An Exercise-Based Precision Medicine Tool and Smartphone App for Managing Achilles Tendinopathy (the 'PhysViz' System): User-Centered Development Study.

Background: People with Achilles tendinopathy (AT) experience persistent pain that can limit engagement with daily occupations and negatively impact mental health. Current therapeutic exercise approaches vary in success, with many people experiencing reinjury, leading to a cycle of chronic tendinopathy often lasting years. High-magnitude precision loading may help people exit this feedback cycle, but applying these principles clinically is challenging.

Acute and Persistent Postoperative Functional Decline in Children with Severe Neurological Impairment: A Qualitative, Exploratory Study.

Background: Children with severe neurologic impairment (SNI) regularly require major surgery to manage their underlying conditions. Anecdotal evidence suggests that children with SNI experience unexpected and persistent postoperative functional changes long after the postoperative recovery period; however, evidence from the perspective of caregivers is limited. The purpose of the study was to explore the functional postoperative recovery process for children with SNI.

Neonatal Face and Facial Landmark Detection from Video Recordings.

This paper explores automated face and facial landmark detection of neonates, which is an important first step in many video-based neonatal health applications, such as vital sign estimation, pain assessment, sleep-wake classification, and jaundice detection. Utilising three publicly available datasets of neonates in the clinical environment, 366 images (258 subjects) and 89 (66 subjects) were annotated for training and testing, respectively. Transfer learning was applied to two YOLO-based models, with input training images augmented with random horizontal flipping, photo-metric colour distortion, translation and scaling during each training epoch.