Multicenter Evaluation of Machine-Learning Continuous Pulse Rate Algorithm on Wrist-Worn Device.

Introduction: Though wrist-worn photoplethysmography (PPG) sensors play an important role in long-term and continuous heart rhythm monitoring, signals measured at the wrist are contaminated by more intense motion artifacts compared to other body locations. Machine learning (ML)-based algorithms can improve long-term pulse rate (PR) tracking but are associated with more stringent regulatory requirements when intended for clinical use. This study aimed to evaluate the accuracy of a digital health technology using wrist-worn PPG sensors and an ML-based algorithm to measure PR continuously.

Necessary for seizure forecasting outcome metrics: Seizure frequency and benchmark model.

Background: This study aims to illustrate the connection between seizure frequency (SF) and performance metrics in seizure forecasting, and to compare the effectiveness of a moving average (MA) model versus the commonly used permutation benchmark.

Methods: Metrics of calibration and discrimination were computed for each dataset, comparing MA and permutation performance across SF values. Three datasets were used: (1) self-reported seizure diaries from 3994 Seizure Tracker patients, (2) automatically detected and sometimes manually reported or edited generalized tonic-clonic seizures from 2350 Empatica Embrace 2 and Mate App users, and (3) simulated datasets with varying SFs.

Necessary for seizure forecasting outcome metrics: seizure frequency and benchmark model.

Work is ongoing to advance seizure forecasting, but the performance metrics used to evaluate model effectiveness can sometimes lead to misleading outcomes. For example, some metrics improve when tested on patients with a particular range of seizure frequencies (SF). This study illustrates the connection between SF and metrics.

Brief Report: Quantifying Speech Production Coordination from Non- and Minimally-Speaking Individuals.

Purpose: Non-verbal utterances are an important tool of communication for individuals who are non- or minimally-speaking. While these utterances are typically understood by caregivers, they can be challenging to interpret by their larger community. To date, there has been little work done to detect and characterize the vocalizations produced by non- or minimally-speaking individuals.

Gaussian-process-based Bayesian optimization for neurostimulation interventions in rats.

Effective neural stimulation requires adequate parametrization. Gaussian-process (GP)-based Bayesian optimization (BO) offers a framework to discover optimal stimulation parameters in real time. Here, we first provide a general protocol to deploy this framework in neurostimulation interventions and follow by exemplifying its use in detail.

Testing a Behavioral Activation Gaming App for Depression During Pregnancy: Multimethod Pilot Study.

Background: Depression during pregnancy is increasingly recognized as a worldwide public health problem. If untreated, there can be detrimental outcomes for the mother and child. Anxiety is also often comorbid with depression.

Prospective clinical validation of the Empatica EmbracePlus wristband as a reflective pulse oximeter.

Introduction: Respiratory diseases such as chronic obstructive pulmonary disease, obstructive sleep apnea syndrome, and COVID-19 may cause a decrease in arterial oxygen saturation (SaO). The continuous monitoring of oxygen levels may be beneficial for the early detection of hypoxemia and timely intervention. Wearable non-invasive pulse oximetry devices measuring peripheral oxygen saturation (SpO) have been garnering increasing popularity.

ReCANVo: A database of real-world communicative and affective nonverbal vocalizations.

Nonverbal vocalizations, such as sighs, grunts, and yells, are informative expressions within typical verbal speech. Likewise, individuals who produce 0-10 spoken words or word approximations ("minimally speaking" individuals) convey rich affective and communicative information through nonverbal vocalizations even without verbal speech. Yet, despite their rich content, little to no data exists on the vocal expressions of this population.

Transforming Health Through Communities: An Experience From a Collaborative Online International Learning Program.

Background: For many years, universities have placed a strong emphasis on providing students with an internationalization experience through study-abroad programs; however, the recent pandemic led many universities to look for alternatives to continue offering students an international experience.

Method: This article describes the implementation and evaluation of a collaborative online international learning (COIL) experience between nursing students in Australia and the United Kingdom.

Results: Students explored community spirit in the recovery from COVID-19.

Interventions to Modify Psychological Well-Being: Progress, Promises, and an Agenda for Future Research.

Psychological well-being, characterized by feelings, cognitions, and strategies that are associated with positive functioning (including hedonic and eudaimonic well-being), has been linked with better physical health and greater longevity. Importantly, psychological well-being can be strengthened with interventions, providing a strategy for improving population health. But are the effects of well-being interventions meaningful, durable, and scalable enough to improve health at a population-level? To assess this possibility, a cross-disciplinary group of scholars convened to review current knowledge and develop a research agenda.

Deploying a robotic positive psychology coach to improve college students' psychological well-being.

Despite the increase in awareness and support for mental health, college students' mental health is reported to decline every year in many countries. Several interactive technologies for mental health have been proposed and are aiming to make therapeutic service more accessible, but most of them only provide one-way passive contents for their users, such as psycho-education, health monitoring, and clinical assessment. We present a robotic coach that not only delivers interactive positive psychology interventions but also provides other useful skills to build rapport with college students.

A Robotic Companion for Psychological Well-being: A Long-term Investigation of Companionship and Therapeutic Alliance.

Social support plays a crucial role in managing and enhancing one's mental health and well-being. In order to explore the role of a robot's companion-like behavior on its therapeutic interventions, we conducted an eight-week-long deployment study with seventy participants to compare the impact of (1) a with only assistant-like skills, (2) a with additional instructive positive psychology interventions, and (3) a that delivered the same interventions in a peer-like and supportive manner. The companion-like robot was shown to be the most effective in building a positive therapeutic alliance with people, enhancing participants' well-being and readiness for change.

Digitally-enabled, patient-centred care in rhinitis and asthma multimorbidity: The ARIA-MASK-air approach.

MASK-air , a validated mHealth app (Medical Device regulation Class IIa) has enabled large observational implementation studies in over 58,000 people with allergic rhinitis and/or asthma. It can help to address unmet patient needs in rhinitis and asthma care. MASK-air is a Good Practice of DG Santé on digitally-enabled, patient-centred care.

Building a culture of responsible neurotech: Neuroethics as socio-technical challenges.

Scientists around the globe are joining the race to achieve engineering feats to read, write, modulate, and interface with the human brain in a broadening continuum of invasive to non-invasive ways. The expansive implications of neurotechnology for our conception of health, mind, decision-making, and behavior has raised social and ethical considerations that are inextricable from neurotechnological progress. We propose "socio-technical" challenges as a framing to integrate neuroethics into the engineering process.

Smartwatch biomarkers and the path to clinical use.

Wearables have advanced from collecting consumer-quality fitness data to collecting continuous clinical-quality physiology that, when processed carefully, can identify medically significant events. In a recent issue of Nature Medicine, Dunn et al. described how vital signs from wearables predict clinical laboratory blood- and urine-based measurements better than vital signs measured in the clinic.

Combining Electrodermal Activity With the Peak-Pain Time to Quantify Three Temporal Regions of Pain Experience.

Background: Self-reported pain levels, while easily measured, are often not reliable for quantifying pain. More objective methods are needed that supplement self-report without adding undue burden or cost to a study. Methods that integrate multiple measures, such as combining self-report with physiology in a structured and specific-to-pain protocol may improve measures.