The role of the peripheral and central adrenergic system in the construction of the subjective emotional experience of panic.

RATIONALE: Although the study of emotions can look back to over 100 years of research, it is unclear which information the brain uses to construct the subjective experience of an emotion. OBJECTIVE: In the current study, we assess the role of the peripheral and central adrenergic system in this respect. METHODS: Healthy volunteers underwent a double inhalation of 35% CO2, which is a well-validated procedure to induce an intense emotion, namely panic. In a randomized, cross-over design, 34 participants received either a ß1-blocker acting selectively in the peripheral nervous system (atenolol), a ß1-blocker acting in the peripheral and central nervous system (metoprolol), or a placebo before the CO2 inhalation. RESULTS: Heart rate and systolic blood pressure were reduced in both ß-blocker conditions compared to placebo, showing effective inhibition of the adrenergic tone. Nevertheless, the subjective experience of the induced panic was the same in all conditions, as measured by self-reported fear, discomfort, and panic symptom ratings. CONCLUSIONS: These results indicate that information from the peripheral and central adrenergic system does not play a major role in the construction of the subjective emotion.

The Design and Implementation of Technology-Based Inclusive Classroom Activities in Inclusive Early Childhood Education and Care: A Pilot Study in Four European Countries.

Access to inclusive and qualitative education on an equal basis is a clear right of every child, even from the very beginning in Early Childhood Education and Care (ECEC). However, inclusive education is often not possible without access to appropriate (assistive) technologies. Notwithstanding the opportunities of technology to enhance inclusion of all children, it is still limitedly integrated by educators and teachers into their curriculum. Therefore, the SKATE project aims in gearing innovative technology as resource for inclusive education. This study describes and evaluates the preparation, the design, the implementation, and the effects of technology-based classroom activities in inclusive ECEC. The classroom activities are developed and implemented by school teams of 14 preschools spread over four European (EU) countries. A total of 50 school team members participated in a SKATE Learning Programme. This resulted in more than 20 technology-based inclusive class activities, created by school teams together with technology experts. Across the four countries, approximately 330 pre-schoolers, with and without special educational needs (SEN), participated. At this moment, 13 school team members from four EU countries and 45 parents from two EU countries evaluated the technology-based inclusive classroom activities. Nearly all teachers agreed that the activity promoted the inclusion of all children. Teachers reported that most of the children enjoyed the activity. This was confirmed in the evaluation by the parents. Most parents had the impression that the activity was meaningful, joyful and inclusive for all children.

Virtual Reality for Distraction and Relaxation in a Pediatric Hospital Setting: An Interventional Study With a Mixed-Methods Design.

Accumulating evidence supports the use of virtual reality (VR) as an effective pain and anxiety management tool for pediatric patients during specific medical procedures in dedicated patient groups. However, VR is still not widely adopted in everyday clinical practice. Feasibility and acceptability measures of clinicians' experiences are often missing in studies, thereby omitting an important stakeholder in VR use in a clinical setting. Therefore, the aim of this mixed-methods study was to investigate the feasibility, acceptability, tolerability (primary outcomes), and preliminary effectiveness (secondary outcome) of Relaxation-VR in both pediatric patients aged 4-16 years and clinicians. Relaxation-VR is a VR application prototype aimed to provide distraction and relaxation for a variety of patient populations and procedures and is used to reduce anxiety, stress (tension) and pain for children in hospital. Multiple measures of acceptability, feasibility and tolerability, and pre-to-post changes in measures of pain, anxiety, stress and happiness were assessed in pediatric patients. At the end of the study, acceptability and feasibility of VR use was assessed in clinicians. Results indicate that VR use (in particular, the Relaxation-VR prototype) for both distraction and relaxation is acceptable, feasible and tolerable for a variety of pediatric patients aged 4-16 years, as assessed in both patients and clinicians, and can reduce anxiety, pain and tension (stress), and increase happiness in a hospital setting.

Rehabilitation Supported by Technology: Protocol for an International Cocreation and User Experience Study.

