A standardized validity assessment protocol for physiological signals from wearable technology: Methodological underpinnings and an application to the E4 biosensor

From lab to life: Evaluating the reliability and validity of psychophysiological data from wearable devices in laboratory and ambulatory settings

Despite the increasing popularity of ambulatory assessment, the reliability and validity of psychophysiological signals from wearable devices is unproven in daily life settings. We evaluated the reliability and validity of physiological signals (electrocardiogram, ECG; photoplethysmography, PPG; electrodermal activity, EDA) collected from two wearable devices (Movisens EcgMove4 and Empatica E4) in the lab (N = 67) and daily life (N = 20) among adults aged 18-64 with Mindware as the laboratory gold standard. Results revealed that both wearable devices' valid data rates in daily life were lower than in the laboratory (Movisens ECG 82.94 vs. 93.10%, Empatica PPG 8.79 vs. 26.14%, and Empatica EDA 41.16 vs. 42.67%, respectively). The poor valid data rates of Empatica PPG signals in the laboratory could be partially attributed to participants' hand movements (r = - .27, p = .03). In laboratory settings, heart rate (HR) derived from both wearable devices exhibited higher concurrent validity than heart rate variability (HRV) metrics (ICCs 0.98-1.00 vs. 0.75-0.97). The number of skin conductance responses (SCRs) derived from Empatica showed higher concurrent validity than skin conductance level (SCL, ICCs 0.38 vs. 0.09). Movisens EcgMove4 provided more reliable and valid HRV measurements than Empatica E4 in both laboratory (split-half reliability: 0.95-0.99 vs. 0.85-0.98; concurrent validity: 0.95-1.00 vs. 0.75-0.98; valid data rate: 93.10 vs. 26.14%) and ambulatory settings (split-half reliability: 0.99-1.00 vs. 0.89-0.98; valid data rate: 82.94 vs. 8.79%). Although the reliability and validity of wearable devices are improving, findings suggest researchers should select devices that yield consistently robust and valid data for their measures of interest.

Feasibility of Wearable Sensors to Assess Cognitive Load During Clinical Performance: Lessons Learned and Blueprint for Success

INTRODUCTION

Cognitive load (CogL) is increasingly recognized as an important resource underlying operative performance. Current innovations in surgery aim to develop objective performance metrics via physiological monitoring from wearable digital sensors. Surgeons have access to consumer technology that could measure CogL but need guidance regarding device selection and implementation. To realize the benefits of surgical performance improvement these methods must be feasible, incorporating human factors usability and design principles. This paper aims to evaluate the feasibility of using wearable sensors to assess CogL, identify the benefits and challenges of implementing devices, and develop guidance for surgeons planning to implement wearable devices in their research or practice.

METHODS

We examined the feasibility of wearable sensors from a series of empirical studies that measured aspects of clinical performance relating to CogL. Across four studies, 84 participants and five sensors were involved in the following clinical settings: (i) real intraoperative surgery; (ii) simulated laparoscopic surgery; and (iii) medical team performance outside the hospital.

RESULTS

Wearable devices worn on the wrist and chest were found to be comfortable. After a learning curve, electrodermal activity data were easily and reliably collected. Devices using photoplethysmography to determine heart rate variability were significantly limited by movement artifact. There was variable success with electroencephalography devices regarding connectivity, comfort, and usability.

CONCLUSIONS

It is feasible to use wearable sensors across various clinical settings, including surgery. There are some limitations, and their implementation is context and device dependent. To scale sensor use in clinical research, surgeons must embrace human factors principles to optimize wearability, usability, reliability, and data security.

A Framework for Selecting and Assessing Wearable Sensors Deployed in Safety Critical Scenarios

Wearable sensors for psychophysiological monitoring are becoming increasingly mainstream in safety critical contexts. They offer a novel solution to capturing sub-optimal states and can help identify when workers in safety critical environments are suffering from states such as fatigue and stress. However, sensors can differ widely in their application, design, usability, and measurement and there is a lack of guidance on what should be prioritized or considered when selecting a sensor. The paper aims to highlight which concepts are important when creating or selecting a device regarding the optimization of both measurement and usability. Additionally, the paper discusses how design choices can enhance both the usability and measurement capabilities of wearable sensors. The hopes are that this paper will provide researchers and practitioners in human factors and related fields with a framework to help guide them in building and selecting wearable sensors that are well suited for deployment in safety critical contexts.

Age-related differences in subjective and physiological emotion evoked by immersion in natural and social virtual environments

Age-related changes in emotional processing are complex, with a bias toward positive information. However, the impact of aging on emotional responses in positive everyday situations remains unclear. Virtual Reality (VR) has emerged as a promising tool for investigating emotional processing, offering a unique balance between ecological validity and experimental control. Yet, limited evidence exists regarding its efficacy to elicit positive emotions in older adults. Our study aimed to explore age-related differences in positive emotional responses to immersion in both social and nonsocial virtual emotional environments. We exposed 34 younger adults and 24 older adults to natural and social 360-degree video content through a low immersive computer screen and a highly immersive Head-Mounted Display, while recording participants' physiological reactions. Participants also provided self-report of their emotions and sense of presence. The findings support VR's efficacy in eliciting positive emotions in both younger and older adults, with age-related differences in emotional responses influenced by the specific video content rather than immersion level. These findings underscore the potential of VR as a valuable tool for examining age-related differences in emotional responses and developing VR applications to enhance emotional wellbeing across diverse user populations.

Social and nonsocial synchrony are interrelated and romantically attractive

The mechanisms of romantic bonding in humans are largely unknown. Recent research suggests that physiological synchrony between partners is associated with bonding. This study combines an experimental approach with a naturalistic dating setup to test whether the individual differences in social and nonsocial synchrony are interdependent, and linked to romantic attractiveness. In a preregistered online experiment with 144 participants, we discover that inducing physiological synchrony between an actor and an actress determines their attractiveness ratings by participants, indicating that synchrony can increase perceived attraction. In a lab-based naturalistic speed-dating experiment, we quantify in 48 participants the individual tendency for social physiological synchrony, nonsocial sensorimotor synchrony, and romantic attractiveness. We discover that the individual propensity to synchronize in social and nonsocial tasks is correlated. Some individuals synchronize better regardless of partners or tasks, and such Super Synchronizers are rated as more attractive. Altogether, this demonstrates that humans prefer romantic partners who can synchronize.

Investigating the association of anxiety disorders with heart rate variability measured using a wearable device

BACKGROUND

Reduced vagally-mediated heart rate variability (HRV) has been associated with anxiety disorders (AD). The aim of this study was to use a wearable device and remote study design to re-evaluate the association of HRV with ADs, anxiety-related traits, and confounders.

METHODS

240 individuals (AD = 120, healthy controls = 120) completed an at-home assessment of their short-term resting vagally-mediated HRV using a wristband, monitored over videoconference. Following quality control, analyses were performed investigating differences in HRV between individuals with AD (n = 119) and healthy controls (n = 116), associations of HRV with anxiety-related traits and confounders, and antidepressants effects on HRV in patients, including analyses stratified by ancestry (i.e., European, East Asian, African).

RESULTS

Among the confounders investigated, only age had a significant association with HRV. Patients with an AD had significantly lower vagally-mediated HRV than healthy controls in the European subsample, with a trend of significance in the whole sample. HRV was significantly associated with the Hamilton Anxiety Rating Scale (HAM-A) but not with antidepressant use in the European subsample.

LIMITATIONS

The study measures occurred in a non-standardized at-home setting, and the three ancestry group sample sizes were unequal.

CONCLUSIONS

This study demonstrates reduced vagally-mediated HRV among patients with ADs compared to healthy controls. Results also point to low HRV being related to more physical anxiety symptoms (measured via HAM-A), suggesting a possible anxiety subtype. Overall, this study highlights the feasibility of using wearables for patients and encourages exploration of the biological and clinical utility of HRV as a risk factor for ADs.

Using machine learning with passive wearable sensors to pilot the detection of eating disorder behaviors in everyday life

BACKGROUND

Eating disorders (ED) are serious psychiatric disorders, taking a life every 52 minutes, with high relapse. There are currently no support or effective intervention therapeutics for individuals with an ED in their everyday life. The aim of this study is to build idiographic machine learning (ML) models to evaluate the performance of physiological recordings to detect individual ED behaviors in naturalistic settings.

METHODS

From an ongoing study (Final N = 120), we piloted the ability for ML to detect an individual's ED behavioral episodes (e.g. purging) from physiological data in six individuals diagnosed with an ED, all of whom endorsed purging. Participants wore an ambulatory monitor for 30 days and tapped a button to denote ED behavioral episodes. We built idiographic (N = 1) logistic regression classifiers (LRC) ML trained models to identify onset of episodes (~600 windows) v. baseline (~571 windows) physiology (Heart Rate, Electrodermal Activity, and Temperature).

