Clinical value of myocardial performance index in patients with isolated diastolic dysfunction.

AIMS: The Doppler-derived myocardial performance index (MPI) has been considered as a diagnostic and prognostic Doppler marker for many different clinical conditions. The purpose of this study was to determine the diagnostic accuracy of traditional Pulsed-wave Doppler (PWD-MPI) and Pulsed-wave tissue Doppler imaging (TDI-MPI) and the degree of agreement between these methods in patients with grade-I diastolic dysfunction (DDI) and a normal ejection fraction. METHODS: Forty-seven consecutive ambulatory patients with DDI were compared to 51 healthy subjects with normal echocardiograms. All subjects underwent measurement of time intervals and MPI with PWD and pulsed TDI. RESULTS: TDI-MPI and PWD-MPI were significantly higher in patients with DDI than in control subjects: 0.49 ± 0.14 vs. 0.40 ± 0.09 (P < 0.001) and 0.45 ± 0.11 vs. 0.37 ± 0.08 (P < 0.001), respectively. Cutoff values of TDI-MPI > 0.42 and PWD-MPI > 0.40 identified DDI subjects, with sensitivities of 74 and 64%; specificities of 61 and 69%; positive likelihood ratios of 1.9 and 2.0; and negative likelihood ratios of 0.42 and 0.53, respectively; no significant difference was noted between the areas under the ROC curves of TDI-MPI and PWD-MPI (P = 0.77). Bland-Altman plots showed wide limits of agreement between these indices: - 0.17 to 0.23 in healthy subjects and - 0.24 to 0.32 in DDI patients. CONCLUSION: PWD-MPI and TDI-MPI showed poor clinical agreement and were not reliable parameters for the assessment of left ventricular diastolic function.

Validation of a Single RGB-D Camera for Gait Assessment of Polyneuropathy Patients.

Motion analysis systems based on a single markerless RGB-D camera are more suitable for clinical practice than multi-camera marker-based reference systems. Nevertheless, the validity of RGB-D cameras for motor function assessment in some diseases affecting gait, such as Transthyretin Familial Amyloid Polyneuropathy (TTR-FAP), is yet to be investigated. In this study, the agreement between the Kinect v2 and a reference system for obtaining spatiotemporal and kinematic gait parameters was evaluated in the context of TTR-FAP. 3-D body joint data provided by both systems were acquired from ten TTR-FAP symptomatic patients, while performing ten gait trials. For each gait cycle, we computed several spatiotemporal and kinematic gait parameters. We then determined, for each parameter, the Bland Altman's bias and 95% limits of agreement, as well as the Pearson's and concordance correlation coefficients, between systems. The obtained results show that an affordable, portable and non-invasive system based on an RGB-D camera can accurately obtain most of the studied gait parameters (excellent or good agreement for eleven spatiotemporal and one kinematic). This system can bring more objectivity to motor function assessment of polyneuropathy patients, potentially contributing to an improvement of TTR-FAP treatment and understanding, with great benefits to the patients' quality of life.

Monkeys time their pauses of movement and not their movement-kinematics during a synchronization-continuation rhythmic task.

A critical question in tapping behavior is to understand whether the temporal control is exerted on the duration and trajectory of the downward-upward hand movement or on the pause between hand movements. In the present study, we determined the duration of both the movement execution and pauses of monkeys performing a synchronization-continuation task (SCT), using the speed profile of their tapping behavior. We found a linear increase in the variance of pause-duration as a function of interval, while the variance of the motor implementation was relatively constant across intervals. In fact, 96% of the variability of the duration of a complete tapping cycle (pause + movement) was due to the variability of the pause duration. In addition, we performed a Bayesian model selection to determine the effect of interval duration (450-1,000 ms), serial-order (1-6 produced intervals), task phase (sensory cued or internally driven), and marker modality (auditory or visual) on the duration of the movement-pause and tapping movement. The results showed that the most important parameter used to successfully perform the SCT was the control of the pause duration. We also found that the kinematics of the tapping movements was concordant with a stereotyped ballistic control of the hand pressing the push-button. The present findings support the idea that monkeys used an explicit timing strategy to perform the SCT, where a dedicated timing mechanism controlled the duration of the pauses of movement, while also triggered the execution of fixed movements across each interval of the rhythmic sequence.

