Wearable devices enable continuous monitoring of physiological signals in real‐world settings, yet a standardized approach for synchronizing signals across devices remains lacking. We present a generalizable, user‐friendly pipeline that enables synchronization of any two devices capturing the same physiological signals, without requiring coding expertise. The pipeline performs resampling, dynamic time warping alignment, amplitude correction via wavelet transforms, and signal standardization, followed by agreement analyses at both waveform and feature levels. To demonstrate its validity, we applied the pipeline to a case study comparing two research‐grade devices, the Empatica E4 and the EmbracePlus, using up to 48 h of concurrent recordings from 31 participants. We compared signal‐level agreement across waveform similarity, amplitude distribution, spectral content, and extracted features between the two research‐grade devices to determine their interchangeability for longitudinal and multi‐site studies. Specifically, we aimed to determine how well these devices agree at the signal level and to identify which physiological signals are most robust to device‐specific variability. Four signals were examined (blood volume pulse, electrodermal activity, accelerometry, and temperature) using NeuroKit2 and FLIRT. We computed Pearson and concordance correlation coefficients, Bland–Altman bias and limits of agreement, root mean squared error (RMSE), KL divergence, spectral coherence, mutual information, and feature‐level correlations using NeuroKit2 and FLIRT. Results showed near‐perfect agreement for BVP (concordance correlation coefficient (CCC) ≈ 1.0; coherence ≤ 0.98) and phasic EDA features (CCC 0.85–0.99), whereas tonic EDA, temperature, and accelerometry exhibited systematic amplitude biases (EmbracePlus lower) and axis‐dependent variability (Z‐axis CCC = 0.85; Y‐axis = 0.19). Relative signal dynamics were preserved across devices despite differences in absolute levels. These findings support integration of BVP, EDA, and TEMP data across E4 and EmbracePlus with proper preprocessing, while highlighting calibration needs for movement signals.

BackgroundPatients with mild to borderline intellectual disability (MBID) are overrepresented in forensic settings. In forensic psychiatric centers (FPCs), aggressive incidents are more frequent among offenders with MBID. Enhancing regular aggression regulation training with Virtual Reality (VR) technology could be effective by providing immersive roleplays and focusing on learning new behavior.ObjectiveThis pilot study aimed to preliminary investigate the effects of the VR Aggression Prevention Training - Intellectual Disability (VRAPT-ID) on reducing aggressive behavior in forensic inpatients with MBID.MethodsA single case experimental design (SCED) study with a multiple baseline approach was conducted. Arousal levels during training sessions were monitored using the Empatica E4, a wristband that measured pulse rate (PR), pulse rate variability (PRV) and electrodermal activity (EDA). Aggressive behavior was measured using the Social Dysfunction and Aggression Scale (SDAS). Therapeutic alliance was assessed with the Session Rating Scale (SRS), a qualitative questionnaire.ResultsFive out of 10 participants completed the entire training. The results showed that VRAPT-ID was associated with a decrease in aggressive behavior in four of the five participants who completed the intervention. Analysis showed that skin conductance responses (electrodermal activity), as an indicator of arousal, increased significantly during training sessions, which may reflect increased physiological activation during sessions, although no direct link with behavioral change was established. No significant changes were observed in pulse rate (PR). Pulse rate variability (PRV) data contained too many artifacts and therefore could not be reliably analyzed. Regarding therapeutic alliance, all participants who completed the training reported that VRAPT-ID helped them manage anger more effectively and that they found the training enjoyable.ConclusionThe results of this pilot study suggest that VRAPT-ID may be a feasible and potentially promising intervention for addressing aggressive behavior in individuals with MBID in a forensic setting. Future research, including RCT, is needed to further examine these preliminary findings and to investigate the proposed underlying mechanisms of VRAPT-ID.