RESULTS

Using physiological data, ML LRC accurately classified on average 91% of cases, with 92% specificity and 90% sensitivity.

CONCLUSIONS

This evidence suggests the ability to build idiographic ML models that detect ED behaviors from physiological indices within everyday life with a high level of accuracy. The novel use of ML with wearable sensors to detect physiological patterns of ED behavior pre-onset can lead to just-in-time clinical interventions to disrupt problematic behaviors and promote ED recovery.

A high altitude respiration and SpO2 dataset for assessing the human response to hypoxia

This report presents the Harespod dataset, an open dataset for high altitude hypoxia research, which includes respiration and SpO2 data. The dataset was collected from 15 college students aged 23-31 in a hypobaric oxygen chamber, during simulated altitude changes and induced hypoxia. Real-time physiological data, such as oxygen saturation waveforms, oxygen saturation, respiratory waveforms, heart rate, and pulse rate, were obtained at 100 Hz. Approximately 12 hours of valid data were collected from all participants. Researchers can easily identify the altitude corresponding to physiological signals based on their inherent patterns. Time markers were also recorded during altitude changes to facilitate realistic annotation of physiological signals and analysis of time-difference-of-arrival between various physiological signals for the same altitude change event. In high altitude scenarios, this dataset can be used to enhance the detection of human hypoxia states, predict respiratory waveforms, and develop related hardware devices. It will serve as a valuable and standardized resource for researchers in the field of high altitude hypoxia research, enabling comprehensive analysis and comparison.

Kinesiophobia, limits of stability, and functional balance assessment in geriatric patients with chronic low back pain and osteoporosis: a comprehensive study

Background

The significance of studying Kinesiophobia, Limits of Stability (LOS), and functional balance in geriatric patients with CLBP and osteoporosis lies in their profound impact on rehabilitation outcomes and fall risk, ultimately affecting patients' quality of life. This study aimed to examine LOS and functional balance in the geriatric population concurrently experiencing Chronic Low Back Pain (CLBP) and osteoporosis, in comparison to age-matched healthy controls; to assess the correlations between Kinesiophobia, LOS, and functional balance assessments; and to evaluate the mediating influence of Kinesiophobia on the association between LOS and functional balance tests.

Methods

This cross-sectional study included a total of 86 participants in each group. Kinesiophobia was assessed using the Tampa Scale of Kinesiophobia (TSK). LOS variables were evaluated with a computerized Iso-free platform in eight different directions. Functional balance was measured using the Timed Up and Go (TUG) test and the Berg Balance Scale (BBS).

Results

Patients with CLBP and osteoporosis showed significantly lower LOS percentages (45.78 ± 6.92) and impaired Functional Balance, reflected in a TUG Score (10.45 ± 2.23), compared to asymptomatic controls (LOS: 76.95 ± 8.21; TUG: 8.73 ± 1.90). Kinesiophobia showed a significant moderate negative correlation with LOS, indicated by r = -0.362 (p < 0.01). Additionally, Kinesiophobia was found to correlate with functional balance tests. Specifically, there was a moderate positive correlation with the TUG Score (r = 0.322, p < 0.01), indicating that higher Kinesiophobia is associated with slower TUG performance. Conversely, a stronger moderate negative correlation was observed with the Berg Balance Scale (BBS) Score (r = -0.436, p < 0.001), suggesting that increased Kinesiophobia is associated with lower BBS scores, indicating poorer balance performance. Mediation analysis revealed that Kinesiophobia significantly influences LOS and Functional Balance. For LOS and the TUG score, Kinesiophobia showed a direct effect (B = 0.24), an indirect effect (B = 0.09), and a total effect (B = 0.13). Similarly, for LOS and the BBS score, the direct effect of Kinesiophobia was B = 0.38, with an indirect effect of B = 0.10 and a total effect of B = 0.20.

Conclusion

This study underscores the substantial impact of Kinesiophobia on both stability and functional balance in individuals coping with CLBP and osteoporosis. The findings emphasize the clinical relevance of addressing Kinesiophobia as a potential target for interventions aimed at improving LOS and functional balance in this specific patient population.

Electrodermal activity in bipolar disorder: Differences between mood episodes and clinical remission using a wearable device in a real-world clinical setting

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.

SmartWear body sensors for neurological and neurosurgical patients: A review of current and future technologies

Background/objective

Recent technological advances have allowed for the development of smart wearable devices (SmartWear) which can be used to monitor various aspects of patient healthcare. These devices provide clinicians with continuous biometric data collection for patients in both inpatient and outpatient settings. Although these devices have been widely used in fields such as cardiology and orthopedics, their use in the field of neurosurgery and neurology remains in its infancy.

Methods

A comprehensive literature search for the current and future applications of SmartWear devices in the above conditions was conducted, focusing on outpatient monitoring.

Findings

Through the integration of sensors which measure parameters such as physical activity, hemodynamic variables, and electrical conductivity - these devices have been applied to patient populations such as those at risk for stroke, suffering from epilepsy, with neurodegenerative disease, with spinal cord injury and/or recovering from neurosurgical procedures. Further, these devices are being tested in various clinical trials and there is a demonstrated interest in the development of new technologies.

Conclusion

This review provides an in-depth evaluation of the use of SmartWear in selected neurological diseases and neurosurgical applications. It is clear that these devices have demonstrated efficacy in a variety of neurological and neurosurgical applications, however challenges such as data privacy and management must be addressed.

Undersampling and cumulative class re-decision methods to improve detection of agitation in people with dementia

Agitation is one of the most prevalent symptoms in people with dementia (PwD) that can place themselves and the caregiver's safety at risk. Developing objective agitation detection approaches is important to support health and safety of PwD living in a residential setting. In a previous study, we collected multimodal wearable sensor data from 17 participants for 600 days and developed machine learning models for detecting agitation in 1-min windows. However, there are significant limitations in the dataset, such as imbalance problem and potential imprecise labels as the occurrence of agitation is much rarer in comparison to the normal behaviours. In this paper, we first implemented different undersampling methods to eliminate the imbalance problem, and came to the conclusion that only 20% of normal behaviour data were adequate to train a competitive agitation detection model. Then, we designed a weighted undersampling method to evaluate the manual labeling mechanism given the ambiguous time interval assumption. After that, the postprocessing method of cumulative class re-decision (CCR) was proposed based on the historical sequential information and continuity characteristic of agitation, improving the decision-making performance for the potential application of agitation detection system. The results showed that a combination of undersampling and CCR improved F1-score and other metrics to varying degrees with less training time and data.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13534-023-00313-8.

AI in Rehabilitation Medicine: Opportunities and Challenges

Artificial intelligence (AI) tools are increasingly able to learn from larger and more complex data, thus allowing clinicians and scientists to gain new insights from the information they collect about their patients every day. In rehabilitation medicine, AI can be used to find patterns in huge amounts of healthcare data. These patterns can then be leveraged at the individual level, to design personalized care strategies and interventions to optimize each patient's outcomes. However, building effective AI tools requires many careful considerations about how we collect and handle data, how we train the models, and how we interpret results. In this perspective, we discuss some of the current opportunities and challenges for AI in rehabilitation. We first review recent trends in AI for the screening, diagnosis, treatment, and continuous monitoring of disease or injury, with a special focus on the different types of healthcare data used for these applications. We then examine potential barriers to designing and integrating AI into the clinical workflow, and we propose an end-to-end framework to address these barriers and guide the development of effective AI for rehabilitation. Finally, we present ideas for future work to pave the way for AI implementation in real-world rehabilitation practices.

Predicting Obsessive-Compulsive Disorder Events in Children and Adolescents in the Wild using a Wearable Biosensor (Wrist Angel): Protocol for the Analysis Plan of a Nonrandomized Pilot Study

BACKGROUND

Physiological signals such as heart rate and electrodermal activity can provide insight into an individual's mental state, which are invaluable information for mental health care. Using recordings of physiological signals from wearable devices in the wild can facilitate objective monitoring of symptom severity and evaluation of treatment progress.

OBJECTIVE

We designed a study to evaluate the feasibility of predicting obsessive-compulsive disorder (OCD) events from physiological signals recorded using wrist-worn devices in the wild. Here, we present an analysis plan for the study to document our a priori hypotheses and increase the robustness of the findings of our planned study.

METHODS

In total, 18 children and adolescents aged between 8 and 16 years were included in this study. Nine outpatients with an OCD diagnosis were recruited from a child and adolescent mental health center. Nine youths without a psychiatric diagnosis were recruited from the catchment area. Patients completed a clinical interview to assess OCD severity, types of OCD, and number of OCD symptoms in the clinic. Participants wore a biosensor on their wrist for up to 8 weeks in their everyday lives. Patients were asked to press an event tag button on the biosensor when they were stressed by OCD symptoms. Participants without a psychiatric diagnosis were asked to press this button whenever they felt really scared. Before and after the 8-week observation period, participants wore the biosensor under controlled conditions of rest and stress in the clinic. Features are extracted from 4 different physiological signals within sliding windows to predict the distress event logged by participants during data collection. We will test the prediction models within participants across time and multiple participants. Model selection and estimation using 2-layer cross-validation are outlined for both scenarios.

