Intelligent plantar pressure offloading for the prevention of diabetic foot ulcers and amputations.

The high prevalence of lower extremity ulceration and amputation in people with diabetes is strongly linked to difficulties in achieving and maintaining a reduction of high plantar pressures (PPs) which remains an important risk factor. The effectiveness of current offloading footwear is opposed in part by poor patient adherence to these interventions which have an impact on everyday living activities of patients. Moreover, the offloading devices currently available utilize primarily passive techniques, whereas PP distribution is a dynamically changing process with frequent shifts of high PP areas under different areas of the foot. Thus, there is a need for pressure offloading footwear capable of regularly and autonomously adapting to PPs of people with diabetes. The aim of this article is to summarize the concepts of intelligent pressure offloading footwear under development which will regulate PPs in people with diabetes to prevent and treat diabetic foot ulcers. Our team is creating this intelligent footwear with an auto-contouring insole which will continuously read PPs and adapt its shape in the forefoot and heel regions to redistribute high PP areas. The PP-redistribution process is to be performed consistently while the footwear is being worn. To improve adherence, the footwear is designed to resemble a conventional shoe worn by patients in everyday life. Preliminary pressure offloading and user perceptions assessments in people without and with diabetes, respectively, exhibit encouraging results for the future directions of the footwear. Overall, this intelligent footwear is designed to prevent and treat diabetic foot ulcers while enhancing patient usability for the ultimate prevention of lower limb amputations.

An IoT Solution for Online Monitoring of Anesthetics in Human Serum Based on an Integrated Fluidic Bioelectronic System.

In this paper, we present the design, the implementation and the validation of a novel Internet of Things (IoT) drug monitoring system for the online continuous and simultaneous detection of two main anesthetics, e.g., propofol and paracetamol, in undiluted human serum. The described full system consists of a custom-built electronic Raspberry Pi (RPi) based Printed Circuit Board (PCB) that drives and reads out the signal from an electrochemical sensing platform integrated into a fluidic system. Thanks to the Polydimethylsiloxane (PDMS) fluidic device, the analyzed sample is automatically fluxed on the sensing site. The IoT network is supported by a Cloud system, which allows the doctor to control and share all the patient's data through a dedicated Android application and a smart watch. The validation closes with the first ever demonstration that our system successfully works for the simultaneous monitoring of propofol and paracetamol in undiluted human serum by measuring the concentration trends of these two drugs in fluxing conditions over time.