Background People with mild intellectual disabilities (MID) are at increased risk of developing PTSD. EMDR therapy appears to be an effective treatment for the treatment of PTSD but communicating stress levels during therapy can be challenging. Wearables may provide additional insight into physiological arousal during treatment. This feasibility study evaluated the acceptability and potential clinical value of wearable physiological monitoring during EMDR therapy in four adults with MID and PTSD. Methods A single-case design was used, collecting minute-by-minute physiological data during EMDR therapy sessions. Feasibility of wearable use was assessed with customized questionnaires completed by participants and therapists. Physiological data were synchronized with EMDR protocol components and analyzed descriptively alongside subjective units of distress (SUD) scores. Overall patterns of arousal across sessions were summarized using boxplots. Results Wearables were considered acceptable by participants and therapists, although technical difficulties were reported. Participants showed reductions in subjective distress during EMDR therapy, but physiological findings were heterogeneous. Little support for a pronounced pattern of de-arousal across EMDR sessions was found, with observed changes being small relative to between-session variability. Conclusion Using wearables during EMDR therapy in adults with MID and PTSD appears acceptable although technical problems seem to be a feasibility barrier. Physiological findings were difficult to interpret, limiting conclusions about consistent patterns of ANS functioning during EMDR therapy. Future research should include larger samples, contextual factors, and baseline and follow-up measurements.

BACKGROUND:Assessment of adaptive functioning is part of the classification of intellectual disability and borderline intellectual functioning and important in estimating support needs. Adaptive functioning may be impaired in clients with psychiatric comorbidity. We investigated relationships between adaptive functioning and psychiatric comorbidity in individuals with intellectual disabilities or borderline intellectual functioning using the ADAPT. METHOD:ADAPT scores of clients with comorbid psychiatric disorders were compared with those of clients without comorbidity (N = 4376). RESULTS:In clients with intellectual disabilities, ASD was associated with lower ADAPT scores while depressive mood disorder was associated with higher ADAPT scores. We found a negative relationship between number of psychiatric disorders and mean total ADAPT score. CONCLUSION:When determining the severity of an intellectual disability or using the V-code borderline intellectual functioning, ASD and multiple comorbidities must be taken into account to prevent an intellectual disability or borderline intellectual functioning from being incorrectly classified.

Abstract Unobtrusive stress detection using wearable sensors could enable scalable, continuous mental-health monitoring. However, stress is an inherently subjective state that can only be inferred indirectly from physiological signals, making generalizable detection in naturalistic settings challenging. Although prior work has focused on improving model performance, it remains unclear whether wearable physiology supports a shared cross-individual mapping to subjective stress or whether this relationship is fundamentally person-specific. We evaluated feature-based and deep-learning models across multiple physiological modalities using ecological momentary assessment (EMA) as the reference standard, comparing within- and between-individual modeling approaches. Within-individual models achieved modest but consistent improvements in stress detection, whereas between-individual models consistently failed to generalize, yielding negative R 2 values despite multimodal fusion and high-capacity architectures. Error analyses revealed regression to the mean, reduced sensitivity to high-stress states, and residual associations with general physiological activation, highlighting the limited stress specificity of wearable physiology. These findings suggest that wearable stress detection is fundamentally a personalized inference problem and that future systems should prioritize individual adaptation and contextual modeling over universal stress predictors.

BACKGROUND:Self-harm is common in people with intellectual disabilities and is associated with multiple adverse consequences for the client engaging in self-harm, other clients and caregivers. Self-harm is related to emotional dysregulation according to both observational and self-report data. Measures of the autonomic nervous system might provide additional insight in this relationship. METHODS:The current systematic review systematically summarized a broad spectrum of studies on the association between self-harm and physiological parameters. The search identified 2400 articles, 46 were included. RESULTS:In most studies, which compared electrodermal activity and heart rate in people with and without self-harm, no clear indications for a relation between physiology and self-harm was found. Studies on heart rate variability showed indications for lower heart rate variability during recovery, which could imply emotion dysregulation, findings which were supported by results from imagery studies (heart rate and skin conductance). No consistent findings were found when self-harm was studied before, during or after actual occurrences of self-harm, although this was examined by very few studies. CONCLUSIONS:Although wearable technology has improved, the majority of studies to date are lab-studies. Future research should focus on measuring physiology in daily life before, during and after self-harm, in people with intellectual disabilities, study different types and functions of self-harm separately, and test multimodal prediction models. This knowledge could improve the understanding, prevention and assessment of this debilitating behaviour.