RESULTS

Participants were included between December 2021 and December 2022. Participants included 10 female and 8 male participants with an even sex distribution between groups. Patients were aged between 10 and 16 years, and adolescents without a psychiatric diagnosis were between the ages of 8 and 16 years. Most patients had moderate to moderate to severe OCD, except for 1 patient with mild OCD.

CONCLUSIONS

The strength of the planned study is the investigation of predictions of OCD events in the wild. Major challenges of the study are the inherent noise of in-the-wild data and the lack of contextual knowledge associated with the recorded signals. This preregistered analysis plan discusses in detail how we plan to address these challenges and may help reduce interpretation bias of the upcoming results. If the obtained results from this study are promising, we will be closer to automated detection of OCD events outside of clinical experiments. This is an important tool for the assessment and treatment of OCD in youth.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05064527; https://clinicaltrials.gov/study/NCT05064527.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/48571.

The Effects of Noise and Simulated Conductive Hearing Loss on Physiological Response Measures During Interactive Conversations

PURPOSE

The purpose of this work was to study the effects of background noise and hearing attenuation associated with earplugs on three physiological measures, assumed to be markers of effort investment and arousal, during interactive communication.

METHOD

Twelve pairs of older people (average age of 63.2 years) with age-adjusted normal hearing took part in a face-to-face communication to solve a Diapix task. Communication was held in different levels of babble noise (0, 60, and 70 dBA) and with two levels of hearing attenuation (0 and 25 dB) in quiet. The physiological measures obtained included pupil size, heart rate variability, and skin conductance. In addition, subjective ratings of perceived communication success, frustration, and effort were obtained.

RESULTS

Ratings of perceived success, frustration, and effort confirmed that communication was more difficult in noise and with approximately 25-dB hearing attenuation and suggested that the implemented levels of noise and hearing attenuation resulted in comparable communication difficulties. Background noise at 70 dBA and hearing attenuation both led to an initial increase in pupil size (associated with effort), but only the effect of the background noise was sustained throughout the conversation. The 25-dB hearing attenuation led to a significant decrease of the high-frequency power of heart rate variability and a significant increase of skin conductance level, measured as the average z value of the electrodermal activity amplitude.

CONCLUSION

This study demonstrated that several physiological measures appear to be viable indicators of changing communication conditions, with pupillometry and cardiovascular as well as electrodermal measures potentially being markers of communication difficulty.

PhysioKit: An Open-Source, Low-Cost Physiological Computing Toolkit for Single- and Multi-User Studies

The proliferation of physiological sensors opens new opportunities to explore interactions, conduct experiments and evaluate the user experience with continuous monitoring of bodily functions. Commercial devices, however, can be costly or limit access to raw waveform data, while low-cost sensors are efforts-intensive to setup. To address these challenges, we introduce PhysioKit, an open-source, low-cost physiological computing toolkit. PhysioKit provides a one-stop pipeline consisting of (i) a sensing and data acquisition layer that can be configured in a modular manner per research needs, and (ii) a software application layer that enables data acquisition, real-time visualization and machine learning (ML)-enabled signal quality assessment. This also supports basic visual biofeedback configurations and synchronized acquisition for co-located or remote multi-user settings. In a validation study with 16 participants, PhysioKit shows strong agreement with research-grade sensors on measuring heart rate and heart rate variability metrics data. Furthermore, we report usability survey results from 10 small-project teams (44 individual members in total) who used PhysioKit for 4-6 weeks, providing insights into its use cases and research benefits. Lastly, we discuss the extensibility and potential impact of the toolkit on the research community.

Using Wearable Passive Sensing to Predict Binge Eating in Response to Negative Affect Among Individuals With Transdiagnostic Binge Eating: Protocol for an Observational Study

BACKGROUND

Binge eating (BE), characterized by eating a large amount of food accompanied by a sense of loss of control over eating, is a public health crisis. Negative affect is a well-established antecedent for BE. The affect regulation model of BE posits that elevated negative affect increases momentary risk for BE, as engaging in BE alleviates negative affect and reinforces the behavior. The eating disorder field's capacity to identify moments of elevated negative affect, and thus BE risk, has exclusively relied on ecological momentary assessment (EMA). EMA involves the completion of surveys in real time on one's smartphone to report behavioral, cognitive, and emotional symptoms throughout the day. Although EMA provides ecologically valid information, EMA surveys are often delivered only 5-6 times per day, involve self-report of affect intensity only, and are unable to assess affect-related physiological arousal. Wearable, psychophysiological sensors that measure markers of affect arousal including heart rate, heart rate variability, and electrodermal activity may augment EMA surveys to improve accurate real-time prediction of BE. These sensors can objectively and continuously measure biomarkers of nervous system arousal that coincide with affect, thus allowing them to measure affective trajectories on a continuous timescale, detect changes in negative affect before the individual is consciously aware of them, and reduce user burden to improve data completeness. However, it is unknown whether sensor features can distinguish between positive and negative affect states, given that physiological arousal may occur during both negative and positive affect states.

OBJECTIVE

The aims of this study are (1) to test the hypothesis that sensor features will distinguish positive and negative affect states in individuals with BE with >60% accuracy and (2) test the hypothesis that a machine learning algorithm using sensor data and EMA-reported negative affect to predict the occurrence of BE will predict BE with greater accuracy than an algorithm using EMA-reported negative affect alone.

METHODS

This study will recruit 30 individuals with BE who will wear Fitbit Sense 2 wristbands to passively measure heart rate and electrodermal activity and report affect and BE on EMA surveys for 4 weeks. Machine learning algorithms will be developed using sensor data to distinguish instances of high positive and high negative affect (aim 1) and to predict engagement in BE (aim 2).

RESULTS

This project will be funded from November 2022 to October 2024. Recruitment efforts will be conducted from January 2023 through March 2024. Data collection is anticipated to be completed in May 2024.

CONCLUSIONS

This study is anticipated to provide new insight into the relationship between negative affect and BE by integrating wearable sensor data to measure affective arousal. The findings from this study may set the stage for future development of more effective digital ecological momentary interventions for BE.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/47098.

On the Reliability of Wearable Technology: A Tutorial on Measuring Heart Rate and Heart Rate Variability in the Wild

Wearable sensors are quickly making their way into psychophysiological research, as they allow collecting data outside of a laboratory and for an extended period of time. The present tutorial considers fidelity of physiological measurement with wearable sensors, focusing on reliability. We elaborate on why ensuring reliability for wearables is important and offer statistical tools for assessing wearable reliability for between participants and within-participant designs. The framework offered here is illustrated using several brands of commercially available heart rate sensors. Measurement reliability varied across sensors and, more importantly, across the situations tested, and was highest during sleep. Our hope is that by systematically quantifying measurement reliability, researchers will be able to make informed choices about specific wearable devices and measurement procedures that meet their research goals.

Generalizable machine learning for stress monitoring from wearable devices: A systematic literature review

INTRODUCTION

Wearable sensors have shown promise as a non-intrusive method for collecting biomarkers that may correlate with levels of elevated stress. Stressors cause a variety of biological responses, and these physiological reactions can be measured using biomarkers including Heart Rate Variability (HRV), Electrodermal Activity (EDA) and Heart Rate (HR) that represent the stress response from the Hypothalamic-Pituitary-Adrenal (HPA) axis, the Autonomic Nervous System (ANS), and the immune system. While Cortisol response magnitude remains the gold standard indicator for stress assessment [1], recent advances in wearable technologies have resulted in the availability of a number of consumer devices capable of recording HRV, EDA and HR sensor biomarkers, amongst other signals. At the same time, researchers have been applying machine learning techniques to the recorded biomarkers in order to build models that may be able to predict elevated levels of stress.

OBJECTIVE

The aim of this review is to provide an overview of machine learning techniques utilized in prior research with a specific focus on model generalization when using these public datasets as training data. We also shed light on the challenges and opportunities that machine learning-enabled stress monitoring and detection face.

METHODS

This study reviewed published works contributing and/or using public datasets designed for detecting stress and their associated machine learning methods. The electronic databases of Google Scholar, Crossref, DOAJ and PubMed were searched for relevant articles and a total of 33 articles were identified and included in the final analysis. The reviewed works were synthesized into three categories of publicly available stress datasets, machine learning techniques applied using those, and future research directions. For the machine learning studies reviewed, we provide an analysis of their approach to results validation and model generalization. The quality assessment of the included studies was conducted in accordance with the IJMEDI checklist [2].