BACKGROUND: Living labs in the health and well-being domain have become increasingly common over the past decade but vary in available infrastructure, implemented study designs, and outcome measures. The Horizon 2020 Project Virtual Health and Wellbeing Living Lab Infrastructure aims to harmonize living lab procedures and open living lab infrastructures to facilitate and promote research activities in the health and well-being domain in Europe and beyond. This protocol will describe the design of a joint research activity, focusing on the use of innovative technology for both rehabilitation interventions and data collection in a rehabilitation context. OBJECTIVE: With this joint research activity, this study primarily aims to gain insight into each living lab's infrastructure and procedures to harmonize health and well-being living lab procedures and infrastructures in Europe and beyond, particularly in the context of rehabilitation. Secondarily, this study aims to investigate the potential of innovative technologies for rehabilitation through living lab methodologies. METHODS: This study has a mixed methods design comprising multiple phases. There are two main phases of data collection: cocreation (phase 1) and small-scale pilot studies (phase 2), which are preceded by a preliminary harmonization of procedures among the different international living labs. An intermediate phase further allows the implementation of minor adjustments to the intervention or protocol depending on the input that was obtained in the cocreation phase. A total of 6 small-scale pilot studies using innovative technologies for intervention or data collection will be performed across 4 countries. The target study sample comprises patients with stroke and older adults with mild cognitive impairment. The third and final phases involve Delphi procedures to reach a consensus on harmonized procedures and protocols. RESULTS: Phase 1 data collection will begin in March 2022, and phase 2 data collection will begin in June 2022. Results will include the output of the cocreation sessions, small-scale pilot studies, and advice on harmonizing procedures and protocols for health and well-being living labs focusing on rehabilitation. CONCLUSIONS: The knowledge gained by the execution of this research will lead to harmonized procedures and protocols in a rehabilitation context for health and well-being living labs in Europe and beyond. In addition to the harmonized procedures and protocols in rehabilitation, we will also be able to provide new insights for improving the implementation of innovative technologies in rehabilitation. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/34537.

E-mental health implementation in inpatient care: Exploring its potential and future challenges.

Background: There is a great evidence base today for the effectiveness of e-mental health, or the use of technology in mental healthcare. However, large-scale implementation in mental healthcare organisations is lacking, especially in inpatient specialized mental healthcare settings. Aim: The current study aimed to gain insights into the factors that promote or hinder the implementation of e-mental health applications on organisational, professional and patient levels in Belgium. Methods: Four Belgian psychiatric hospitals and psychiatric departments of general hospitals invited their professionals and patients to use Moodbuster, which is a modular web-based platform with a connected smartphone application for monitoring. The platform was used in addition to treatment as usual for three to four months. The professionals and patients completed pre- and post-implementation questionnaires on their reasons to participate or to decline participation and experiences with the Moodbuster platform. Results: Main reasons for the organisations to participate in the implementation study were a general interest in e-mental health and seeing it is a helpful add-on to regular treatment. The actual use of Moodbuster by professionals and patients proved to be challenging with only 10 professionals and 24 patients participating. Implementation was hindered by technical difficulties and inpatient care specific factors such as lack of structural facilities to use e-mental health and patient-specific factors. Professionals saw value in using e-mental health applications for bridging the transition from inpatient to outpatient care. Twenty-two professionals and 31 patients completed the questionnaire on reasons not to participate. For the patients, lack of motivation because of too severe depressive symptoms was the most important reason not to participate. For professionals, it was lack of time and high workload. Conclusions: The current implementation study reveals several important barriers to overcome in order to successfully implement e-mental health in inpatient psychiatric care.

Physiological and self-reported arousal in virtual reality versus face-to-face emotional activation and cognitive restructuring in university students: A crossover experimental study using wearable monitoring.

BACKGROUND: Arousal may be important for learning to restructure ones' negative cognitions, a core technique in depression treatment. In virtual reality (VR), situations may be experienced more vividly than, e.g., in an imaginative approach, potentially aiding the emotional activation of negative cognitions. However, it is unclear whether such activation and subsequent cognitive restructuring in VR elicits more physiological, e.g. changes in skin conductance (SC), heart rate (HR), and self-reported arousal. METHOD: In a cross-over experiment, 41 healthy students experienced two sets, one in VR, one face-to-face (F2F), of three situations aimed at activating negative cognitions. Order of the sets and mode of delivery were randomised. A wristband wearable monitored SC and HR; self-reported arousal was registered verbally. RESULTS: Repeated measures analyses of variance revealed significantly more SC peaks per minute, F (1, 40) = 13.89, p = .001, higher mean SC, F (1,40) = 7.47, p = .001, and higher mean HR, F (1, 40) = 75.84, p < .001 in VR compared to F2F. No differences emerged on the paired-samples t-test for self-reported arousal, t (40) = -1.35, p = .18. DISCUSSION: To the best of our knowledge, this is the first study indicating that emotional activation and subsequent cognitive restructuring in VR can lead to significantly more physiological arousal compared to an imaginative approach. These findings need to be replicated before they can be extended to patient populations.

Feature selection methods for accelerometry-based seizure detection in children.

We investigate the application of feature selection methods and their influence on distinguishing nocturnal motor seizures in epileptic children from normal nocturnal movements using accelerometry signals. We studied two feature selection methods applied one after the other to reduce the complexity and computation costs of least-squares support vector machine (LS-SVM) models. Simultaneous feature selection analyses were performed for each seizure type individually and jointly. Starting from 140 features, a filter method based on mutual information was applied to remove irrelevant and redundant features. The obtained subset was further reduced through a wrapper feature selection strategy using an LS-SVM classifier with both forward search and backward elimination. The discriminative power of each feature subset was evaluated on the test data in terms of the area under the receiver operating characteristic curve, sensitivity, and false detection rate per hour. We showed that, by using only a filter method for feature selection, it was possible to obtain classification results of comparable or slightly reduced performance with respect to the complete feature set. The attained results could facilitate further development of accelerometry-based seizure detection and alarm systems.

