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Age group classification based on optical measurement of brain pulsation using machine learning.
Sci Rep
January 2025
Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland.
Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monitor real-time changes in cerebral hemodynamics. In this study, thirty-six healthy adults were measured by single channel fNIRS to explore differences between two age groups using machine learning (ML). The subjects, measured during functional magnetic resonance imaging (fMRI) at Oulu University Hospital, were divided into young (age ≤ 32) and elderly (age ≥ 57) groups.
View Article and Find Full Text PDFPurpose: To evaluate the effect of osilodrostat and hypercortisolism control on blood pressure (BP) and glycemic control in patients with Cushing's disease.
Methods: Pooled analysis of two Phase III osilodrostat studies (LINC 3 and LINC 4), both comprising a 48-week core phase and an optional open-label extension. Changes from baseline in systolic and diastolic BP (SBP and DBP), fasting plasma glucose (FPG), and glycated hemoglobin (HbA) were evaluated during osilodrostat treatment in patients with/without hypertension or diabetes at baseline.
Ability of dynamic chest radiography to identify left ventricular systolic dysfunction in heart failure.
Int J Cardiovasc Imaging
January 2025
Department of Cardiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan.
Dynamic chest radiography (DCR) can estimate haemodynamic parameters in heart failure (HF). However, no studies have evaluated its ability to determine cardiac systolic function in HF. This experimental study investigates the correlation between left ventricular (LV) ejection fraction (LVEF) and DCR image parameters in HF.
View Article and Find Full Text PDFDepression Recognition Using Daily Wearable-Derived Physiological Data.
Sensors (Basel)
January 2025
Department of Psychological and Cognitive Sciences, Tsinghua University, Beijing 100084, China.
The objective identification of depression using physiological data has emerged as a significant research focus within the field of psychiatry. The advancement of wearable physiological measurement devices has opened new avenues for the identification of individuals with depression in everyday-life contexts. Compared to other objective measurement methods, wearables offer the potential for continuous, unobtrusive monitoring, which can capture subtle physiological changes indicative of depressive states.
View Article and Find Full Text PDFMonitoring Sleep and Nightly Recovery with Wrist-Worn Wearables: Links to Training Load and Performance Adaptations.
Sensors (Basel)
January 2025
Faculty of Sport and Health Sciences, University of Jyväskylä, 40014 Jyväskylä, Finland.
Previous studies on the effects of intensified training on sleep quality/quantity have been somewhat contradictory. Moreover, recreational athletes often track various sleep metrics, and those metrics' actual connections to training adaptations are unknown. This study explored the effects of intensified training on sleep and nightly recovery along with their associations with training adaptations.
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