RESULTS

A number of public datasets were identified that are labeled for stress detection. These datasets were most commonly produced from sensor biomarker data recorded using the Empatica E4 device, a well-studied, medical-grade wrist-worn wearable that provides sensor biomarkers most notable to correlate with elevated levels of stress. Most of the reviewed datasets contain less than twenty-four hours of data, and the varied experimental conditions and labeling methodologies potentially limit their ability to generalize for unseen data. In addition, we discuss that previous works show shortcomings in areas such as their labeling protocols, lack of statistical power, validity of stress biomarkers, and model generalization ability.

CONCLUSION

Health tracking and monitoring using wearable devices is growing in popularity, while the generalization of existing machine learning models still requires further study, and research in this area will continue to provide improvements as newer and more substantial datasets become available.

Impairments in Physiological Reactivity to Emotive Stimuli After Traumatic Brain Injury: A Systematic Review of Skin Conductance and Heart Rate Variability Evidence

OBJECTIVE

To examine evidence of impairments in physiological reactivity to emotive stimuli following traumatic brain injury (TBI).

METHODS

A search of PsychINFO, CINAHL (Cumulative Index to Allied Health Literature), Web of Science, EMBASE (Excerpta Medica dataBASE), and Scopus databases was conducted from 1991 to June 24, 2021, for studies comparing changes in skin conductance or heart rate variability to emotive stimuli between adults with TBI and controls. Two reviewers independently assessed eligibility and rated methodological quality.

RESULTS

Twelve eligible studies examined physiological reactivity to laboratory-based emotive stimuli, which included nonpersonal pictures/videos, posed emotion, stressful events, and personal event recall. Overall, 9 reported evidence that individuals with TBI experience lower physiological reactivity to emotive stimuli compared with healthy controls, although the findings varied according to the type and valence of emotional stimuli and physiological parameter. Most studies using nonpersonal pictures or videos found evidence of lower physiological reactivity in TBI participants compared with controls.

CONCLUSIONS

Based on laboratory-based studies, individuals with TBI may experience lower physiological reactivity to emotive stimuli. Further research is needed to investigate physiological responses to personally relevant emotional stimuli in real-world settings and to understand the interplay between physiological reactivity, subjective experiences, and behavior.

Home-Based Measurements of Nocturnal Cardiac Parasympathetic Activity in Athletes during Return to Sport after Sport-Related Concussion

Sport-related concussions (SRC) are characterized by impaired autonomic control. Heart rate variability (HRV) offers easily obtainable diagnostic approaches to SRC-associated dysautonomia, but studies investigating HRV during sleep, a crucial time for post-traumatic cerebral regeneration, are relatively sparse. The aim of this study was to assess nocturnal HRV in athletes during their return to sports (RTS) after SRC in their home environment using wireless wrist sensors (E4, Empatica, Milan, Italy) and to explore possible relations with clinical concussion-associated sleep symptoms. Eighteen SRC athletes wore a wrist sensor obtaining photoplethysmographic data at night during RTS as well as one night after full clinical recovery post RTS (>3 weeks). Nocturnal heart rate and parasympathetic activity of HRV (RMSSD) were calculated and compared using the Mann-Whitney U Test to values of eighteen; matched by sex, age, sport, and expertise, control athletes underwent the identical protocol. During RTS, nocturnal RMSSD of SRC athletes (Mdn = 77.74 ms) showed a trend compared to controls (Mdn = 95.68 ms, p = 0.021, r = -0.382, p adjusted using false discovery rate = 0.126) and positively correlated to "drowsiness" (r = 0.523, p = 0.023, p adjusted = 0.046). Post RTS, no differences in RMSSD between groups were detected. The presented findings in nocturnal cardiac parasympathetic activity during nights of RTS in SRC athletes might be a result of concussion, although its relation to recovery still needs to be elucidated. Utilization of wireless sensors and wearable technologies in home-based settings offer a possibility to obtain helpful objective data in the management of SRC.

Exploring the effects of a wearable biocueing app (Sense-IT) as an addition to aggression regulation therapy in forensic psychiatric outpatients

Objective

Preventing and reducing violence is of high importance for both individuals and society. However, the overall efficacy of current treatment interventions aimed at reducing aggressive behavior is limited. New technological-based interventions may enhance treatment outcomes, for instance by facilitating out-of-session practice and providing just-in-time support. Therefore, the aim of this study was to assess the effects of the Sense-IT biocueing app as an addition to aggression regulation therapy (ART) on interoceptive awareness, emotion regulation, and aggressive behavior among forensic outpatients.

Methods

A combination of methods was used. Quantitatively, a pretest-posttest design was applied to explore group changes in aggression, emotion regulation, and anger bodily sensations associated with the combination of biocueing intervention and ART. Measures were assessed at pretest, after 4 weeks posttest, and after one-month follow-up. During the 4 weeks, a single-case experimental ABA design was applied for each participant. Biocueing was added in the intervention phase. During all phases anger, aggressive thoughts, aggressive behavior, behavioral control, and physical tension were assessed twice a day, and heart rate was measured continuously. Qualitative information regarding interoceptive awareness, coping, and aggression was collected at posttest. 25 forensic outpatients participated.

Results

A significant decrease in self-reported aggression was found between pre- and posttest. Furthermore, three-quarters of participants reported increased interoceptive awareness associated with the biocueing intervention. However, the repeated ambulatory measurements of the single-case experimental designs (SCEDs) did not indicate a clear effect favoring the addition of biocueing. On group level, no significant effects were found. On the individual level, effects favoring the intervention were only found for two participants. Overall, effect sizes were small.

Conclusion

Biocueing seems a helpful addition to increase interoceptive awareness among forensic outpatients. However, not all patients benefit from the current intervention and, more specifically, from its behavioral support component aimed at enhancing emotion regulation. Future studies should therefore focus on increasing usability, tailoring the intervention to individual needs, and on integration into therapy. Individual characteristics associated with effective support by a biocueing intervention should be further investigated, as the use of personalized and technological-based treatment interventions is expected to increase in the coming years.

An ecological approach to clinically assess nightmares in military service members with severe PTSD

BACKGROUND

Trauma-related nightmares (TRNs) are distressing events which contribute to insomnia severity, chronicity and treatment resistance of PTSD. Therefore, recording TRNs is a crucial technical challenge in order to understand their physiopathological patterns and their impact on sleep. However, TRNs are difficult to record during a single night in a sleep laboratory, which, moreover, is likely to be considered by patients as a protective sleep environment that is therefore not representative of home sleep conditions.

METHOD

In the present study, we investigate if objective sleep measures acquired at-home using two ambulatory devices is of clinical value by correlating with PTSD patients' complaints about sleep and nightmares. A secondary objective is to relate awakenings associated with TRNs to sleep stages and to provide new insights into the use of electrodermal activity (EDA) as a potential physiological marker of TRNs. Sixty veterans and active-duty service members were assessed by questionnaires and recorded for 5 consecutive nights in their homes.

RESULTS

Our approach firstly identified positive correlations between subjective and objective sleep parameters (total sleep time, sleep-onset latency and TRNs frequency). We also developed a method of synchronization between the two ambulatory devices that allowed us to match 200 TRNs (reported by event marker push button) with sleep stages corresponding to 91 nights and 37 patients. Most awakenings associated with TRNs occurred during NREM sleep (65.5% versus 34.5% during REM sleep). Our results also reveal significant differences in the frequency of EDA peaks 10 min before the reported events, with a lower frequency in REM (13.7 peaks) than in NREM (24.8 peaks) awakenings associated with TRNs. This EDA peaks frequency in REM sleep is not statistically different from that in REM sleep preceding awakenings that are not associated with TRNs.

CONCLUSION

The development of wearable devices to collect physiological parameters is of interest in clinical practice to improve our knowledge of sleep and trauma-related nightmares in patients with PTSD.

How aging couples' emotional and physiological associations change across positive, supportive, and conflictual discussions: Roles of capitalization and responsive behaviors

BACKGROUND

Couples' emotions and physiology change across interactions and based on behaviors. Aging couples' emotions and physiology may be closely related as they spend more time together and rely on each other for support. We examined aging couples' emotional and physiological associations across multiple indices and marital interactions; we also assessed how couples' capitalization and responsive behaviors during the first discussion were protective in subsequent emotional conversations.

METHODS

Married couples (n = 107 couples, 214 individuals) engaged in positive event, social support, and conflict discussions. Emotional and physiological assessments across discussions included: positive and negative emotion, electrodermal activity, systolic and diastolic blood pressure, heart rate, and heart rate variability. We coded partners' capitalization and responsive behaviors during the first discussion.

RESULTS

There were ties in spouses' positive emotion, negative emotion, electrodermal activity, systolic blood pressure, heart rate, and heart rate variability during positive, supportive, and conflictual discussions. Emotional and physiological associations reflecting shared stress (negative emotion, electrodermal activity, systolic blood pressure) were stronger in couples who were less capitalizing or responsive earlier that day; associations reflecting physiological adaptation (heart rate variability) were stronger for more capitalizing and responsive couples.