Corrigendum: Clinical 3-D gait assessment of patients with polyneuropathy associated with hereditary transthyretin amyloidosis.

[This corrects the article DOI: 10.3389/fneur.2020.605282.].

Supporting the Assessment of Hereditary Transthyretin Amyloidosis Patients Based On 3-D Gait Analysis and Machine Learning.

Hereditary Transthyretin Amyloidosis (vATTR-V30M) is a rare and highly incapacitating sensorimotor neuropathy caused by an inherited mutation (Val30Met), which typically affects gait, among other symptoms. In this context, we investigated the possibility of using machine learning (ML) techniques to build a model(s) that can be used to support the detection of the Val30Met mutation (possibility of developing the disease), as well as symptom onset detection for the disease, given the gait characteristics of a person. These characteristics correspond to 24 gait parameters computed from 3-D body data, provided by a Kinect v2 camera, acquired from a person while walking towards the camera. To build the model(s), different ML algorithms were explored: k-nearest neighbors, decision tree, random forest, support vector machines (SVM), and multilayer perceptron. For a dataset corresponding to 66 subjects (25 healthy controls, 14 asymptomatic mutation carriers, and 27 patients) and several gait cycles per subject, we were able to obtain a model that distinguishes between controls and vATTR-V30M mutation carriers (with or without symptoms) with a mean accuracy of 92% (SVM). We also obtained a model that distinguishes between asymptomatic and symptomatic carriers with a mean accuracy of 98% (SVM). These results are very relevant, since this is the first study that proposes a ML approach to support vATTR-V30M patient assessment based on gait, being a promising foundation for the development of a computer-aided diagnosis tool to help clinicians in the identification and follow-up of this disease. Furthermore, the proposed method may also be used for other neuropathies.

Clinical 3-D Gait Assessment of Patients With Polyneuropathy Associated With Hereditary Transthyretin Amyloidosis.

Hereditary amyloidosis associated with transthyretin V30M (ATTRv V30M) is a rare and inherited multisystemic disease, with a variable presentation and a challenging diagnosis, follow-up and treatment. This condition entails a definitive and progressive motor impairment that compromises walking ability from near onset. The detection of the latter is key for the disease's diagnosis. The aim of this work is to perform quantitative 3-D gait analysis in ATTRv V30M patients, at different disease stages, and explore the potential of the obtained gait information for supporting early diagnosis and/or stage distinction during follow-up. Sixty-six subjects (25 healthy controls, 14 asymptomatic ATTRv V30M carriers, and 27 symptomatic patients) were included in this case-control study. All subjects were asked to walk back and forth for 2 min, in front of a Kinect v2 camera prepared for body motion tracking. We then used our own software to extract gait-related parameters from the camera's 3-D body data. For each parameter, the main subject groups and symptomatic patient subgroups were statistically compared. Most of the explored gait parameters can potentially be used to distinguish between the considered group pairs. Despite of statistically significant differences being found, most of them were undetected to the naked eye. Our Kinect camera-based system is easy to use in clinical settings and provides quantitative gait information that can be useful for supporting clinical assessment during ATTRv V30M onset detection and follow-up, as well as developing more objective and fine-grained rating scales to further support the clinical decisions.

Doppler-derived myocardial performance index in patients with impaired left ventricular relaxation and preserved systolic function.

BACKGROUND: The Doppler-derived myocardial performance index (MPI) has been used in the evaluation of left ventricular (LV) function in several diseases. In patients with isolated diastolic dysfunction, the diagnostic utility of this index remains unclear. The aim of this study was to determine the diagnostic utility of MPI in patients with systemic hypertension, impaired LV relaxation, and normal ejection fraction. METHODS: Thirty hypertensive patients with impaired LV relaxation were compared to 30 control subjects. MPI and its components, isovolumetric relaxation time (IRT), isovolumetric contraction time (ICT), and the ejection time (ET), were measured from LV outflow and mitral inflow Doppler velocity profiles. RESULTS: MPI was higher in patients than in control subjects (0.45 +/- 0.13 vs 0.37 +/- 0.07 P < 0.0029). The increase in MPI was due to the prolongation of IRT without significant change of ICT and ET. MPI cutoff value of > or =0.40 identified impaired LV relaxation with a sensitivity of 63% and specificity of 70% while an IRT >94 ms had a sensitivity of 67% and specificity of 80%. Multivariate analysis identified relative wall thickness, mitral early filling wave velocity (E), and systolic myocardial velocity (Sm) as independent predictors of MPI in patients with hypertension. CONCLUSIONS: MPI was increase in patients with hypertension, diastolic dysfunction, and normal ejection fraction but was not superior to IRT to detect impaired LV relaxation.