BACKGROUND:Many people with mild intellectual disabilities are at increased risk to experience stress. Reducing stress is important because experiencing prolonged and elevated stress can have detrimental effects on mental and physical health and it is associated with aggressive behaviour and self-harm. AIMS:This preliminary study investigated whether an intervention combining biofeedback with listening to music is effective and whether a personalized music playlist is more effective than self-selected music in reducing physiological and subjective stress in participants with mild intellectual disabilities. METHODS:We collected 103 music listening sessions over a period of 2-4 weeks for 11 participants throughout their daily routines. They listened to music when they received biofeedback on their increased stress level (as measured by wearable biosensor Nowatch) or when they themselves felt stressed. Participants listened either to self-selected music or to a personalised playlist compiled with X-system, music technology that predicts the effect of a song on levels of autonomic arousal. Pulse rate (PR) and skin conductance level (SCL) were measured with the EmbracePlus and subjective feelings of stress and mood were measured with two scale questions. After the intervention phase, participants and their caregivers completed a short questionnaire to evaluate their experiences with using the X-system playlist. RESULTS:Mixed regression analyses showed reductions in PR and SCL during listening to music, and indications were found for reductions in subjective stress and improvement of mood after intervention. Listening to music compiled with X-system was not more effective than listening to self-selected music. However, lower combined arousal values (a feature of X-system) from self-selected and X-system music predicted lower PR and SCL, indicating that these indices can be used to select songs that have a relaxing or energizing effect. CONCLUSIONS AND IMPLICATIONS:The present study suggests that music listening is associated with both subjective and physiological stress reduction. Listening to music might be an accessible, inexpensive and empowering strategy for stress reduction and improving emotion regulation, which could also benefit mental and physical health. Several challenges were encountered while implementing the intervention and suggestions for future research are given.

BACKGROUND:Aggressive behaviour (AB) and non-suicidal self-injury (NSSI) are common in people with mild intellectual disability or borderline intellectual functioning, leading to adverse consequences for themselves and those around them. METHOD:We investigated the relationship between AB (both total and physical in particular) and NSSI and risk factors in 125 residents in a treatment clinic using incident reports and standard clinical measurements. RESULTS:There was a weak correlation between AB and NSSI, as well as between impulsivity and total AB, and between coping and AB and NSSI. However, NSSI, impulsivity and coping skills did not predict AB. CONCLUSION:Results do not corroborate those of other studies in this area. In future studies impulsivity, coping, aggression and NSSI may be measured using other instruments, and differences between people with and without intellectual disability regarding these variables may be explored.

IntroductionForensic psychiatric patients receive treatment to address their violent and aggressive behavior with the aim of facilitating their safe reintegration into society. On average, these treatments are effective, but the magnitude of effect sizes tends to be small, even when considering more recent advancements in digital mental health innovations. Recent research indicates that wearable technology has positive effects on the physical and mental health of the general population, and may thus also be of use in forensic psychiatry, both for patients and staff members. Several applications and use cases of wearable technology hold promise, particularly for patients with mild intellectual disability or borderline intellectual functioning, as these devices are thought to be user-friendly and provide continuous daily feedback.MethodIn the current randomized crossover trial, we addressed several limitations from previous research and compared the (continuous) usability and acceptance of four selected wearable devices. Each device was worn for one week by staff members and patients, amounting to a total of four weeks. Two of the devices were general purpose fitness trackers, while the other two devices used custom made applications designed for bio-cueing and for providing insights into physiological reactivity to daily stressors and events.ResultsOur findings indicated significant differences in usability, acceptance and continuous use between devices. The highest usability scores were obtained for the two fitness trackers (Fitbit and Garmin) compared to the two devices employing custom made applications (Sense-IT and E4 dashboard). The results showed similar outcomes for patients and staff members.DiscussionNone of the devices obtained usability scores that would justify recommendation for future use considering international standards; a finding that raises concerns about the adaptation and uptake of wearable technology in the context of forensic psychiatry. We suggest that improvements in gamification and motivational aspects of wearable technology might be helpful to tackle several challenges related to wearable technology.