CONCLUSION

Aging couples' emotions and physiology tracked together during discussions central to maintaining relationships, and their past behaviors carried over into future interactions and across contexts. Enthusiastic, caring, and understanding behaviors may protect partners from shared emotional and physiological stress; lacking such behaviors may increase emotional and physiological vulnerability. This research identifies behavioral, emotional, and physiological pathways connecting relationships to health in adulthood.

An ideographic study into physiology, alcohol craving and lapses during one hundred days of daily life monitoring

Introduction

Alcohol craving is a highly challenging obstacle to achieve long-term abstinence. Making alcohol use disorder patients timely aware of high-risk craving situations may protect them against relapse by prompting them to mobilize their coping resources. Current advances in wearable and smart-phone technology provide novel opportunities for the development of detecting these situations of heightened risk of craving, by enabling continuous tracking of fluctuations in psychological and physiological parameters. The present study therefore aims to determine the association between self-reported craving and relapses, and between heightened physiological activity. Specifically, we measured cardiovascular and electrodermal activity, and self-reported craving during one hundred days in the daily life of people trying to recover from alcoholism. The secondary aim is to study whether the association between physiology and craving can be strengthened by the inclusion of context related psychological parameters.

Methods

An intensive repeated and continuous measures in naturalistic settings case-study design was employed. Ten participants were monitored with wearable bio-sensors and answered multiple questions every three hours on a smartphone app about craving, lapsing and multiple evidence based contextual variables. The association between physiology, craving and lapses was explored using Matthews correlation coefficients both with a current and 3 h lagged design. The contextual variables were included in a decision tree together with the physiological parameters to explore the added effect on the correlation of these contextual variables.

Results

The association between lapses and craving was highly different across individuals, varying between a weak to a strong association. The association between cardiovascular activity and heightened self-reported craving was negligible to weak, however with a high specificity, meaning that most craving events were accompanied by increase heart rate. However, the association between electrodermal activity and craving was lower than with cardiovascular activity for most participants, both prior (lagged) and during craving. For two of the participants the association between physiology and craving improved by adding contextual variables, however, precision was too low.

Conclusions

People differ strongly in their bodily reactions and psychological experiences during the first months of their addiction treatment. No individual in our study had unique one-to-one mappings between on the one hand physiological or psychological precursors, and on the other hand craving and (re)lapses. Therefore, detecting high risk craving situations with both physiological activity measured with wearables and psychological precursors to alert people specifically for an imminent (re)lapse, does not seem viable on the basis of the current results. We do see an added benefit of using physiology during treatment, as physiology can help start the conversation about possible high risk craving situations during that week. This would also help the counselor to gain added insights into the fluctuating states of the clients, and help to ameliorate the recall bias of clients. The present study showed the possibility and paved the way for future intensive longitudinal designs integrating both physiological, psychological and contextual factors during the challenging and lengthy recovery from addiction.

Investigating the effect of synchronized movement on toddlers' word learning

The effect of interpersonal behavioral synchrony on children's behavior is an emerging field rich with research potential. While studies demonstrate its effect on affiliative and prosocial outcomes, the role of synchronized movement on children's specific learning outcomes has not yet been investigated experimentally. One possibility is that synchrony, as a coordinated social activity, encourages perceived social bonds, leading to heightened attention, and better information retention. Equally likely is that physiological, rather than social learning, mechanisms mediate the effect, given the previously demonstrated role of autonomic arousal in attentional fluctuations, cognitive engagement, problem solving, exploration, and curiosity. The present study investigated the behavioral and physiological effects of synchrony conceptualized as induced, interpersonal, behavioral, movement-based interaction, on word learning in 2.5-year-old children. In a laboratory experiment, toddlers engaged in either a synchronous or an asynchronous movement-based interaction with an adult experimenter while listening to an upbeat children's song. After the (a)synchronous movement episode, the same experimenter engaged children in a word learning task. During the (a)synchrony and learning phases, children's physiological arousal was continuously recorded, resulting in heart rate and skin conductance response measures. Following a caregiver-child free play break, children were tested on their novel word retention. The results indicated that children learned novel labels at equal rates during the learning phase in both conditions, and their retention at test did not differ between conditions: although above chance retention of novel labels was found only following the synchronous, but not the asynchronous episode, the cross-episode comparisons did not reach statistical significance. Physiological arousal indices following the (a)synchrony episode did not differ between conditions and did not predict better word learning, although skin conductance response was higher during the learning than the movement episode. This study contributes to our understanding of the underlying cognitive and physiological mechanisms of interpersonal behavioral synchrony in the knowledge acquisition domain and paves the way to future investigations.

3D Printing Technology for Smart Clothing: A Topic Review

Clothing is considered to be an important element of human social activities. With the increasing maturity of 3D printing technology, functional 3D printing technology can realize the perfect combination of clothing and electronic devices while helping smart clothing to achieve specific functions. Furthermore, the application of functional 3D printing technology in clothing not only provides people with the most comfortable and convenient wearing experience, but also completely subverts consumers' perception of traditional clothing. This paper introduced the progress of the application of 3D printing from the aspect of traditional clothing and smart clothing through two mature 3D printing technologies normally used in the field of clothing, and summarized the challenges and prospects of 3D printing technology in the field of smart clothing. Finally, according to the analysis of the gap between 3D-printed clothing and traditionally made clothing due to the material limitations, this paper predicted that the rise in intelligent materials will provide a new prospect for the development of 3D-printed clothing. This paper will provide some references for the application research of 3D printing in the field of smart clothing.

Sensor Technology and Intelligent Systems in Anorexia Nervosa: Providing Smarter Healthcare Delivery Systems

Ubiquitous technology, big data, more efficient electronic health records, and predictive analytics are now at the core of smart healthcare systems supported by artificial intelligence. In the present narrative review, we focus on sensing technologies for the healthcare of Anorexia Nervosa (AN). We employed a framework inspired by the Interpersonal Neurobiology Theory (IPNB), which posits that human experience is characterized by a flow of energy and information both within us (within our whole body), and between us (in the connections we have with others and with nature). In line with this framework, we focused on sensors designed to evaluate bodily processes (body sensors such as implantable sensors, epidermal sensors, and wearable and portable sensors), human social interaction (sociometric sensors), and the physical environment (indoor and outdoor ambient sensors). There is a myriad of man-made sensors as well as nature-based sensors such as plants that can be used to design and deploy intelligent systems for human monitoring and healthcare. In conclusion, sensing technologies and intelligent systems can be employed for smarter healthcare of AN and help to relieve the burden of health professionals. However, there are technical, ethical, and environmental sustainability issues that must be considered prior to implementing these systems. A joint collaboration of professionals and other members of the society involved in the healthcare of individuals with AN can help in the development of these systems. The evolution of cyberphysical systems should also be considered in these collaborations.

Wearables: An R Package With Accompanying Shiny Application for Signal Analysis of a Wearable Device Targeted at Clinicians and Researchers

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.

Design and Implementation of an Emergency Undocking Curriculum for Robotic Surgery

INTRODUCTION

Current training for robotic surgery crisis management, specifically emergency robotic undocking protocol (ERUP), remains limited to anecdotal experience. A curriculum to impart the skills and knowledge necessary to recognize and complete a successful ERUP was developed using an education approach then evaluated.

METHODS

Baseline knowledge and confidence regarding ERUP were established for 5 robotic teams before completing 2 full-immersion simulations separated by an online self-paced learning module. In each simulation, teams operated on a perfused hydrogel model and were tasked to dissect a retroperitoneal tumor abutting a major vessel. During vascular pedicle ligation, a major vascular bleed and nonrecoverable robotic fault were remotely induced, necessitating ERUP with open conversion. After the simulation, participants completed surgery task load index (cognitive load assessment) and realism surveys. Weighted checklists scored participants' actions during each simulation. Surgical metrics including estimated blood loss, time to control bleeding, and undocking time were recorded. Curriculum retention was assessed by repeating the exercise at 6 months.

RESULTS

Participants experienced high levels of cognitive demand and agreed that the simulation's realism and stress mimicked live surgery. Longitudinal analysis showed significant knowledge (+37.5 points, p = 0.004) and confidence (+15.3 points, p < 0.001) improvements from baseline to completion. Between simulations, checklist errors, undocking time, and estimated blood loss decreased (38⇾17, -40 seconds, and -500 mL, respectively), whereas action scores increased significantly (+27 points, p = 0.008). At 6 months, insignificant changes from curriculum completion were seen in knowledge (-4.8 points, p = 0.36) and confidence (+3.7 points, p = 0.1).

CONCLUSIONS

This simulation-based curriculum successfully improves operative team's confidence, knowledge, and skills required to manage robotic crisis events.

