Feedback Control of Medication Delivery Device Using Machine Learning-Based Control Co-Design

Although the opioid crisis is a problem worldwide, recent emerging technology has the potential of curtailing the epidemic. By administering micro-doses of medication as needed, a feedback-driven medicine pump could lessen the highs and lows associated with the formation of an addiction. The focus of this study was to develop a feedback control loop for this pump that optimizes drug concentration in the bloodstream based on set criteria. In the process of optimization of the system, the mathematical model representing the system was analyzed to find an open loop transfer function. Using this function, a PID tuner was applied to set feedback control. Both machine learning (ML) and deep learning (DL) techniques are explored to act as a classifier that aids the pump in administering doses. The setpoint concentration of medication in the patient’s bloodstream was calculated to be 7.55 mg/ml this setpoint was the basis for steady state concentration of the transfer function. When a PID tuner was added to the feedback system, the plot was optimized to satisfy the design criteria of a rise time less than 25-minutes and no more than a 5% overshoot of the setpoint concentration. Naïve Bayesian (NB), Tree and support-vector machines (SVM) classifiers achieved the best classification accuracy of 100%. A DL network was successfully developed to predict patient class. This work is the theoretical basis for developing a feedback-driven medicine pump and an algorithm that can classify patients based on their body’s metabolism that will aid the doctor in formatting the medicine pump so that the patient is receiving the proper amount of medication.

Do drones have a realistic place in a pandemic fight for delivering medical supplies in healthcare systems problems?

The advancement of Unmanned Aerial Vehicle(UAV) technology in terms of industrial processes and communication and networking technologies has led to an increase in their use in civil, business, and social applications. Global rules in most countries had previously limited the use of drones to military applications due to their deployment in the open air, drones are likely to be lost, destroyed, or physically hijacked. However, more recently, the presence of COVID-19 has forced the world to present new implementing measures which will also widen the use of drones in civil and commercial and social applications, especially now in the delivery of medicines for medical home care. In the period of required public isolation as a consequence of the SARS-COV-2 pandemic, this knowledge has become one of the principal partners in the fight against the coronavirus. This paper offers a summary of the medical drone manufacturing, with a specific emphasis on its approval by the pharmaceutical sector to solve logistical problems in healthcare during times of sensitive need. We also discuss the numerous challenges to be met in the integration of drones to save our lives and suggest future research directions. The question that arises for this problem, how to optimize delivery medical supplies times in-home health care made up of drones? We conducted a synthesis literature review devoted to the use of UAVs in healthcare with their different aspects. A total of different research made are given to describe the role of UAV in Home healthcare with the presence of SARS-COV-2. We conclude that the drones will be able to optimize the way of eliminating contamination with a very high percentage(through the reduction of human contact) with the increase of the flexibility of the flight(reaching the less accessible regions every hour of the day).