Full-body motion assessment: Concurrent validation of two body tracking depth sensors versus a gold standard system during gait.

RGB-D cameras provide 3-D body joint data in a low-cost, portable and non-intrusive way, when compared with reference motion capture systems used in laboratory settings. In this contribution, we evaluate the validity of both Microsoft Kinect versions (v1 and v2) for motion analysis against a Qualisys system in a simultaneous protocol. Two different walking directions in relation to the Kinect (towards - WT, and away - WA) were explored. For each gait trial, measures related with all body parts were computed: velocity of all joints, distance between symmetrical joints, and angle at some joints. For each measure, we compared each Kinect version and Qualisys by obtaining the mean true error and mean absolute error, Pearson's correlation coefficient, and optical-to-depth ratio. Although both Kinect v1 and v2 and/or WT and WA data present similar accuracy for some measures, better results were achieved, overall, when using WT data provided by the Kinect v2, especially for velocity measures. Moreover, the velocity and distance presented better results than angle measures. Our results show that both Kinect versions can be an alternative to more expensive systems such as Qualisys, for obtaining distance and velocity measures as well as some angles metrics (namely the knee angles). This conclusion is important towards the off-lab non-intrusive assessment of motor function in different areas, including sports and healthcare.

TTR-FAP Progression Evaluation Based on Gait Analysis Using a Single RGB-D Camera.

Transthyretin Familial Amyloid Polyneuropathy (TTR-FAP) is a rare and disabling neurological disorder caused by a mutation of the transthyretin gene. One of the disease's characteristics that mostly affects patients' quality of life is its influence on locomotion, with a variable evolution timing. Quantitative motion analysis is useful for assessing motor function, including gait, in diseases affecting movement. However, it is still an evolving field, especially in TTR-FAP, with only a few available studies. A single markerless RGB-D camera provides 3-D body joint data in a less expensive, more portable and less intrusive way than reference multi-camera marker-based systems for motion capture. In this contribution, we investigate if a gait analysis system based on a RGB-D camera can be used to detect gait changes over time for a given TTR-FAP patient. 3-D data provided by that system and a reference system were acquired from six TTR-FAP patients, while performing a simple gait task, once and then a year and a half later. For each gait cycle and system, several gait parameters were computed. For each patient, we investigated if the RBG-D camera system is able to detect the existence or not of statistically significant differences between the two different acquisitions (separated by 1.5 years of disease evolution), in a similar way to the reference system. The obtained results show the potential of using a single RGB-D camera to detect relevant changes in spatiotemporal gait parameters (e.g., stride duration and stride length), during TTR-FAP patient follow-up.

System for automatic gait analysis based on a single RGB-D camera.

Human gait analysis provides valuable information regarding the way of walking of a given subject. Low-cost RGB-D cameras, such as the Microsoft Kinect, are able to estimate the 3-D position of several body joints without requiring the use of markers. This 3-D information can be used to perform objective gait analysis in an affordable, portable, and non-intrusive way. In this contribution, we present a system for fully automatic gait analysis using a single RGB-D camera, namely the second version of the Kinect. Our system does not require any manual intervention (except for starting/stopping the data acquisition), since it firstly recognizes whether the subject is walking or not, and identifies the different gait cycles only when walking is detected. For each gait cycle, it then computes several gait parameters, which can provide useful information in various contexts, such as sports, healthcare, and biometric identification. The activity recognition is performed by a predictive model that distinguishes between three activities (walking, standing and marching), and between two postures of the subject (facing the sensor, and facing away from it). The model was built using a multilayer perceptron algorithm and several measures extracted from 3-D joint data, achieving an overall accuracy and F1 score of 98%. For gait cycle detection, we implemented an algorithm that estimates the instants corresponding to left and right heel strikes, relying on the distance between ankles, and the velocity of left and right ankles. The algorithm achieved errors for heel strike instant and stride duration estimation of 15 ± 25 ms and 1 ± 29 ms (walking towards the sensor), and 12 ± 23 ms and 2 ± 24 ms (walking away from the sensor). Our gait cycle detection solution can be used with any other RGB-D camera that provides the 3-D position of the main body joints.

