Journal of Biomedical And Health Informatics

Featured Articles
FENet: A Frequency Extraction Network for Obstructive Sleep Apnea Detection
Obstructive Sleep Apnea (OSA) is a highly prevalent but inconspicuous disease that seriously jeopardizes the health of human beings. Polysomnography (PSG), the gold standard of detecting OSA, requires multiple specialized sensors for signal collection, hence patients have to physically visit... Read more
Articles
Continuous Gait Phase Estimation using LSTM for Robotic Transfemoral Prosthesis Across Walking Speeds
User gait phase estimation plays a key role for the seamless control of the lower-limb robotic assistive devices (e.g., exoskeletons or prostheses) during ambulation. To achieve this, several studies have attempted to estimate the gait phase using a thigh or... Read more
Articles
Characterization of a Benchmark Database for Myoelectric Movement Classification
In this paper, we characterize the Ninapro database and its use as a benchmark for hand prosthesis evaluation. The database is a publicly available resource that aims to support research on advanced myoelectric hand prostheses. The database is obtained by... Read more
Articles
A Novel Wearable Device for Continuous Temperature Monitoring & Fever Detection
Continuous temperature monitoring in high-risk patients can enable healthcare providers to remotely track patients’ temperatures, promptly detect fevers and timely intervene to improve clinical outcomes. We evaluated if a novel wearable, continuous temperature monitor (Verily Patch) can reliably estimate body... Read more
Articles
Using Wearables and Machine Learning to Enable Personalized Lifestyle Recommendations to Improve Blood Pressure
Background: Blood pressure (BP) is an essential indicator for human health and is known to be greatly influenced by lifestyle factors, like activity and sleep factors. However, the degree of impact of each lifestyle factor on BP is unknown and... Read more
Featured Articles
Quantification of Motor Function Post-stroke using Novel Combination of Wearable Inertial and Mechanomyographic Sensors
Subjective clinical rating scales represent the gold-standard diagnosis of motor function following stroke, however in practice they suffer from well-recognized limitations including assessor variance, low inter-rater reliability and low resolution. Automated systems have been proposed for empirical quantification but have... Read more
Featured Articles
Evaluation of a Wireless Tongue Tracking System on the Identification of Phoneme Landmarks
Visualizing tongue movement in real-time has the potential to improve therapy outcome for millions of people worldwide living with a speech sound disorder because the positioning of the tongue is crucial in the production of many phonemes to be intelligible. Our team has developed a wearable 3D tongue tracking system based on a wireless magnetic localization method. To evaluate its tracking accuracy, 2,500 tongue trajectories were recorded from 10 subjects uttering 25 phonemes. The results show that our system is capable of tracking tongue motion with positional errors in the order of few millimeters (median: 3.9 mm, Q3: 5.8 mm)... Read more
Featured Articles
Fit to Burst: Toward Noninvasive Estimation of Achilles Tendon Load Using Burst Vibrations
In this study, we present a novel method of noninvasively estimating mechanical load in the Achilles tendon using burst vibrations. These vibrations, produced by a small vibration motor on the skin superficial to the tendon, are sensed by a skin-mounted accelerometer, which measures the tendon’s response to burst excitation under varying tensile load. Characteristic changes in the burst response profile as a function of tendon tension are observed and used as inputs to an ML model, which yields accurate (R2 = 0.85) estimates of ankle loading during gait. Preliminary results of a fully wearable ankle load monitor are also presented... Read more
Featured Articles
A Machine Learning Enabled Wireless Intracranial Brain Deformation Sensing System
A leading cause of traumatic brain injury (TBI) is intracranial brain deformation from mechanical impact. This deformation is viscoelastic and differs from a traditional rigid transformation. Here, we present a machine learning enabled wireless sensing system, which can predict the trajectory of intracranial brain deformation by interpreting the magnetic sensor outputs created by the change in position of the implanted soft magnet. Both in vitro and in vivo experimental results showed an overall accuracy of over 92%, suggesting that this sensing scheme can be an effective tool for studying TBI due to in situ and real-time brain deformation prediction... Read more
Articles
Modeling Large Sparse Data for Feature Selection: Hospital Admission Predictions of the Dementia Patients using Primary Care Electronic Health Records
A growing elderly population suffering from incurable, chronic conditions such as dementia present a continual strain on medical services due to mental impairment paired with high comorbidity resulting in increased hospitalization risk. The identification of at risk individuals allows for... Read more