An Analysis of COVID-19 Recovery Duration: Smartwatch Activity and Self-Report
Annu Int Conf IEEE Eng Med Biol Soc. 2025 Jul;2025:1-7. doi: 10.1109/EMBC58623.2025.11251653. ABSTRACT This study investigates the relationship between smartphone tracking data and self-reported COVID-19 experiences to better understand recovery patterns after COVID-19 infection in patients. We developed COronaVIden, an app that collects activity data through the iOS Health and Google Fit APIs, along with […]
Self-Reported Triggers Evaluation of High-Risk Dietary and Environmental Factors Preceding Migraine Onset by Using a Mobile Tracking App (Migraine Insight): Comparative Analysis Study
JMIR Form Res. 2025 Dec 3;9:e59951. doi: 10.2196/59951. ABSTRACT BACKGROUND: Migraines are a significant health concern affecting millions of individuals, often requiring habitual tracking of potential triggers to mitigate or predict episodes. Digital health tools such as mobile apps offer a scalable solution for personalized tracking and pattern recognition. Migraine Insight is one such app […]
Development of AI-integrated infrastructure with biomedical device and mobile app for neonatal vital monitoring during and in between kangaroo care sessions
Annu Int Conf IEEE Eng Med Biol Soc. 2025 Jul;2025:1-7. doi: 10.1109/EMBC58623.2025.11251596. ABSTRACT Premature infant mortality remains a critical challenge in low- and middle-income countries (LMICs), with continuous vital sign monitoring being essential for early detection of life-threatening conditions. This paper presents an integrated system combining NeoWarm, a novel biomedical device, with NeoRoo, a mobile […]
Eye State Prediction on Android Devices using Machine Learning for Natural Environment Electroencephalogram Applications
Annu Int Conf IEEE Eng Med Biol Soc. 2025 Jul;2025:1-7. doi: 10.1109/EMBC58623.2025.11253625. ABSTRACT Electroencephalogram (EEG) signals capture brain activity and are valuable for cognitive and medical applications. While deep learning models achieve high EEG classification accuracy, they require large datasets and significant resources. To overcome this, we developed a lightweight machine learning pipeline for EEG […]
The impact of workplace psychological violence on clinical nurses’ turnover intention: the mediating role of perceived stress
Front Public Health. 2025 Nov 17;13:1672644. doi: 10.3389/fpubh.2025.1672644. eCollection 2025. ABSTRACT BACKGROUND: The global shortage of nurses has become a significant health emergency, and nurses’ turnover intention is a key influencing factor, serving as an important predictor of actual turnover rates. However, studies integrating workplace psychological violence, perceived stress, and turnover intention in the same […]
Validation of a smartphone-based tremor measurement tool for Parkinson’s disease
Annu Int Conf IEEE Eng Med Biol Soc. 2025 Jul;2025:1-6. doi: 10.1109/EMBC58623.2025.11253144. ABSTRACT This study validates a smartphone app for hand tremor assessment in Parkinson’s disease (PD). Twenty-eight PD patients performed a weekly tremor test using the app while wearing a wrist-worn actigraphy device (GeneActiv), of which twenty-one yielded usable actigraphy data for comparative analysis. […]
Unsupervised Characterization of Temporal Dataset Shifts as an Early Indicator of AI Performance Variations: Evaluation Study Using the Medical Information Mart for Intensive Care-IV Dataset
JMIR Med Inform. 2025 Dec 3;13:e78309. doi: 10.2196/78309. ABSTRACT BACKGROUND: Reusing long-term data from electronic health records is essential for training reliable and effective health artificial intelligence (AI). However, intrinsic changes in health data distributions over time-known as dataset shifts, which include concept, covariate, and prior shifts-can compromise model performance, leading to model obsolescence and […]
Neonatal jaundice screening with variable screening thresholds using a smartphone and a transcutaneous bilirubinometer
Annu Int Conf IEEE Eng Med Biol Soc. 2025 Jul;2025:1-5. doi: 10.1109/EMBC58623.2025.11254104. ABSTRACT The neoSCB app is a smartphone app in development that can screen newborn babies for “significant jaundice“, defined as total serum bilirubin (TSB)> 250 μmol/L, which is the screening threshold for newborn babies older than 24 hours as recommended by the NICE […]
Understanding the user experience of a mobile produce market intervention toolkit
Transl Behav Med. 2025 Jan 16;15(1):ibaf083. doi: 10.1093/tbm/ibaf083. ABSTRACT OBJECTIVE: Veggie Van (VV) is an evidenced-based intervention for improving diet through a mobile market (MM) and is disseminated through an online toolkit. Understanding the user experience of the VV toolkit is crucial to inform its refinement and ensure future implementation success and positive public health […]
Privacy-Preserving Infant Sleep-Wake Detection in NICUs based on Federated Learning: A Multi-center Clinical Study
Annu Int Conf IEEE Eng Med Biol Soc. 2025 Jul;2025:1-4. doi: 10.1109/EMBC58623.2025.11251758. ABSTRACT Clinically, monitoring infants’ sleep-wake cycles provides crucial information of sleep parameters (e.g., sleep duration and frequency), enabling the assessment to their physiological and neuro developmental status. Recently, camera-based infant sleep-wake detection using facial features had been demonstrated in the Neonatal Intensive Care […]