BACKGROUND:Affective states influence the sympathetic nervous system, inducing variations in electrodermal activity (EDA), however, EDA association with bipolar disorder (BD) remains uncertain in real-world settings due to confounders like physical activity and temperature. We analysed EDA separately during sleep and wakefulness due to varying confounders and potential differences in mood state discrimination capacities. METHODS:We monitored EDA from 102 participants with BD including 35 manic, 29 depressive, 38 euthymic patients, and 38 healthy controls (HC), for 48 h. Fifteen EDA features were inferred by mixed-effect models for repeated measures considering sleep state, group and covariates. RESULTS:Thirteen EDA feature models were significantly influenced by sleep state, notably including phasic peaks (p < 0.001). During wakefulness, phasic peaks showed different values for mania (M [SD] = 6.49 [5.74, 7.23]), euthymia (5.89 [4.83, 6.94]), HC (3.04 [1.65, 4.42]), and depression (3.00 [2.07, 3.92]). Four phasic features during wakefulness better discriminated between HC and mania or euthymia, and between depression and euthymia or mania, compared to sleep. Mixed symptoms, average skin temperature, and anticholinergic medication affected the models, while sex and age did not. CONCLUSION:EDA measured from awake recordings better distinguished between BD states than sleep recordings, when controlled by confounders.

In the study of synchronization dynamics between interacting systems, several techniques are available to estimate coupling strength and coupling direction. Currently, there is no general ‘best’ method that will perform well in most contexts. Inter-system recurrence networks (IRN) combine auto-recurrence and cross-recurrence matrices to create a graph that represents interacting networks. The method is appealing because it is based on cross-recurrence quantification analysis, a well-developed method for studying synchronization between 2 systems, which can be expanded in the IRN framework to include N > 2 interacting networks. In this study we examine whether IRN can be used to analyze coupling dynamics between physiological variables (acceleration, blood volume pressure, electrodermal activity, heart rate and skin temperature) observed in a client in residential care with severe to profound intellectual disabilities (SPID) and their professional caregiver. Based on the cross-clustering coefficients of the IRN conclusions about the coupling direction (client or caregiver drives the interaction) can be drawn, however, deciding between bi-directional coupling or no coupling remains a challenge. Constructing the full IRN, based on the multivariate time series of five coupled processes, reveals the existence of potential feedback loops. Further study is needed to be able to determine dynamics of coupling between the different layers.

Aggression incidents are common in residential youth care, and impede treatment progress and the possibility of evolving into an independent healthy individual. Aggression incidents can lead to feelings of anxiety and unsafety in others, and can have major physical and/or traumatic impact for everyone involved. Current methods to prevent incidents are based on observations of increasing tension by professionals or adolescents themselves, however, they both might have difficulties recognizing these signals. A complementary and promising alternative might be the measurement of physiological reactivity to observe the stress response or increasing tension in adolescents. The present study used a wearable wireless device to examine patterns of physiological reactivity prior to aggression incidents in residential youth care. A total of 19 adolescents in residential youth care participated, who were involved in 87 aggression incidents during study participation. Participants wore a wearable wireless device to measure physiological stress response parameters (peaks per minute (PPM) , skin conductance (SCL), heart rate (HR)) during three, preferably consecutive, weeks, in which aggression incidents were accurately registered. Longitudinal multilevel models showed that PPM rose preceding incidents, but we failed to replicate previous SCL and HR findings in relation to incidents, as there was no significant effect for time, although both slopes did rise preceding aggression incidents. In sum, this study supports the idea that wearable devices measuring physiological stress reactivity might help in the prevention of aggression incidents. There is, however, high within-subject variation, which suggests that future studies should examine more personalized feedback and interventions to take this within-subject variation into account. To date, only a few tools adjusted the interface to this young (clinical) population, and store the data locally on the users’ phone.