The feasibility of an augment reality system to study the psychophysiological correlates of fear-related responses.

BACKGROUND: Previous studies have successfully used augmented reality (AR) as an aid to exposure-based treatments for anxiety disorders. However, to the best of our knowledge, none of these studies have measured the physiological correlates of the fear response, relying solely on self-reports and behavioral avoidance tests. METHODS: As the physiological defensive reactivity pattern impacts on the treatment effectiveness, we tested the feasibility of an AR system integrated in a mobile and wearable device for assessing the psychophysiological mechanisms (heart rate) involved in fear responses in real-life contexts. Specific phobia was used as a model given its prototypical defensive hyperreactivity toward the feared stimulus (spiders to spider phobics, in the current study). RESULTS: The results showed that the stimuli presented using AR were able to induce physiological alterations in the participants, which were specific depending on the stimulus type (fear or neutral) and on the participants' level of spider fear (phobic and control group). These physiological correlates of the fear response were reflected both in the intensity of heart rate (in relation to the baseline) and in the time needed to react and recover after the stimulus exposure. Finally, we tested a theoretical model that showed that the physiological responses of phobic individuals when facing their phobic stimulus only explained its own data. CONCLUSIONS: We argue in favor of the system's feasibility at capturing and quantifying the physiological dimension of fear-related responses, which may be of great value for diagnostic and treatment purposes in anxiety disorders, namely specific phobia.

NeuroKinect 3.0: Multi-Bed 3Dvideo-EEG System for Epilepsy Clinical Motion Monitoring.

Epilepsy diagnosis is typically performed through 2Dvideo-EEG monitoring, relying on the viewer's subjective interpretation of the patient's movements of interest. Several attempts at quantifying seizure movements have been performed in the past using 2D marker-based approaches, which have several drawbacks for the clinical routine (e.g. occlusions, lack of precision, and discomfort for the patient). These drawbacks are overcome with a 3D markerless approach. Recently, we published the development of a single-bed 3Dvideo-EEG system using a single RGB-D camera (Kinect v1). In this contribution, we describe how we expanded the previous single-bed system to a multi-bed departmental one that has been managing 6.61 Terabytes per day since March 2016. Our unique dataset collected so far includes 2.13 Terabytes of multimedia data, corresponding to 278 3Dvideo-EEG seizures from 111 patients. To the best of the authors' knowledge, this system is unique and has the potential of being spread to multiple EMUs around the world for the benefit of a greater number of patients.

A Grid framework for non-linear brain FMRI analysis.

Functional magnetic resonance imaging (fMRI) is an imaging technique that can be used to characterize brain physiological activity, usually presented as 3D volumes in function of time. In the context of our previous work in nonlinear association studies in electroencephalogram (EEG) time series, we were able to identify clinical relevant features useful in clinical diagnosis. The use of a similar approach in fMRI, now adapted for 3D time series, is both appealing and new. Such time series analysis imposes challenging requirements regarding computational power and medical image management. In this paper we propose a grid architecture framework to support the typical analysis protocol of association analysis applied to fMRI. The system, implemented using the gLite middleware, provides the necessary support to manage brain images and run non-linear fMRI analysis methods.

The first Transthyretin Familial Amyloid Polyneuropathy gait quantification study - preliminary results.

Transthyretin Familial Amyloid Polyneuropathy (TTR-FAP) is a rare neurological disease caused by a genetic mutation with a variable presentation and consequent challenging diagnosis, complex follow-up and treatment. At this moment, this condition has no cure and treatment options are under development. One of the disease's implications is a definite and progressive motor impairment that from the early stages compromises walking ability and daily life activities. The detection of this impairment is key for the disease onset diagnosis. With the goal of improving diagnosis of the symptoms and patients' quality of life, the authors have assessed the gait characteristics of subjects suffering from this condition. This contribution shows the results of a preliminary study, using a non-intrusive, markerless vision-based gait analysis tool. To the best of our knowledge, the reported results constitute the first gait analysis data of TTR-FAP mutation carriers.

