Blood glucose monitoring is considered the gold standard for diabetes diagnostics and self-monitoring. However, the underlying process is invasive and highly uncomfortable for patients. Furthermore, the process must be completed several times a day to successfully manage the disease, which greatly contributes to the massive need for non-invasive monitoring options. Human serums, such as saliva, sweat, breath, urine and tears, contain traces of glucose and are easily accessible. Therefore, they allow minimal to non-invasive glucose monitoring, making them attractive alternatives to blood measurements. Numerous developments regarding noninvasive glucose detection techniques have taken place over the years, but recently, they have gained recognition as viable alternatives, due to the advent of nanotechnology-based sensors. Such sensors are optimal for testing the amount of glucose in serums other than blood thanks to their enhanced sensitivity and selectivity ranges, in addition to their size and compatibility with electronic circuitry. These nanotechnology approaches are rapidly evolving, and new techniques are constantly emerging. Hence, this manuscript aims to review current and future nanomaterial-based technologies utilizing saliva, sweat, breath and tears as a diagnostic medium for diabetes monitoring.

A 100-channel fully implantable wireless broadband neural recording system was developed. It features 100 parallel broadband (0.1 Hz-7.8 kHz) neural recording channels, a medical grade 200 mAh Li-ion battery recharged inductively at 150 kHz , and data telemetry using 3.2 GHz to 3.8 GHz FSK modulated wireless link for 48 Mbps Manchester encoded data. All active electronics are hermetically sealed in a titanium enclosure with a sapphire window for electromagnetic transparency. A custom, high-density configuration of 100 individual hermetic feedthrough pins enable connection to an intracortical neural recording microelectrode array. A 100 MHz bandwidth custom receiver was built to remotely receive the FSK signal and achieved -77.7 dBm sensitivity with 10 ^-8 BER at 48 Mbps data rate. ESD testing on all the electronic inputs and outputs has proven that the implantable device satisfies the HBM Class-1B ESD Standard. In addition, the evaluation of the worst-case charge density delivered to the tissue from each I/O pin verifies the patient safety of the device in the event of failure. Finally, the functionality and reliability of the complete device has been tested on-bench and further validated chronically in ongoing freely moving swine and monkey animal trials for more than one year to date.

Background and Purpose: One emerging power mobility device (PMD) option that has gained recognition as a means for a cost-effective introduction to power mobility for young children is the battery powered modified ride-on toy car. Many groups, nationally and internationally, have been modifying battery powered ride-on toy cars by adding seating support and a large center placed push button switch for motor activation. The purpose of this technical report is to introduce an enhanced steering and drive system based on proportional control through a joystick. Key Points: This report offers (1) a technical description of these modifications that allow directional steering and programmable starting and driving velocity, (2) an example of a modified ride on toy, including common seating modifications, and (3) a short summary of results from a group of 7 children under the age of six with complex, severe disabilities. Clinical Impact: Although proportional joystick modifications are more complex than the common single switch activation, they allow children greater control to achieve self-initiated, self-directed movement that allow play, peer interaction, and exploration in their natural environments, even in the most highly complex cases. All seven children were able to intentionally self-initiate activation of the modified ride-on car and experience the subsequent movement.

The School of Engineering and the Physical Therapy program at the University of North Florida developed a novel, community-based course where undergraduate engineering students are partnered with physical therapy students. In this course students participate in hands-on, team-based design projects focused on low-tech and high-tech rehabilitation technology for children with disabilities. The impact of this interprofessional education experience on the students has been evaluated using the Public Service Motivation Scale for three years and its impact on the students is presented.

Toy-related injuries have increased significantly in the past decade, in particular those related to ride-on toys. This increase has been attributed to movement related events such as falls and inertial impacts. Furthermore, children with disabilities have been reported to be at a greater risk of being injured, and are therefore more susceptible to toy-related injuries. Although, efforts are being made to modify ride-on toys as a method for increasing quality of life in children with disabilities, there are very limited pediatric safety studies regarding children with disabilities and modified ride-on toys. This manuscript presents a systematic review of literature summarizing the current state of toy-related injuries including children with and without disabilities. Children exposed to inertial impacts in motor vehicle crashes have also been reviewed to present current pediatric safety testing methodologies and injury tolerance thresholds. Out of 2608 articles, 10 studies were included regarding current trends in toy-related injuries and safety testing methodologies. From this study, a gap in the literature was discovered concerning the susceptibility of children with disabilities to toy-related injuries, specifically in relation to ride-on toys and the repercussion surrounding such injuries. It is theorized that such lack of data is due to the difficulty and costs associated with experimental validation. Hence, it is recommended that computer simulations be used to provide preliminary data analysis.

Human movement analysis is crucial in health and sports biomechanics for understanding physical performance, guiding rehabilitation, and preventing injuries. However, existing tools are often proprietary, expensive, and function as "black boxes", limiting user control and customization. This paper introduces vailá-Versatile Anarcho Integrated Liberation Ánalysis in Multimodal Toolbox-an open-source, Python-based platform designed to enhance human movement analysis by integrating data from multiple biomechanical systems. vailá supports data from diverse sources, including retroreflective motion capture systems, inertial measurement units (IMUs), markerless video capture technology, electromyography (EMG), force plates, and GPS or GNSS systems, enabling comprehensive analysis of movement patterns. Developed entirely in Python 3.11.9, which offers improved efficiency and long-term support, and featuring a straightforward installation process, vailá is accessible to users without extensive programming experience. In this paper, we also present several workflow examples that demonstrate how vailá allows the rapid processing of large batches of data, independent of the type of collection method. This flexibility is especially valuable in research scenarios where unexpected data collection challenges arise, ensuring no valuable data point is lost. We demonstrate the application of vailá in analyzing sit-to-stand movements in pediatric disability, showcasing its capability to provide deeper insights even with unexpected movement patterns. By fostering a collaborative and open environment, vailá encourages users to innovate, customize, and freely explore their analysis needs, potentially contributing to the advancement of rehabilitation strategies and performance optimization.