Clinical Decision Support Using Speech Signal Analysis: Systematic Scoping Review of Neurological Disorders.

Background: Digital biomarkers are increasingly used in clinical decision support for various health conditions. Speech features as digital biomarkers can offer insights into underlying physiological processes due to the complexity of speech production. This process involves respiration, phonation, articulation, and resonance, all of which rely on specific motor systems for the preparation and execution of speech.

The mediating role of social support on the link between adverse childhood experiences and adult mental health.

Adverse childhood experiences (ACEs) have been associated with adult mental health, especially anxiety and depression. We aimed to explain these relationships by investigating perceived social support as a mediating factor. In this model, it is proposed that individuals who experience more ACEs will have less perceived social support in adulthood, which in turn will increase reported anxiety and depression symptoms.

A Comprehensive Multifunctional Approach for Measuring Parkinson's Disease Severity.

Objectives:  This research study aims to advance the staging of Parkinson's disease (PD) by incorporating machine learning to assess and include a broader multifunctional spectrum of neurocognitive symptoms in the staging schemes beyond motor-centric assessments. Specifically, we provide a novel framework to modernize and personalize PD staging more objectively by proposing a hybrid feature scoring approach.

Methods:  We recruited 37 individuals diagnosed with PD, each of whom completed a series of tablet-based neurocognitive tests assessing motor, memory, speech, executive functions, and tasks ranging in complexity from single to multifunctional.

Predicting long-term sleep deprivation using wearable sensors and health surveys.

Sufficient sleep is essential for individual well-being. Inadequate sleep has been shown to have significant negative impacts on our attention, cognition, and mood. The measurement of sleep from in-bed physiological signals has progressed to where commercial devices already incorporate this functionality.

Mental Health Monitoring: Design Concept of a Smartphone Application.

Mental health (MH) has become a global issue. Digital phenotyping in mental healthcare provides a highly effective, scaled, cost-effective approach to handling global MH problems. We propose an MH monitoring application.