Depression and Cardiovascular Disease in Women

Abstract The prevalence of depression varies from 1 to 17% in different geographic regions, and its incidence is 70% higher in women than men. Today, depression affects more than 300 million people worldwide, affecting twice as many women from adolescence to adulthood. In addition to this earlier onset, depression in women tends to be more severe. Cardiovascular disease and depression are chronic diseases that have a major impact on cardiovascular and all-cause morbidity and mortality, with evidence of a two-way relationship between them, in which depression is a predictor of cardiovascular disease and vice versa. In females, the degree of illness and prognosis are more severe when both diseases are present, than when diagnosed alone. In patients with acute or chronic cardiovascular disease, especially women, a systematic screening for depression should be considered as a preventive strategy of cardiovascular events, aiming to reduce the risk of future events. There are still no clinical studies designed to assess the impact of antidepressant treatment on cardiovascular outcomes in women.

Head and Neck Non-Melanoma Skin Cancer Treated By Superficial X-Ray Therapy: An Analysis of 1021 Cases.

INTRODUCTION: To report a single-institutional experience with the use of Superficial X-Ray Therapy (SXRT) for head and neck non-melanoma skin cancer (N-MSC) and to compare outcomes by prescribed fractionation schedules. MATERIALS AND METHODS: The medical records of 597 patients with 1021 lesions (720 BCC, 242 SCC, 59 SCC in situ) treated with kilovoltage radiation from 1979-2013 were retrospectively reviewed. The majority of patients were treated according to 1 of 3 institutional protocols based on the discretion of the radiation oncologist: 1) 22 x 2.5 Gy; 2) 20 x 2.5 Gy; 3) 30 x 2.0 Gy. "T" stage at first presentation was as follows: Tis (59); T1 (765); T2 (175); T3 (6), T4 (9); Tx, (7). All patients were clinical N0 and M0 at presentation. Chi-square test was used to evaluate any potential association between variables. The Kaplan-Meier method was used to analyze survival with the Log Rank test used for comparison. A Cox Regression analysis was performed for multivariate analysis. RESULTS: The median follow up was 44 months. No significant difference was observed among the 3 prescribed fractionation schemes (p = 0.78) in terms of RTOG toxicity. There were no failures among SCC in situ, 37 local failures (23 BCC, 14 SCC), 5 regional failures (all SCC) and 2 distant failures (both SCC). For BCC, the 5-year LC was 96% and the 10-year LC was 94%. For SCC the corresponding rates of local control were 92% and 87%, respectively (p = 0.03). The use of >2.0 Gy daily was significantly associated with improved LC on multivariate analysis (HR: 0.17; CI 95%: 0.05-0.59). CONCLUSION: SXRT for N-MSC of the head and neck is well tolerated, achieves excellent local control, and should continue to be recommended in the management of this disease. Fractionation schedules using >2.0 Gy daily appear to be associated with improved LC.

NeuroKinect: A Novel Low-Cost 3Dvideo-EEG System for Epileptic Seizure Motion Quantification.

Epilepsy is a common neurological disorder which affects 0.5-1% of the world population. Its diagnosis relies both on Electroencephalogram (EEG) findings and characteristic seizure-induced body movements--called seizure semiology. Thus, synchronous EEG and (2D)video recording systems (known as Video-EEG) are the most accurate tools for epilepsy diagnosis. Despite the establishment of several quantitative methods for EEG analysis, seizure semiology is still analyzed by visual inspection, based on epileptologists' subjective interpretation of the movements of interest (MOIs) that occur during recorded seizures. In this contribution, we present NeuroKinect, a low-cost, easy to setup and operate solution for a novel 3Dvideo-EEG system. It is based on a RGB-D sensor (Microsoft Kinect camera) and performs 24/7 monitoring of an Epilepsy Monitoring Unit (EMU) bed. It does not require the attachment of any reflectors or sensors to the patient's body and has a very low maintenance load. To evaluate its performance and usability, we mounted a state-of-the-art 6-camera motion-capture system and our low-cost solution over the same EMU bed. A comparative study of seizure-simulated MOIs showed an average correlation of the resulting 3D motion trajectories of 84.2%. Then, we used our system on the routine of an EMU and collected 9 different seizures where we could perform 3D kinematic analysis of 42 MOIs arising from the temporal (TLE) (n = 19) and extratemporal (ETE) brain regions (n = 23). The obtained results showed that movement displacement and movement extent discriminated both seizure MOI groups with statistically significant levels (mean = 0.15 m vs. 0.44 m, p<0.001; mean = 0.068 m(3) vs. 0.14 m(3), p<0.05, respectively). Furthermore, TLE MOIs were significantly shorter than ETE (mean = 23 seconds vs 35 seconds, p<0.01) and presented higher jerking levels (mean = 345 ms(-3) vs 172 ms(-3), p<0.05). Our newly implemented 3D approach is faster by 87.5% in extracting body motion trajectories when compared to a 2D frame by frame tracking procedure. We conclude that this new approach provides a more comfortable (both for patients and clinical professionals), simpler, faster and lower-cost procedure than previous approaches, therefore providing a reliable tool to quantitatively analyze MOI patterns of epileptic seizures in the routine of EMUs around the world. We hope this study encourages other EMUs to adopt similar approaches so that more quantitative information is used to improve epilepsy diagnosis.