BACKGROUND:Bipolar disorder (BD) lacks objective measures for illness activity and treatment response. Electrodermal activity (EDA) is a quantitative measure of autonomic function, which is altered in manic and depressive episodes. We aimed to explore differences in EDA (1) inter-individually: between patients with BD on acute mood episodes, euthymic states and healthy controls (HC), and (2) intra-individually: longitudinally within patients during acute mood episodes of BD and after clinical remission. METHODS:A longitudinal observational study. EDA was recorded using a research-grade wearable in patients with BD during acute manic and depressive episodes and at clinical remission. Euthymic BD patients and HC were recorded during a single session. We compared EDA parameters derived from the tonic (mean EDA, mEDA) and phasic components (EDA peaks per minute, pmEDA, and EDA peaks mean amplitude, pmaEDA). Inter- and intra-individual comparisons were computed respectively with ANOVA and paired t-tests. RESULTS:49 patients with BD (15 manic, 9 depressed, and 25 euthymic), and 19 HC were included. Patients with bipolar depression showed significantly reduced mEDA (p = 0.003) and pmEDA (p = 0.001), which increased to levels similar to euthymia or HC after clinical remission (mEDA, p = 0.011; pmEDA, p < 0.001; pmaEDA, p < 0.001). Manic patients showed no differences compared to euthymic patients and HCs, but a significant reduction of tonic and phasic EDA parameters after clinical remission (mEDA, p = 0.035; pmEDA, p = 0.004). LIMITATIONS:Limited sample size, high inter-individual variability of EDA parameters, limited comparability to previous studies and non-adjustment for medication. CONCLUSION:EDA ecological monitoring might provide several opportunities for early detection of depressive symptoms, and might aid at assessing early response to treatments in mania and bipolar depression.

Introduction: In this study, we explored if low vision or blindness affects adaptive functioning in individuals with and without intellectual disabilities, using the adaptive ability performance test (ADAPT). Method: Two hundred and nine ADAPTs were collected from individuals with low vision and blindness who were in care or lived independently. ADAPT scores were compared with 2642 ADAPT scores from sighted individuals. Separate comparisons were made for intellectually disabled and nonintellectually disabled groups. Results: ADAPT scores of low vision and blind individuals in both intellectually disabled and nonintellectually disabled groups were significantly lower than those of sighted individuals. ADAPT scores did not differ significantly between low vision and blind individuals. Reference values were established for individuals with visual impairments with and without intellectual disabilities. Discussion: Despite some limitations of this study, we conclude that adaptive skills are lower in individuals with visual impairments than in sighted individuals. Cross-cultural studies are required. Information for Practitioners: The results of this study provide insight into adaptive skills in individuals with visual impairments. Reference data on the ADAPT can be used for the classification of (the severity of) intellectual disabilities and assessment of the need for support or training of adaptive skills, which makes the ADAPT a useful instrument for professionals who work with individuals with visual impairments with and without intellectual disabilities.