Non-EEG seizure detection systems and potential SUDEP prevention: State of the art: Review and update.

PURPOSE: Detection of, and alarming for epileptic seizures is increasingly demanded and researched. Our previous review article provided an overview of non-invasive, non-EEG (electro-encephalography) body signals that can be measured, along with corresponding methods, state of the art research, and commercially available systems. Three years later, many more studies and devices have emerged. Moreover, the boom of smart phones and tablets created a new market for seizure detection applications. METHOD: We performed a thorough literature review and had contact with manufacturers of commercially available devices. RESULTS: This review article gives an updated overview of body signals and methods for seizure detection, international research and (commercially) available systems and applications. Reported results of non-EEG based detection devices vary between 2.2% and 100% sensitivity and between 0 and 3.23 false detections per hour compared to the gold standard video-EEG, for seizures ranging from generalized to convulsive or non-convulsive focal seizures with or without loss of consciousness. It is particularly interesting to include monitoring of autonomic dysfunction, as this may be an important pathophysiological mechanism of SUDEP (sudden unexpected death in epilepsy), and of movement, as many seizures have a motor component. CONCLUSION: Comparison of research results is difficult as studies focus on different seizure types, timing (night versus day) and patients (adult versus pediatric patients). Nevertheless, we are convinced that the most effective seizure detection systems are multimodal, combining for example detection methods for movement and heart rate, and that devices should especially take into account the user's seizure types and personal preferences.

Long-term accelerometry-triggered video monitoring and detection of tonic-clonic and clonic seizures in a home environment: Pilot study.

PURPOSE: The aim of our study was to test the efficacy of the VARIA system (video, accelerometry, and radar-induced activity recording) and validation of accelerometry-based detection algorithms for nocturnal tonic-clonic and clonic seizures developed by our team. METHODS: We present the results of two patients with tonic-clonic and clonic seizures, measured for about one month in a home environment with four wireless accelerometers (ACM) attached to wrists and ankles. The algorithms were developed using wired ACM data synchronized with the gold standard video-/electroencephalography (EEG) and then run offline on the wireless ACM signals. Detection of seizures was compared with semicontinuous monitoring by professional caregivers (keeping an eye on multiple patients). RESULTS: The best result for the two patients was obtained with the semipatient-specific algorithm which was developed using all patients with tonic-clonic and clonic seizures in our database with wired ACM. It gave a mean sensitivity of 66.87% and false detection rate of 1.16 per night. This included 13 extra seizures detected (31%) compared with professional caregivers' observations. CONCLUSION: While the algorithms were previously validated in a controlled video/EEG monitoring unit with wired sensors, we now show the first results of long-term, wireless testing in a home environment.

Automated Detection of Tonic-Clonic Seizures Using 3-D Accelerometry and Surface Electromyography in Pediatric Patients.

Epileptic seizure detection is traditionally done using video/electroencephalography monitoring, which is not applicable for long-term home monitoring. In recent years, attempts have been made to detect the seizures using other modalities. In this study, we investigated the application of four accelerometers (ACM) attached to the limbs and surface electromyography (sEMG) electrodes attached to upper arms for the detection of tonic-clonic seizures. sEMG can identify the tension during the tonic phase of tonic-clonic seizure, while ACM is able to detect rhythmic patterns of the clonic phase of tonic-clonic seizures. Machine learning techniques, including feature selection and least-squares support vector machine classification, were employed for detection of tonic-clonic seizures from ACM and sEMG signals. In addition, the outputs of ACM and sEMG-based classifiers were combined using a late integration approach. The algorithms were evaluated on 1998.3 h of data recorded nocturnally in 56 patients of which seven had 22 tonic-clonic seizures. A multimodal approach resulted in a more robust detection of short and nonstereotypical seizures (91%), while the number of false alarms increased significantly compared with the use of single sEMG modality (0.28-0.5/12h). This study also showed that the choice of the recording system should be made depending on the prevailing pediatric patient-specific seizure characteristics and nonepileptic behavior.

Accelerometry-based home monitoring for detection of nocturnal hypermotor seizures based on novelty detection.