Bio-behavioral synchrony is a potential mechanism for mate selection in humans

The decision with whom to form a romantic bond is of great importance, yet the biological or behavioral mechanisms underlying this selective process in humans are largely unknown. Classic evolutionary theories of mate selection emphasize immediate and static features such as physical appearance and fertility. However, they do not explain how initial attraction temporally unfolds during an interaction, nor account for mutual physiological or behavioral adaptations that take place when two people become attracted. Instead, recent theories on social bonding emphasize the importance of co-regulation during social interactions (i.e., the social coordination of physiology and behavior between partners), and predict that co-regulation plays a role in bonding with others. In a speed-date experiment of forty-six heterosexual dates, we recorded the naturally occurring patterns of electrodermal activity and behavioral motion in men and women, and calculated their co-regulation during the date. We demonstrate that co-regulation of behavior and physiology is associated with the date outcome: when a man and a woman synchronize their electrodermal activity and dynamically tune their behavior to one another, they are more likely to be romantically and sexually attracted to one another. This study supports the hypothesis that co-regulation of sympathetic and behavioral rhythms between a man and a woman serves as a mechanism that promotes attraction.

Quantifying Occupational Stress in Intensive Care Unit Nurses: An Applied Naturalistic Study of Correlations Among Stress, Heart Rate, Electrodermal Activity, and Skin Temperature

OBJECTIVE

To identify physiological correlates to stress in intensive care unit nurses.

BACKGROUND

Most research on stress correlates are done in laboratory environments; naturalistic investigation of stress remains a general gap.

METHOD

Electrodermal activity, heart rate, and skin temperatures were recorded continuously for 12-hr nursing shifts (23 participants) using a wrist-worn wearable technology (Empatica E4).

RESULTS

Positive correlations included stress and heart rate (ρ = .35, p < .001), stress and skin temperature (ρ = .49, p < .05), and heart rate and skin temperatures (ρ = .54, p = .0008).

DISCUSSION

The presence and direction of some correlations found in this study differ from those anticipated from prior literature, illustrating the importance of complementing laboratory research with naturalistic studies. Further work is warranted to recognize nursing activities associated with a high level of stress and the underlying reasons associated with changes in physiological responses.

APPLICATION

Heart rate and skin temperature may be used for real-time detection of stress, but more work is needed to validate such surrogate measures.

Exploring physiologic reactions to persuasive information

Persuasion aims at changing peoples’ motivations and/or behaviors. This study explores how and when physiology reflects persuasion processes and specifically whether individual differences in motivations and behaviors affect psychophysiologic reactions to persuasive information. Participants (N = 70) with medium or high meat consumption patterns watched a persuasive video advocating limited meat consumption, while their electrodermal and cardiovascular physiology was measured. Results indicated that the video increased participants’ moral beliefs, perceived behavioral control, and reduction intentions. This study also found an increase in physiologic arousal during the persuasive video and that people with motivations less aligned to the persuasion objective had more physiologic arousal. The findings encourage further psychophysiologic persuasion research, especially as these insights can potentially be used to personalize persuasive messages of behavior change applications.

Persuasion consists of a diversity of mental processes that despite the efforts of many scholars are not fully understood. This explorative manuscript describes an important next step in using peripheral physiology to get information about persuasion‐related processes. It describes how and when people’s physiologic activity changes due to persuasion and what these changes might mean for the personalization of Persuasive Technologies.

Accuracy of Heart Rate Measurement by the Fitbit Charge 2 During Wheelchair Activities in People With Spinal Cord Injury: Instrument Validation Study

Background

Heart rate (HR) is an important and commonly measured physiological parameter in wearables. HR is often measured at the wrist with the photoplethysmography (PPG) technique, which determines HR based on blood volume changes, and is therefore influenced by blood pressure. In individuals with spinal cord injury (SCI), blood pressure control is often altered and could therefore influence HR accuracy measured by the PPG technique.

Objective

The objective of this study is to investigate the HR accuracy measured with the PPG technique with a Fitbit Charge 2 (Fitbit Inc) in wheelchair users with SCI, how the activity intensity affects the HR accuracy, and whether this HR accuracy is affected by lesion level.

Methods

The HR of participants with (38/48, 79%) and without (10/48, 21%) SCI was measured during 11 wheelchair activities and a 30-minute strength exercise block. In addition, a 5-minute seated rest period was measured in people with SCI. HR was measured with a Fitbit Charge 2, which was compared with the HR measured by a Polar H7 HR monitor used as a reference device. Participants were grouped into 4 groups—the no SCI group and based on lesion level into the <T5 (midthoracic and lower) group, T5-T1 (high-thoracic) group, and >T1 (cervical) group. Mean absolute percentage error (MAPE) and concordance correlation coefficient were determined for each group for each activity type, that is, rest, wheelchair activities, and strength exercise.

Results

With an overall MAPE_{all lesions} of 12.99%, the accuracy fell below the standard acceptable MAPE of –10% to +10% with a moderate agreement (concordance correlation coefficient=0.577). The HR accuracy of Fitbit Charge 2 seems to be reduced in those with cervical lesion level in all activities (MAPE_{no SCI}=8.09%; MAPE_<T5=11.16%; MAPE_T1−T5=10.5%; and MAPE_>T1=20.43%). The accuracy of the Fitbit Charge 2 decreased with increasing intensity in all lesions (MAPE_rest=6.5%, MAPE_activity=12.97%, and MAPE_strength=14.2%).

Conclusions

HR measured with the PPG technique showed lower accuracy in people with SCI than in those without SCI. The accuracy was just above the acceptable level in people with paraplegia, whereas in people with tetraplegia, a worse accuracy was found. The accuracy seemed to worsen with increasing intensities. Therefore, high-intensity HR data, especially in people with cervical lesions, should be used with caution.

Cardiovascular reactivity as a measure of irritability in a transdiagnostic sample of youth: Preliminary associations

OBJECTIVES

Irritability is a transdiagnostic symptom in developmental psychopathology, conceptualized as a low threshold for frustration and increased proneness to anger. While central to emotion regulation, there is a vital need for empirical studies to explore the relationship between irritability and underlying physiological mechanisms of cardiovascular arousal.

METHODS

We examined the relationship between irritability and cardiovascular arousal (i.e., heart rate [HR] and heart rate variability [HRV]) in a transdiagnostic sample of 51 youth (M = 12.63 years, SD = 2.25; 62.7% male). Data was collected using the Empatica E4 during a laboratory stop-signal task. In addition, the impact of motion activity, age, medication, and sleep on cardiovascular responses was explored.

RESULTS

Main findings showed that irritability was associated with increased HR and decreased HRV during task performance.

CONCLUSIONS

Findings support the role of peripheral physiological dysregulation in youth with emotion regulation problems and suggest the potential use of available wearable consumer electronics as an objective measure of irritability and physiological arousal in a transdiagnostic sample of youth.

Emotional Responses to the Visual Patterns of Urban Streets: Evidence from Physiological and Subjective Indicators

Despite recent progress in the research of people's emotional response to the environment, the built-rather than natural-environment's emotional effects have not yet been thoroughly examined. In response to this knowledge gap, we recruited 26 participants and scrutinized their emotional response to various urban street scenes through an immersive exposure experiment using virtual reality. We utilized new physiological monitoring technologies that enable synchronized observation of the participants' electroencephalography, electrodermal activity, and heart rate, as well as their subjective indicators. With the newly introduced measurement for the global visual patterns of the built environment, we built statistical models to examine people's emotional response to the physical element configuration and color composition of street scenes. We found that more diverse and less fragmented scenes inspired positive emotional feelings. We also found (in)consistency among the physiological and subjective indicators, indicating a potentially interesting neural-physiological interpretation for the classic form-function dichotomy in architecture. Besides the practical implications on promoting physical environment design, this study combined objective physiology-monitoring technology and questionnaire-based research techniques to demonstrate a better approach to quantify environment-emotion relationships.

Insomnia in Emotional Labor: Its Role in Autonomic Nervous System Regulation

OBJECTIVE

The relation between female emotional laborers' sleep quality and autonomic nervous system activity was investigated.

METHODS

Thirty-three subjects' heart rate variability (HRV) data and results of self-reported scale on sleep, depression, anxiety and suicidality, were collected. Subjects were classified into good sleeper (GS) and poor sleeper (PS) groups relying on sleep quality. Changes of HRV between working time and resting time in each group were compared.

RESULTS

The PS group showed significantly lower difference in root mean square of successive differences (RMSSD), percentage of successive normal-to-normal intervals that differ by more than 50 ms (pNN50), and natural logarithm high-frequency (LnHF) when they were working as compared to when they were resting, which means decreased function of the parasympathetic nervous system (PNS). Repeated measures analysis of covariance showed that the group effect was significant only for LnHF, with score of depression scale as a covariate.

CONCLUSION

Female emotional laborers who complain of sleep difficulty may have decreased function of the PNS. Therefore, good sleep quality is essential for maintaining and promoting mental and physical health of women engage in emotional labor.