Listening to music can have a calming effect on people, but the natural "consumption" of music is generally not used in a goal-oriented way to reduce physiological arousal (i.e., heart rate and skin conductance) and tension, and to enhance mood. X-System is designed to predict the innate neurophysiological response to pieces of music and influence the arousal levels of users. We hypothesized that listening to a preferred genre of music has beneficial physiological and psychological effects and that X-System had an effect over and above the use of preferred music genres. A small-scale study (N = 38) was conducted in a medium secure forensic psychiatric facility to investigate the effects of passive music therapy on the arousal, tension, and mood of patients and their caregivers. Participants listened to a selection of songs of their preferred music genre for 2 days. On one of the 2 days, the music selection was played in an order established by X-System, with the aim to maximally reduce arousal, whereas on the other day the music selection was played in random order. In both conditions, physiological indices and self-reported tension decreased after listening to the preferred music. The hypothesized accelerated reduction in skin conductance for the X-System playlist was evident on visual inspection of the data, but the trend was non-significant (p = .065). The use of personalized music in forensic psychiatry might be a relatively effective, inexpensive way to benefit patients and staff members, especially patients that are hesitant to engage in the more traditional therapies.

BACKGROUND:The adaptive ability performance test (ADAPT) was developed to assess adaptive skills in individuals with intellectual disabilities and borderline intellectual functioning, with or without mental disorders. As a follow-up to earlier research on the ADAPT, a factor analytic study was conducted.METHOD:One thousand and sixty six ADAPTs from clients with (suspected) intellectual disabilities or borderline intellectual functioning and 129 ADAPTs from participants from the general population were collected along with other characteristics (e.g., IQ, psychiatric classifications, living situation).RESULTS:An exploratory factor analysis (EFA) was performed and resulted in good fit indices. Subsequent confirmatory factor analysis (CFA) and multigroup CFA showed acceptable to good fit indices. This resulted in an instrument with eight factors and 62 items.CONCLUSION:Factor analytic results suggest that the ADAPT is a valid instrument that measures adaptive skills in individuals with intellectual disabilities or borderline intellectual functioning.

The associations between physiological measures (i.e., heart rate and skin conductance) of autonomic nervous system (ANS) activity and severe antisocial spectrum behavior (AB) were meta-analyzed. We used an exhaustive partitioning of variables relevant to the ANS-AB association and investigated four highly relevant questions (on declining effect sizes, psychopathy subscales, moderators, and ANS measures) that are thought to be trans formative for future research on AB. We investigated a broad spectrum of physiological measures (e.g., heart rate (variability), pre-ejection period) in relation to AB. The search date for the current meta-analysis was on January 1st, 2020, includes 101 studies and 769 effect sizes. Results indicate that effect sizes are heterogeneous and bidirectional. The careful partitioning of variables sheds light on the complex associations that were obscured in previous meta-analyses. Effects are largest for the most violent offenders and for psychopathy and are dependent on the experimental tasks used, parameters calculated, and analyses run. Understanding the specificity of physiological reactions may be expedient for differentiating between (and within) types of AB.

Physiological signals (e.g., heart rate, skin conductance) that were traditionally studied in neuroscientific laboratory research are currently being used in numerous real-life studies using wearable technology. Physiological signals obtained with wearables seem to offer great potential for continuous monitoring and providing biofeedback in clinical practice and healthcare research. The physiological data obtained from these signals has utility for both clinicians and researchers. Clinicians are typically interested in the day-to-day and moment-to-moment physiological reactivity of patients to real-life stressors, events, and situations or interested in the physiological reactivity to stimuli in therapy. Researchers typically apply signal analysis methods to the data by pre-processing the physiological signals, detecting artifacts, and extracting features, which can be a challenge considering the amount of data that needs to be processed. This paper describes the creation of a "Wearables" R package and a Shiny "E4 dashboard" application for an often-studied wearable, the Empatica E4. The package and Shiny application can be used to visualize the relationship between physiological signals and real-life stressors or stimuli, but can also be used to pre-process physiological data, detect artifacts, and extract relevant features for further analysis. In addition, the application has a batch process option to analyze large amounts of physiological data into ready-to-use data files. The software accommodates users with a downloadable report that provides opportunities for a careful investigation of physiological reactions in daily life. The application is freely available, thought to be easy to use, and thought to be easily extendible to other wearable devices. Future research should focus on the usability of the application and the validation of the algorithms.