Nocturnal home monitoring of epileptic children is often not feasible due to the cumbersome manner of seizure monitoring with the standard method of video/EEG-monitoring. We propose a method for hypermotor seizure detection based on accelerometers attached to the extremities. From the acceleration signals, multiple temporal, frequency, and wavelet-based features are extracted. After determining the features with the highest discriminative power, we classify movement events in epileptic and nonepileptic movements. This classification is only based on a nonparametric estimate of the probability density function of normal movements. Such approach allows us to build patient-specific models to classify movement data without the need for seizure data that are rarely available. If, in the test phase, the probability of a data point (event) is lower than a threshold, this event is considered to be an epileptic seizure; otherwise, it is considered as a normal nocturnal movement event. The mean performance over seven patients gives a sensitivity of 95.24% and a positive predictive value of 60.04%. However, there is a noticeable interpatient difference.

Non-EEG seizure-detection systems and potential SUDEP prevention: state of the art.

PURPOSE: There is a need for a seizure-detection system that can be used long-term and in home situations for early intervention and prevention of seizure related side effects including SUDEP (sudden unexpected death in epileptic patients). The gold standard for monitoring epileptic seizures involves video/EEG (electro-encephalography), which is uncomfortable for the patient, as EEG electrodes are attached to the scalp. EEG analysis is also labour-intensive and has yet to be automated and adapted for real-time monitoring. It is therefore usually performed in a hospital setting, for a few days at the most. The goal of this article is to provide an overview of body signals that can be measured, along with corresponding methods, state-of-art research, and commercially available systems, as well as to stress the importance of a good detection system. METHOD: Narrative literature review. RESULTS: A range of body signals can be monitored for the purpose of seizure detection. It is particularly interesting to include monitoring of autonomic dysfunction, as this may be an important patho-physiological mechanism of SUDEP, and of movement, as many seizures have a motor component. CONCLUSION: The most effective seizure detection systems are multimodal. Such systems should also be comfortable and low-power. The body signals and modalities on which a system is based should take account of the user's seizure types and personal preferences.

Long-term home monitoring of hypermotor seizures by patient-worn accelerometers.

Long-term home monitoring of epileptic seizures is not feasible with the gold standard of video/electro-encephalography (EEG) monitoring. The authors developed a system and algorithm for nocturnal hypermotor seizure detection in pediatric patients based on an accelerometer (ACM) attached to extremities. Seizure detection is done using normal movement data, meaning that the system can be installed in a new patient's room immediately as prior knowledge on the patient's seizures is not needed for the patient-specific model. In this study, the authors compared video/EEG-based seizure detection with ACM data in seven patients and found a sensitivity of 95.71% and a positive predictive value of 57.84%. The authors focused on hypermotor seizures given the availability of this seizure type in the data, the typical occurrence of these seizures during sleep, i.e., when the measurements were done, and the importance of detection of hypermotor seizures given their often refractory nature and the possible serious consequences. To our knowledge, it is the first detection system focusing on this type of seizure in pediatric patients.

On-site electronic observational assessment tool for discomfort and pain.

Over the recent years pen-paper observational assessment scales have proven to be useful to monitor behaviour and responses of humans and animals. Observational assessment tools are typically applied for subjects who are not able to communicate directly. For on-site observational assessment however it is hard to record and evaluate timing patterns of observed events using pen-paper scales. Although timing information is in many cases assumed highly valuable, only (videotaped) laboratory scales are able to benefit from this knowledge. In the work described in this paper we digitize pen-paper assessment scales resulting in new functionalities capable to improve assessment scores. A study of on-site pain and discomfort assessment of severely demented elderly is presented. The resulting system is a mobile electronic device with a graphical user interface (GUI) on a touch screen. Moreover digital information is stored in a database improving administration, providing immediate feedback and allowing applications like: visualisation, statistical analysis and scientific research like data mining. The device allows easily registering and automatically interpreting complex timing patterns of behaviours and responses, on-site. This feature could be employed in the development of new more accurate observational assessment instruments.

Acquiring a dataset of labeled video images showing discomfort in demented elderly.

One of the effects of late-stage dementia is the loss of the ability to communicate verbally. Patients become unable to call for help if they feel uncomfortable. The first objective of this article was to record facial expressions of bedridden demented elderly. For this purpose, we developed a video acquisition system (ViAS) that records synchronized video coming from two cameras. Each camera delivers uncompressed color images of 1,024 x 768 pixels, up to 30 frames per second. It is the first time that such a system has been placed in a patient's room. The second objective was to simultaneously label these video recordings with respect to discomfort expressions of the patients. Therefore, we developed a Digital Discomfort Labeling Tool (DDLT). This tool provides an easy-to-use software representation on a tablet PC of validated "paper" discomfort scales. With ViAS and DDLT, 80 different datasets were obtained of about 15 minutes of recordings. Approximately 80% of the recorded datasets delivered the labeled video recordings. The remainder were not usable due to under- or overexposed images and due to the patients being out of view as the system was not properly replaced after care. In one of 6 observed patients, nurses recognized a higher discomfort level that would not have been observed without the DDLT.