W. M. J, Alvarez-Jimenez M, Nieman DH. ENgage YOung people earlY (ENYOY): a mixed-method study design for a digital transdiagnostic clinical - and peer- moderated treatment platform for youth with beginning mental health complaints in the Netherlands

BACKGROUND

The onset of mental disorders typically occurs between the ages of 12 and 25, and the burden of mental health problems is the most consequential for this group. Indicated prevention interventions to target individuals with subclinical symptoms to prevent the transition to clinical levels of disorders, even leading to suicide, have shown to be effective. However, the threshold to seek help appears to be high. Digital interventions could offer a solution, especially during the Covid-19 pandemic. This implementation study will investigate the digital indicated prevention intervention ENgage YOung people Early (ENYOY), the Dutch version of the original Moderated Online Social Therapy Platform (MOST+) from Australia. In addition, the relationship between stress biomarkers, symptoms and outcome measures of youth using the platform will be investigated in this study.

METHODS

The MOST+ platform will be adapted, translated and developed for the situation in the Netherlands in collaboration with a Youth Panel. A prospective cohort of 125 young people (16-25 years) with beginning mental health complaints will be on the platform and followed for a year, of which 10 participants will have an additional smart watch and 10 participants will be asked to provide feedback about the platform. Data will be collected at baseline and after 3, 6 and 12 months. Outcome measures are Psychological Distress assessed with the Kessler Psychological Distress Scale (K10), Social and occupational functioning (measures by the SOFAS), positive mental health indicators measured by the Positive Health Instrument, stress biomarkers with a smart-watch, website journeys of visitors, and feedback of youth about the platform. It will be a mixed-method study design, containing qualitative and quantitative measures.

DISCUSSION

This trial will specifically address young people with emerging mental health complaints, and offers a new approach for treatment in the Netherlands. Considering the waiting lists in (child and adolescent)-psychiatry and the increase in suicides among youth, early low-threshold and non-stigmatizing help to support young people with emerging psychiatric symptoms is of crucial importance. Moreover, this project aims to bridge the gap between child and adolescent and adult psychiatry.

TRIAL REGISTRATION

Netherlands Trial Register ID NL8966 , retrospectively registered on the 19th of October 2020.

Physiological Measurements of Stress Preceding Incidents of Challenging Behavior in People With Severe to Profound Intellectual Disabilities: Longitudinal Study Protocol of Single-Case Studies

Background

Clients with severe to profound intellectual disabilities (SPID) and challenging behavior (CB) and the professional caregivers that support them are vulnerable to high stress levels, which negatively impact their well-being and the quality of care. CB is thought to result from an increase in the intensity and frequency of clients’ stress experiences. In turn, staff members experience stress in dealing with this behavior, and stressed staff members might behave in ways that increase clients’ stress levels, contributing to the origin and maintenance of CB. Research into these dyadic interactions between clients and staff is scarce for people with SPID, especially in real-life situations. The barriers of studying stress in this population include clients’ difficulties in communicating stress experiences and the lack of an objective continuous measure of stress.

Objective

This paper presents a protocol for studying patterns of physiological stress in 15 client-caregiver dyads in the 30 minutes preceding incidents of CB compared to control periods without CB and the interplay between the stress levels of clients and professional caregivers.

Methods

We will conduct 15 single-case studies to assess patterns of physiological stress in dyads of clients with SPID and professional caregivers prior to CB in several Dutch residential institutes. Client-caregiver dyads will wear the Empatica E4 wristband for 20 sessions of 3 to 8 hours without interruptions of daily routines while caregivers report clients’ CB. The physiological measures obtained will be electrodermal activity (microsiemens) and heart rate (beats per minute). A multilevel model with repeated measures at the incident level nested within the person level will be applied, employing separate models for electrodermal activity and heart rate to compare stress levels in the 30 minutes prior to incidents with control epochs. Covariates in the models include movement, temperature, and gender. In addition, cross-recurrence quantification analyses will be performed to study the synchronization between the stress levels of clients and professional caregivers.

Results

The Ethics Committee of the Radboud University (NL-number: NL71683.091.19) approved the study on February 12, 2020. In total, 15 organizations have declared their commitment to participate in the study. The first result is expected in the spring of 2022.

Conclusions

Study results will demonstrate whether changes in patterns of electrodermal activity and heart rate are apparent in the 30 minutes preceding an incident of CB compared to baseline levels when the client does not engage in CB. The synchronization between caregivers’ and clients’ physiological stress levels will be explored with cross-recurrence quantification analyses. Insights into the physiological stress levels of clients and caregivers may contribute to a reduction of CB and an improvement of both clients’ and caregivers’ safety and well-being.

International Registered Report Identifier (IRRID)

DERR1-10.2196/24911

Framework for selecting and benchmarking mobile devices in psychophysiological research

Commercially available consumer electronics in (smartwatches and wearable biosensors) are increasingly enabling acquisition of peripheral physiological and physical activity data inside and outside of laboratory settings. However, there is scant literature available for selecting and assessing the suitability of these novel devices for scientific use. To overcome this limitation, the current paper offers a framework to aid researchers in choosing and evaluating wearable technologies for use in empirical research. Our seven-step framework includes: (1) identifying signals of interest; (2) characterizing intended use cases; (3) identifying study-specific pragmatic needs; (4) selecting devices for evaluation; (5) establishing an assessment procedure; (6) performing qualitative and quantitative analyses on resulting data; and, if desired, (7) conducting power analyses to determine sample size needed to more rigorously compare performance across devices. We illustrate the application of the framework by comparing electrodermal, cardiovascular, and accelerometry data from a variety of commercial wireless sensors (Affectiva Q, Empatica E3, Empatica E4, Actiwave Cardio, Shimmer) relative to a well-validated, wired MindWare laboratory system. Our evaluations are performed in two studies (N = 10, N = 11) involving psychometrically sound, standardized tasks that include physical activity and affect induction. After applying our framework to this data, we conclude that only some commercially available consumer devices for physiological measurement are capable of wirelessly measuring peripheral physiological and physical activity data of sufficient quality for scientific use cases. Thus, the framework appears to be beneficial at suggesting steps for conducting more systematic, transparent, and rigorous evaluations of mobile physiological devices prior to deployment in studies.

Usability and Acceptance of Wearable Biosensors in Forensic Psychiatry: Cross-sectional Questionnaire Study

Background

The use of wearable biosensor devices for monitoring and coaching in forensic psychiatric settings yields high expectations for improved self-regulation of emotions and behavior in clients and staff members. More so, if clients have mild intellectual disabilities (IQ 50-85), they might benefit from these biosensors as they are easy to use in everyday life, which ensures that clients can practice with the devices in multiple stress and arousal-inducing situations. However, research on (continuous) use and acceptance of biosensors in forensic psychiatry for clients with mild intellectual disabilities and their caretakers is scarce. Although wearable biosensors show promise for health care, recent research showed that the acceptance and continuous use of wearable devices in consumers is not as was anticipated, probably due to low expectations.

Objective

The main goal of this study was to investigate the associations between and determinants of the expectation of usability, the actual experienced usability, and the intention for continuous use of biosensors.

Methods

A total of 77 participants (31 forensic clients with mild intellectual disabilities and 46 forensic staff members) participated in a 1-week trial. Preceding the study, we selected 4 devices thought to benefit the participants in domains of self-regulation, physical health, or sleep. Qualitative and quantitative questionnaires were used that explored the determinants of usability, acceptance, and continuous use of biosensors. Questionnaires consisted of the System Usability Scale, the Technology Acceptance Model questionnaire, and the extended expectation confirmation model questionnaire.

Results

Only the experienced usability of the devices was associated with intended continuous use. Forensic clients scored higher on acceptance and intention for continuous use than staff members. Moderate associations were found between usability with acceptance and continuous use. Staff members showed stronger associations between usability and acceptance (r=.80, P<.001) and usability and continuous use (r=.79, P<.001) than clients, who showed more moderate correlations between usability and acceptance (r=.46, P=.01) and usability and continuous use (r=.52, P=.003). The qualitative questionnaires in general indicated that the devices were easy to use and gave clear information.

Conclusions

Contrary to expectations, it was the actual perceived usability of wearing a biosensor that was associated with continuous use and to a much lesser extent the expectancy of usability. Clients scored higher on acceptance and intention for continuous use, but associations between usability and both acceptance and continuous use were markedly stronger in staff members. This study provides clear directions on how to further investigate these associations. For example, whether this is a true effect or due to a social desirability bias in the client group must be investigated. Clients with mild intellectual disabilities might benefit from the ease of use of these devices and their continuing monitoring and coaching apps. For these clients, it is especially important to develop easy-to-use biosensors with a minimum requirement on cognitive capacity to increase usability, acceptance, and continuous use.

Is There a Characteristic Autonomic Response During Outbursts of Combative Behavior in Dementia Patients?

