limiter-based tDCS device: a resting-state electroencephalography study.

Recently, we introduced a current limiter-based novel transcranial direct-current stimulation (tDCS) device that does not generate significant tDCS-induced electrical artifacts, thereby facilitating simultaneous electroencephalography (EEG) measurement during tDCS application. In this study, we investigated the neuromodulatory effect of the tDCS device using resting-state EEG data measured during tDCS application in terms of EEG power spectral densities (PSD) and brain network indices (clustering coefficient and path length). Resting-state EEG data were recorded from 10 healthy subjects during both eyes-open (EO) and eyes-closed (EC) states for each of five different conditions (baseline, sham, post-sham, tDCS, and post-tDCS). In the tDCS condition, tDCS was applied for 12min with a current intensity of 1.5 mA, whereas tDCS was applied only for the first 30s in the sham condition. EEG PSD and brain network indices were computed for the alpha frequency band most closely associated with resting-state EEG. Both alpha PSD and network indices were found to significantly increase during and after tDCS application compared to those of the baseline condition in the EO state, but not in the EC state owing to the ceiling effect. Our results demonstrate the neuromodulatory effect of the tDCS device that does not generate significant tDCS-induced electrical artifacts, thereby allowing simultaneous measurement of electrical brain activity. We expect our novel tDCS device to be practically useful in exploring the impact of tDCS on neuromodulation more precisely using ongoing EEG data simultaneously measured during tDCS application.

Dynamic facial reanimation: feasibility of using an implantable electromagnetic actuator for active eye closure in facial nerve palsy

Dynamic facial reanimation: feasibility of using an implantable electromagnetic actuator for active eye closure in facial nerve palsy

Automatic characterization of stroke patients’ posturography based on probability density analysis

ObjectiveThe probability density analysis was applied to automatically characterize the center of pressure (COP) data for evaluation of the stroke patients’ balance ability.MethodsThe real-time COP coordinates of 38 stroke patients with eyes open and closed during quiet standing were obtained, respectively, from a precision force platform. The COP data were analyzed and characterized by the commonly used parameters: total sway length (SL), sway radius (SR), envelope sway area (EA), and the probability density analysis based parameters: projection area (PA), skewness (SK) and kurtosis (KT), and their statistical correlations were analyzed. The differences of both conventional parameters and probability density parameters under the conditions of eyes open (EO) and eyes closed (EC) were compared.ResultsThe PA from probability density analysis is strongly correlated with SL and SR. Both the traditional parameters and probability density parameters in the EC state are significantly different from those in the EO state. The obtained various statokinesigrams were calculated and categorized into typical sway types through probability density function for clinical evaluation of the balance ability of stroke patients.ConclusionsThe probability density analysis of COP data can be used to characterize the posturography for evaluation of the balance ability of stroke patients.