Longitudinal Changes in Pitch-Related Acoustic Characteristics of the Voice Throughout the Menstrual Cycle: Observational Study.

Background: Identifying subtle changes in the menstrual cycle is crucial for effective fertility tracking and understanding reproductive health.

Objective: The aim of the study is to explore how fundamental frequency features vary between menstrual phases using daily voice recordings.

Methods: This study analyzed smartphone-collected voice recordings from 16 naturally cycling female participants, collected every day for 1 full menstrual cycle.

Linear effects of glucose levels on voice fundamental frequency in type 2 diabetes and individuals with normoglycemia.

Glucose levels in the body have been hypothesized to affect voice characteristics. One of the primary justifications for voice changes are due to Hooke's law, in which a variation in the tension, mass, or length of the vocal folds, mediated by the body's glucose levels, results in an alteration in their vibrational frequency. To explore this hypothesis, 505 participants were fitted with a continuous glucose monitor (CGM) and instructed to record their voice using a custom mobile application up to six times daily for 2 weeks.

Investigation of Deepfake Voice Detection Using Speech Pause Patterns: Algorithm Development and Validation.

Background: The digital era has witnessed an escalating dependence on digital platforms for news and information, coupled with the advent of "deepfake" technology. Deepfakes, leveraging deep learning models on extensive data sets of voice recordings and images, pose substantial threats to media authenticity, potentially leading to unethical misuse such as impersonation and the dissemination of false information.

Objective: To counteract this challenge, this study aims to introduce the concept of innate biological processes to discern between authentic human voices and cloned voices.

Impact of Audio Data Compression on Feature Extraction for Vocal Biomarker Detection: Validation Study.

Background: Vocal biomarkers, derived from acoustic analysis of vocal characteristics, offer noninvasive avenues for medical screening, diagnostics, and monitoring. Previous research demonstrated the feasibility of predicting type 2 diabetes mellitus through acoustic analysis of smartphone-recorded speech. Building upon this work, this study explores the impact of audio data compression on acoustic vocal biomarker development, which is critical for broader applicability in health care.

A Radar-Based Opioid Overdose Detection Device for Public Restrooms: Design, Development, and Evaluation Study.

Background: The opioid epidemic is a growing crisis worldwide. While many interventions have been put in place to try to protect people from opioid overdoses, they typically rely on the person to take initiative in protecting themselves, requiring forethought, preparation, and action. Respiratory depression or arrest is the mechanism by which opioid overdoses become fatal, but it can be reversed with the timely administration of naloxone.

A parsimonious model of blood glucose homeostasis.

The mathematical modelling of biological systems has historically followed one of two approaches: comprehensive and minimal. In comprehensive models, the involved biological pathways are modelled independently, then brought together as an ensemble of equations that represents the system being studied, most often in the form of a large system of coupled differential equations. This approach often contains a very large number of tuneable parameters (> 100) where each describes some physical or biochemical subproperty.