Comprehensive Symptom Prediction in Inpatients With Acute Psychiatric Disorders Using Wearable-Based Deep Learning Models: Development and Validation Study.

Background: Assessing the complex and multifaceted symptoms of patients with acute psychiatric disorders proves to be significantly challenging for clinicians. Moreover, the staff in acute psychiatric wards face high work intensity and risk of burnout, yet research on the introduction of digital technologies in this field remains limited. The combination of continuous and objective wearable sensor data acquired from patients with deep learning techniques holds the potential to overcome the limitations of traditional psychiatric assessments and support clinical decision-making.

Association of heart rate variability with REM sleep without atonia in idiopathic REM sleep behavior disorder.

Study Objectives: Idiopathic rapid eye movement sleep behavior disorder (iRBD), characterized by rapid eye movement sleep without atonia (RSWA) and dream-enactment behavior, has been suggested to be a predictor of α-synucleinopathies. Autonomic instability, represented by heart rate variability, is a common characteristic of both iRBD and α-synucleinopathies. Previous studies reported that RSWA was associated with autonomic dysfunction and was a possible predictor of phenoconversion.

Design of a dual sensor probe array for internal field measurement in Versatile Experiment Spherical Torus.

A dual sensor probe array is designed and constructed for internal magnetic field measurement at Versatile Experiment Spherical Torus (VEST) at the Seoul National University. Simultaneous use of Hall sensors and chip inductors allows cross-calibration among the measurements and compensation for each other's weaknesses while their small sizes are expected to cause only mild plasma perturbations. Calibration of the dual sensor probe array, using a Helmholtz coil, shows good sensitivity for the magnetic field measurement of the VEST.