Assessment of Physiological Signals from Photoplethysmography Sensors Compared to an Electrocardiogram Sensor: A Validation Study in Daily Life.

Wearables with photoplethysmography (PPG) sensors are being increasingly used in clinical research as a non-invasive, inexpensive method for remote monitoring of physiological health. Ensuring the accuracy and reliability of PPG-derived measurements is critical, as inaccuracies can impact research findings and clinical decisions. This paper systematically compares heart rate (HR) and heart rate variability (HRV) measures from PPG against an electrocardiogram (ECG) monitor in free-living settings.

Evaluation of walking activity and gait to identify physical and mental fatigue in neurodegenerative and immune disorders: preliminary insights from the IDEA-FAST feasibility study.

Background: Many individuals with neurodegenerative (NDD) and immune-mediated inflammatory disorders (IMID) experience debilitating fatigue. Currently, assessments of fatigue rely on patient reported outcomes (PROs), which are subjective and prone to recall biases. Wearable devices, however, provide objective and reliable estimates of gait, an essential component of health, and may present objective evidence of fatigue.

Fatigue-Related Changes of Daily Function: Most Promising Measures for the Digital Age.

Background: Fatigue is a prominent symptom in many diseases and is strongly associated with impaired daily function. The measurement of daily function is currently almost always done with questionnaires, which are subjective and imprecise. With the recent advances of digital wearable technologies, novel approaches to evaluate daily function quantitatively and objectively in real-life conditions are increasingly possible.

Using a wearable patch to develop a digital monitoring biomarker of inflammation in response to LPS challenge.

Remote inflammation monitoring with digital health technologies (DHTs) would provide valuable information for both clinical research and care. Controlled perturbations of the immune system may reveal physiological signatures which could be used to develop a digital biomarker of inflammatory state. In this study, molecular and physiological profiling was performed following an in vivo lipopolysaccharide (LPS) challenge to develop a digital biomarker of inflammation.

Identification of Fatigue and Sleepiness in Immune and Neurodegenerative Disorders from Measures of Real-World Gait Variability.

Current assessments of fatigue and sleepiness rely on patient reported outcomes (PROs), which are subjective and prone to recall bias. The current study investigated the use of gait variability in the "real world" to identify patient fatigue and daytime sleepiness. Inertial measurement units were worn on the lower backs of 159 participants (117 with six different immune and neurodegenerative disorders and 42 healthy controls) for up to 20 days, whom completed regular PROs.

Regulatory Qualification of a Cross-Disease Digital Measure: Benefits and Challenges from the Perspective of IMI Consortium IDEA-FAST.

Background: Innovative Medicines Initiative (IMI) consortium IDEA-FAST is developing novel digital measures of fatigue, sleep quality, and impact of sleep disturbances for neurodegenerative diseases and immune-mediated inflammatory diseases. In 2022, the consortium met with the European Medicines Agency (EMA) to receive advice on its plans for regulatory qualification of the measures. This viewpoint reviews the IDEA-FAST perspective on developing digital measures for multiple diseases and the advice provided by the EMA.

A patient-centred conceptual model of nocturnal scratch and its impact in atopic dermatitis: A mixed-methods study supporting the development of novel digital measurements.

Background: Emerging digital measures and clinical outcome assessments (COAs) leveraging digital health technologies (DHTs) could address the need for objective, quantitative measures of symptoms of atopic dermatitis (AD), such as nocturnal scratching. Development of such measures needs to be supported by evidence reflecting meaningfulness to patients.

Objectives: To assess nocturnal scratching as a concept of interest associated with meaningful aspects of health of patients with AD (adults and children); and to explore patient-centred considerations for novel COAs measuring nocturnal scratch using DHTs.

Assessing fatigue and sleep in chronic diseases using physiological signals from wearables: A pilot study.

Problems with fatigue and sleep are highly prevalent in patients with chronic diseases and often rated among the most disabling symptoms, impairing their activities of daily living and the health-related quality of life (HRQoL). Currently, they are evaluated primarily Patient Reported Outcomes (PROs), which can suffer from recall biases and have limited sensitivity to temporal variations. Objective measurements from wearable sensors allow to reliably quantify disease state, changes in the HRQoL, and evaluate therapeutic outcomes.

Fatigue and Sleep Assessment using Digital Sleep Trackers: Insights from a Multi-Device Pilot Study.

For the patient community with neurodegenerative disorders (NDD) and immune-mediated inflammatory diseases (IMID), fatigue and sleep disturbances stand out as two of the most common and disabling symptoms, which mightily impair patient's quality of life. Traditional questionnaire-oriented approaches to reflect such symptoms suffer from recall bias and poor sensitivity to change. By virtue of multiple sensing modalities at home, IDEA-FAST project aims to identify novel digital endpoints of fatigue and sleep disturbances, that are objective, reliable and sensitive to change.