We sought to determine whether skin conductance level could warn of outbursts of combative behavior in dementia patients by using a wristband device. Two outbursts were captured and are reported here. Although no physiologic parameter measured by the wristband gave advance warning, there is a common pattern of parasympathetic withdrawal (increased heart rate) followed approximately 30 seconds later by sympathetic activation (increased skin conductance). In the literature, a similar pattern occurs in psychogenic non-epileptic seizures. We hypothesize that similar autonomic responses reflect similarities in pathophysiology and that physical activity may partially account for the time course of skin conductance.

Infants relax in response to unfamiliar foreign lullabies

Music is characterized by acoustic forms that are predictive of its behavioural functions. For example, adult listeners accurately identify unfamiliar lullabies as infant-directed on the basis of their musical features alone. This property could reflect a function of listeners' experiences, the basic design of the human mind, or both. Here, we show that US infants (N = 144) relax in response to eight unfamiliar foreign lullabies, relative to matched non-lullaby songs from other foreign societies, as indexed by heart rate, pupillometry and electrodermal activity. They do so consistently throughout the first year of life, suggesting that the response is not a function of their musical experiences, which are limited relative to those of adults. The infants' parents overwhelmingly chose lullabies as the songs that they would use to calm their fussy infant, despite their unfamiliarity. Together, these findings suggest that infants may be predisposed to respond to common features of lullabies found in different cultures.

Facial emotion mimicry in older adults with and without cognitive impairments due to Alzheimer's disease

Facial expression of humans is one of the main channels of everyday communication. The reported research work investigated communication regarding the pattern of emotional expression of healthy older adults and with mild cognitive impairments (MCI) or Alzheimer's disease (AD). It focuses on mimicking of displayed emotional facial expression on a sample of 25 older adults (healthy, MCI and AD patients). The adequacy of the patients' individual facial expressions in six basic emotions was measured with the Kinect 3D recording of the participants' facial expressions and compared to their own typical emotional facial expressions. The reactions were triggered by mimicking 49 still pictures of emotional facial expressions. No statistically significant differences in terms of frequency nor adequacy of emotional facial expression were reported in healthy and MCI groups. Unique patterns of emotional expressions have been observed in the AD group. Further investigating the pattern of older adults' facial expression may decrease the misunderstandings and increase the quality of life of the patients.

Biocueing and ambulatory biofeedback to enhance emotion regulation: A review of studies investigating non-psychiatric and psychiatric populations

Over the last years, biofeedback applications are increasingly used to enhance interoceptive awareness and self-regulation, in psychiatry and beyond. These applications are used to strengthen emotion regulation skills by home training (ambulatory biofeedback) and real-time support in everyday life stressful situations (biocueing). Unfortunately, knowledge about the feasibility and effectivity of these applications is still scarce. Therefore, a systematic literature search was performed. In total, 30 studies (4 biocueing, 26 ambulatory biofeedback) were reviewed; 21 of these studies were conducted in non-psychiatric samples and 9 studies in psychiatric samples. Study characteristics, biofeedback characteristics, effectivity and feasibility outcomes were extracted. Despite the rapid advances in wearable technology, only a few biocueing studies were found. In the majority of the studies significant positive effects were found on self-reported (stress-related) psychological measures. Significant improvements on physiological measures were also reported, though these measures were used less frequently. Feasibility of the applications was often reported as sufficient, though not adequately assessed in most studies. Taken into account the small sample sizes and the limited quality of the majority of the studies in this recently emerging field, biocueing and ambulatory biofeedback interventions showed promising results. Future research is expected to be focusing on biocueing as a just-in-time adaptive intervention. To establish this research field, closer cooperation between research groups, use of more rigorous as well as individually tailored research designs and more valid feasibility and effectivity assessment are recommended.

Embodiment of Wearable Technology: Qualitative Longitudinal Study

Background

Current technology innovations, such as wearables, have caused surprising reactions and feelings of deep connection to devices. Some researchers are calling mobile and wearable technologies cognitive prostheses, which are intrinsically connected to individuals as if they are part of the body, similar to a physical prosthesis. Additionally, while several studies have been performed on the phenomenology of receiving and wearing a physical prosthesis, it is unknown whether similar subjective experiences arise with technology.

Objective

In one of the first qualitative studies to track wearables in a longitudinal investigation, we explore whether a wearable can be embodied similar to a physical prosthesis. We hoped to gain insights and compare the phases of embodiment (ie, initial adjustment to the prosthesis) and the psychological responses (ie, accept the prosthesis as part of their body) between wearables and limb prostheses. This approach allowed us to find out whether this pattern was part of a cyclical (ie, period of different usage intensity) or asymptotic (ie, abandonment of the technology) pattern.

Methods

We adapted a limb prosthesis methodological framework to be applied to wearables and conducted semistructured interviews over a span of several months to assess if, how, and to what extent individuals come to embody wearables similar to prosthetic devices. Twelve individuals wore fitness trackers for 9 months, during which time interviews were conducted in the following three phases: after 3 months, after 6 months, and at the end of the study after 9 months. A deductive thematic analysis based on Murray’s work was combined with an inductive approach in which new themes were discovered.

Results

Overall, the individuals experienced technology embodiment similar to limb embodiment in terms of adjustment, wearability, awareness, and body extension. Furthermore, we discovered two additional themes of engagement/reengagement and comparison to another device or person. Interestingly, many participants experienced a rarely reported phenomenon in longitudinal studies where the feedback from the device was counterintuitive to their own beliefs. This created a blurring of self-perception and a dilemma of “whom” to believe, the machine or one’s self.

Conclusions

There are many similarities between the embodiment of a limb prosthesis and a wearable. The large overlap between limb and wearable embodiment would suggest that insights from physical prostheses can be applied to wearables and vice versa. This is especially interesting as we are seeing the traditionally “dumb” body prosthesis becoming smarter and thus a natural merging of technology and body. Future longitudinal studies could focus on the dilemma people might experience of whether to believe the information of the device over their own thoughts and feelings. These studies might take into account constructs, such as technology reliance, autonomy, and levels of self-awareness.

Using a Telegram chatbot as cost-effective software infrastructure for ambulatory assessment studies with iOS and Android devices

In this work, we present an innovative and cost-effective approach to run ambulatory assessment (AA) studies on participants’ smartphones via Telegram Messenger. Our approach works both for Android and iOS devices. The population of potential participants in a given country or region consists of all individuals who (a) are in possession of a smartphone, (b) are willing to install Telegram Messenger, and (c) live in an environment providing constant connection to the Internet. In our new approach to AA, participants are asked to subscribe to a Telegram chatbot that provides them with links to brief surveys at specified points in time in their everyday lives via short notifications. We developed a user-friendly Python script that allows for the flexible editing of the chatbot’s settings, e.g., the number of surveys per day. All common survey software designed for mobile devices can be used to present surveys to participants. This means that data collection takes place exclusively via the selected survey software, not via Telegram. With our approach, AA studies can be carried out among iOS and Android users cost-effectively and reliably while data security is ensured. Initial data from a pilot study show that studies of this kind are feasible, and the procedure is accepted by participants. Our Python script is licensed under General Public License (GPLv3) and therefore freely available and editable: https://github.com/Raze97/Telegram-Survey-Bot

Patch validation: an observational study protocol for the evaluation of a multisignal wearable sensor in patients during anaesthesia and in the postanaesthesia care unit

INTRODUCTION

Except for operating rooms, postanaesthesia care units and intensive care units, where the monitoring of vital signs is continuous, intermittent care is standard practice. However, at a time when only the patients with the most serious conditions are hospitalised and only a fraction of these patients are in intensive care units, this type of monitoring is no longer sufficient. Wireless monitoring has been proposed, but it requires rigorous validation. The aim of this observational study is to compare vital signs obtained from a precordial patch sensor to those obtained with conventional monitoring.

METHODS AND ANALYSIS

This patch validation trial will be an observational, prospective, single-centre open study of 115 anaesthetised adult patients monitored with both a wireless sensor (myAngel VitalSigns, Devinnova, Montpellier, France) and a standard bedside monitor (Carescape Monitor B850, GE Healthcare, Chicago, Illinois). Both sensors will be used to record peripheral oxygen saturation, respiratory rate, heart rate, body temperature and blood pressure (systolic and diastolic). The main objective will be to assess the degree of agreement between the two systems during the patients' stay in the postanaesthesia care unit, both at the raw signal level and at the clinical parameter level. The secondary objectives will be to assess the same performance under anaesthesia, the frequency of missing data or artefacts, the diagnostic performance of the systems, the influence of patients' characteristics on agreement between the two systems, the adverse events and the acceptability of the patch to patients. Bland-Altman plots will be used in the main analysis to detect discrepancies and estimate the limits of agreement.

ETHICS AND DISSEMINATION

Ethics approval was obtained from the Ethical Committee (Toulouse, France) on 10 April 2020. We are not yet recruiting subjects for this study. The results will be submitted for publication in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT04344093.