Deep prescription understanding and low-cost medication dispensing and management for elderly care

Abstract

Effective medication management is crucial for improving treatment outcomes, particularly among the elderly and those with chronic conditions. To mitigate the risks associated with poor medication management, this paper proposes an artificial intelligence-based medical dispenser system. The proposed system addresses the limitations of existing pill dispenser systems through medical paper digitization and an adaptable pick-and-drop dispensing system capable of accommodating pills with different shapes, textures, and sizes. Our methodology initially involved developing a computer vision algorithm to identify key details in medical prescriptions, such as medication dosage and frequency. The image data was then converted into textual data frames for further analysis using a large language model. Subsequently, we designed a suction-based pill dispensing unit with a linear actuator and an air pump motor, picking up pills from compartments on a tray controlled by a stepper motor. Our proposed digitization algorithm achieved an average intersection over the union score of 0.952 in detecting regions of interest in medical prescriptions with optical character recognition yielding average word and character error rates of 0.039 and 0.025, respectively. The employment of OpenAI’s language model demonstrates efficacy in error parsong, resolving 52.63 % of the optical character recognition errors. The pill dispensing mechanism effectively extracts pills of different sizes and shapes, and the rotating tray mechanism aligns in the respective dispensing and collection locations precisely with a success rate of 100 % in placing the containers in the required locations. Overall, the results are promising, suggesting that the proposed system may pave the way for more generalized, intelligent medication management solutions.

Keywords: Medication management, Medication adherence, Pill dispenserm, Health, Digitization, Automation, Artificial intelligence