Advancing non-human primate welfare: An automated facial recognition system for unrestrained cynomolgus monkeys.

Cynomolgus monkeys (Macaca fascicularis) are vital in biomedical research, particularly for drug development and studying neurological diseases. However, accurately identifying individuals in group housing environments remains a significant challenge. This paper presents a near real-time facial recognition system tailored for cynomolgus monkeys, utilizing a fine-tuned Detectron2 model for face detection, followed by eigenface-based classification with Support Vector Machine (SVM) and radial basis function (RBF) kernel.

Disruption in Autonomic Nervous Activity Is Associated With Central and Peripheral-Level in Dry Eye With Unstable Tear Film.

Purpose: To measure autonomic nerve activity (ANA) in several eye conditions and verify whether ANA modulation is regulated by peripheral or central control in short tear film break-up time dry eye (sBUTDE).

Methods: This study included 23 eyes of 23 patients with sBUTDE (mean age 55.2 ± 16.

Effect of carbonated water on cerebral blood flow in the frontal region: a study using near-infrared spectroscopy.

Introduction: Carbonated water (CarbW) affects the swallowing function associated with the action of the brainstem. In addition, CarbW ingestion promotes mean blood flow in the middle cerebral artery, which is associated with blood flow to the frontal and temporal lobes. In this milieu, studies regarding the effect of drinking CarbW on brain activity are of significance.

Evaluation of a new portable corneal topography system for self-measurement using smartphones: a pilot study.

Purpose: Herein, we propose the use of the "KeraVio Ring", which is a portable, selfie-based, smartphone-attached corneal topography system that is based on the Placido ring videokeratoscope. The goal of this study was to evaluate and compare corneal parameters between KeraVio Ring and conventional corneal tomography images.

Methods: We designed the KeraVio Ring as a device comprising 3D-printed LED rings for generating Placido rings that can be attached to a smartphone.

Frontotemporal EEG as potential biomarker for early MCI: a case-control study.

Background: Previous studies using EEG (electroencephalography) as biomarker for dementia have attempted to research, but results have been inconsistent. Most of the studies have extremely small number of samples (average N = 15) and studies with large number of data do not have control group. We identified EEG features that may be biomarkers for dementia with 120 subjects (dementia 10, MCI 33, against control 77).

Characteristics of single-channel electroencephalogram in depression during conversation with noise reduction technology.

Background: Previous studies have attempted to characterize depression using electroencephalography (EEG), but results have been inconsistent. New noise reduction technology allows EEG acquisition during conversation.

Methods: We recorded EEG from 40 patients with depression as they engaged in conversation using a single-channel EEG device while conducting real-time noise reduction and compared them to those of 40 healthy subjects.

A Study on Legume-Based Noodles as Staple Food for Office Workers.

This study aims to verify the effects of "legume-based noodles" as a staple food for lunch, specifically: blood glucose, cognitive function tests, value, work questionnaires, typing, and body weight. The experiment is divided into two groups: the intervention group (legumes-based noodle) and the control group (regular lunch). Both groups have similar menu except the staple food.

Online improvisation training, hybrid improvisation training and on-site improvisation training; are they the same?

Background: Since the outbreak of COVID-19 in Wuhan in December 2019, lifestyle has been changing to an online-based learning and working environment rather than on-site, and improvisation training is no exception. However, no research compares the efficacy of online versus on-site training. Although we believed that the most effective way to learn improvisation is an on-site format, it is important to explore how format differences can affect learners.

Finding of the factors affecting the severity of COVID-19 based on mathematical models.

Since 2019, a large number of people worldwide have been infected with severe acute respiratory syndrome coronavirus 2. Among those infected, a limited number develop severe coronavirus disease 2019 (COVID-19), which generally has an acute onset. The treatment of patients with severe COVID-19 is challenging.

Sleep Stage Estimation from Bed Leg Ballistocardiogram Sensors.

Ballistocardiogram (BCG) is a graphical representation of the subtle oscillations in body movements caused by cardiovascular activity. Although BCGs cause less burden to the user, electrocardiograms (ECGs) are still commonly used in the clinical scene due to BCG sensors' noise sensitivity. In this paper, a robust method for sleep time BCG measurement and a mathematical model for predicting sleep stages using BCG are described.

The project for objective measures using computational psychiatry technology (PROMPT): Rationale, design, and methodology.

Introduction: Depressive and neurocognitive disorders are debilitating conditions that account for the leading causes of years lived with disability worldwide. However, there are no biomarkers that are objective or easy-to-obtain in daily clinical practice, which leads to difficulties in assessing treatment response and developing new drugs. New technology allows quantification of features that clinicians perceive as reflective of disorder severity, such as facial expressions, phonic/speech information, body motion, daily activity, and sleep.

Speech Quality Feature Analysis for Classification of Depression and Dementia Patients.

Loss of cognitive ability is commonly associated with dementia, a broad category of progressive brain diseases. However, major depressive disorder may also cause temporary deterioration of one's cognition known as pseudodementia. Differentiating a true dementia and pseudodementia is still difficult even for an experienced clinician and extensive and careful examinations must be performed.

Evaluating the severity of depressive symptoms using upper body motion captured by RGB-depth sensors and machine learning in a clinical interview setting: A preliminary study.

Background: Mood disorders have long been known to affect motor function. While methods to objectively assess such symptoms have been used in experiments, those same methods have not yet been applied in clinical practice because the methods are time-consuming, labor-intensive, or invasive.

Methods: We videotaped the upper body of each subject using a Red-Green-Blue-Depth (RGB-D) sensor during a clinical interview setting.