A novel portable, low-cost kinect-based system for motion analysis in neurological diseases.

Many neurological diseases, such as Parkinson's disease and epilepsy, can significantly impair the motor function of the patients, often leading to a dramatic loss of their quality of life. Human motion analysis is regarded as fundamental towards an early diagnosis and enhanced follow-up in this type of diseases. In this contribution, we present NeuroKinect, a novel system designed for motion analysis in neurological diseases. This system includes an RGB-D camera (Microsoft Kinect) and two integrated software applications, KiT (KinecTracker) and KiMA (Kinect Motion Analyzer). The applications enable the preview, acquisition, review and management of data provided by the sensor, which are then used for motion analysis of relevant events. NeuroKinect is a portable, low-cost and markerless solution that is suitable for use in the clinical environment. Furthermore, it is able to provide quantitative support to the clinical assessment of different neurological diseases with movement impairments, as demonstrated by its usage in two different clinical routine scenarios: gait analysis in Parkinson's disease and seizure semiology analysis in epilepsy.

What does an epileptiform spike look like in MEG? Comparison between coincident EEG and MEG spikes.

Recent investigations suggest that there are differences between the characteristics of EEG and MEG epileptiform spikes. The authors performed an objective characterization of the morphology of epileptiform spikes recorded simultaneously in both EEG and MEG to determine whether they present the same morphologic characteristics. Based on a stepwise approach, the authors performed a computer analysis of EEG and MEG of a set of coincident epileptiform transients selected by a senior clinical neurophysiologist in recordings of three patients with drug-resistant epilepsy. A computer-based algorithm was applied to extract parameters that could be used to describe quantitatively the morphology of the transients, followed by a statistical comparison over the extracted metrics of the EEG and MEG waveforms. EEG and MEG coincident events were statistically different with respect to several morphologic characteristics, such as duration, sharpness, and shape. The differences found appear to be a consequence of MEG signals not being influenced by volume propagation through the tissues with different conductivities that surround the brain, compared with EEG, and of the different orientation of the underlying dipolar sources. The results indicate that visual inspection of MEG spikes and automatic spike-detector algorithms should use criteria adapted to the specific characteristics of the MEG, and not simply those used on conventional EEG.

Monitoring physiology and behavior using Android in phobias.

In this paper, we present an Android-based system Application - AWARE - for the assessment of the person's physiology and behavior outside of the laboratory. To accomplish this purpose, AWARE delivers context dependent audio-visual stimuli, embedded into the subject's real-world perception, via marker/vision-based augmented reality (AR) technology. In addition, it employs external measuring resources connected via Bluetooth, as well as the smartphone's integrated resources. It synchronously acquires the experiment's video (camera input with AR overlay), physiologic responses (with a dedicated ECG measuring device) and behavior (through movement and location, with accelerometer/gyroscope and GPS, respectively). Psychological assessment is heavily based on laboratory procedures, even though it is known that these settings disturb the subjects' natural reactions and condition. The major idea of this application is to evaluate the participant condition, mimicking his/her real life conditions. Given that phobias are rather context specific, they represent the ideal candidate for assessing the feasibility of a mobile system application. AWARE allowed presenting AR stimuli (e.g., 3D spiders) and quantifying the subjects' reactions non-intrusively (e.g., heart rate variation) - more emphatic in the phobic volunteer when presented with spider vs non phobic stimulus. Although still a proof of concept, AWARE proved to be flexible, and straightforward to setup, with the potential to support ecologically valid monitoring experiments.