Flexible Gel-Free Multi-Modal Wireless Sensors With Edge Deep Learning for Detecting and Alerting Freezing of Gait Symptom.

Freezing of gait (FoG) is a debilitating symptom of Parkinson's disease (PD). This work develops flexible wearable sensors that can detect FoG and alert patients and companions to help prevent falls. FoG is detected on the sensors using a deep learning (DL) model with multi-modal sensory inputs collected from distributed wireless sensors.

Experiences with recruitment and retention of adolescents and emerging adults in a weight loss intervention trial.

Background/aims: Efficient and effective participant recruitment is key for successful clinical research. Adolescent and emerging adult recruitment into clinical trials can be particularly challenging, especially when targeting underrepresented groups. This study aimed to determine the most successful recruitment strategies from those employed during a pediatric trial testing the efficacy of a behavioral intervention on adiposity and cardiovascular disease risk.

Contrasting behavior of heterochromatic and euchromatic chromosome portions and pericentric genome separation in pre-bouquet spermatocytes of hybrid mice.

The spatial distribution of parental genomes has attracted much interest because intranuclear chromosome distribution can modulate the transcriptome of cells and influence the efficacy of meiotic homologue pairing. Pairing of parental chromosomes is imperative to sexual reproduction as it translates into homologue segregation and genome haploidization to counteract the genome doubling at fertilization. Differential FISH tagging of parental pericentromeric genome portions and specific painting of euchromatic chromosome arms in Mus musculus (MMU) × Mus spretus (MSP) hybrid spermatogenesis disclosed a phase of homotypic non-homologous pericentromere clustering that led to parental pericentric genome separation from the pre-leptoteneup to zygotene stages.

Markerless motion capture and measurement of hand kinematics: validation and application to home-based upper limb rehabilitation.

Dynamic movements of the hand, fingers, and thumb are difficult to measure due to the versatility and complexity of movement inherent in function. An innovative approach to measuring hand kinematics is proposed and validated. The proposed system utilizes the Microsoft Kinect and goes beyond gesture recognition to develop a validated measurement technique of finger kinematics.