Learning Scan Paths of Eye Movement in Autism Spectrum Disorder.

Eye tracking studies have demonstrated deficits in attention in individuals with Autism Spectrum Disorder (ASD) for a range of different social attention-based tasks. Here we examined social attention skills in a large sample of ASD participants (n = 120), using eye tracking data from a social information processing task, and compared them with a typically developing (TD) group (n = 35). Assuming eye movement parameters are random variables generated by an underlying stochastic process, we modeled the fixation sequences of participants in ASD and TD groups with a Hidden Markov Model.

Automated recognition of spontaneous facial expression in individuals with autism spectrum disorder: parsing response variability.

Background: Reduction or differences in facial expression are a core diagnostic feature of autism spectrum disorder (ASD), yet evidence regarding the extent of this discrepancy is limited and inconsistent. Use of automated facial expression detection technology enables accurate and efficient tracking of facial expressions that has potential to identify individual response differences.

Methods: Children and adults with ASD (N = 124) and typically developing (TD, N = 41) were shown short clips of "funny videos.

Relationship Between Sleep and Behavior in Autism Spectrum Disorder: Exploring the Impact of Sleep Variability.

Objective: The relationship between sleep (caregiver-reported and actigraphy-measured) and other caregiver-reported behaviors in children and adults with autism spectrum disorder (ASD) was examined, including the use of machine learning to identify sleep variables important in predicting anxiety in ASD.

Methods: Caregivers of ASD ( = 144) and typically developing (TD) ( = 41) participants reported on sleep and other behaviors. ASD participants wore an actigraphy device at nighttime during an 8 or 10-week non-interventional study.

Caregiver Daily Reporting of Symptoms in Autism Spectrum Disorder: Observational Study Using Web and Mobile Apps.

Background: Currently, no medications are approved to treat core symptoms of autism spectrum disorder (ASD). One barrier to ASD medication development is the lack of validated outcome measures able to detect symptom change. Current ASD interventions are often evaluated using retrospective caregiver reports that describe general clinical presentation but often require recall of specific behaviors weeks after they occur, potentially reducing accuracy of the ratings.

An Observational Study With the Janssen Autism Knowledge Engine (JAKE) in Individuals With Autism Spectrum Disorder.

The Janssen Autism Knowledge Engine (JAKE®) is a clinical research outcomes assessment system developed to more sensitively measure treatment outcomes and identify subpopulations in autism spectrum disorder (ASD). Here we describe JAKE and present results from its digital phenotyping (My JAKE) and biosensor (JAKE Sense) components. An observational, non-interventional, prospective study of JAKE in children and adults with ASD was conducted at nine sites in the United States.

Visual Exploration in Autism Spectrum Disorder: Exploring Age Differences and Dynamic Features Using Recurrence Quantification Analysis.

Eye-tracking studies have demonstrated that individuals with autism spectrum disorder sometimes show differences in attention and gaze patterns. This includes preference for certain nonsocial objects, heightened attention to detail, and more difficulty with attention shifting and disengagement, which may be associated with restricted and repetitive behaviors. This study utilized a visual exploration task and replicates findings of reduced number of objects explored and increased fixation duration on high autism interest objects in a large sample of individuals with autism spectrum disorder (n = 129, age 6-54 years) in comparison with a typically developing group.

Intra-monsoonal variation of zooplankton population in the Sundarbans Estuarine System, India.

The present study was conducted during July 2013 (early phase of monsoon or EM) and September 2013 (later phase of monsoon or LM) to ascertain the intra-monsoonal variation on zooplankton, by selecting 15 study stations in the river Saptamukhi, one of the main estuaries in the Sundarbans Estuarine System (SES). In 2013, SES experienced an unusually high monsoonal rainfall also exacerbated by cloud burst event at Himalayan region (upper stretches of SES) which tremendously increased the river runoff. The present work was aimed to decipher the effect of this unusual precipitation during the monsoon season on zooplankton assemblages along with different hydrological parameters.

Heritable stress response dynamics revealed by single-cell genealogy.

Cells often respond to environmental stimuli by activating specific transcription factors. Upon exposure to glucose limitation stress, it is known that yeast cells dephosphorylate the general stress response factor Msn2, leading to its nuclear localization, which in turn activates the expression of many genes. However, the precise dynamics of Msn2 nucleocytoplasmic translocations and whether they are inherited over multiple generations in a stress-dependent manner are not well understood.