Design of a Diagnostic System for Patient Recovery Based on Deep Learning Image Processing: For the Prevention of Bedsores and Leg Rehabilitation

Abstract

Worldwide COVID-19 infections have caused various problems throughout different countries. In the case of Korea, problems related to the demand for medical care concerning wards and doctors are serious, which were already slowly worsening problems in Korea before the COVID-19 pandemic. In this paper, we propose the direction of developing a system by combining artificial intelligence technology with limited areas that do not require high expertise in the rehabilitation medical field that should be improved in Korea through the prevention of bedsores and leg rehabilitation methods. Regarding the introduction of artificial intelligence technology, medical and related laws and regulations were quite limited, so the actual needs of domestic rehabilitation doctors and advice on the hospital environment were obtained. Satisfaction with the test content was high, the degree of provision of important medical data was 95%, and the angular error was within 5 degrees and suitable for recovery confirmation.

Implement Improved Process Design Using a Lightweight Deep Learning Model to Reduce Hardware Computational Load in Instance Segmentation: Using Apple Dataset

“…These methods result in better utilization than using a single existing model, but the proposed method can gain the convenience of not having to change the existing model and improve the use of artificial intelligence models limited by performance or specification in some hardware. In fact, before conducting this study, there was a problem that the joints were tracked very unstable when deep learning was used to track the joints of patients in hospitals [40], [41]. Here, in order to solve the problem that the measured value of the joint position and angle has a large error, it could be improved simply and quickly by controlling the input values without using additional neural network changes or deep learning.…”

Review and Analysis of Patients’ Body Language From an Artificial Intelligence Perspective

“…The results show no significant differences between a set of specified parameters calculated using the standard and markerless approaches. Study [152] proposes a system that integrates artificial intelligence technology with certain sectors of the Korean medical area of rehabilitation. The goal is to stop bedsores in patients lying down following surgery by turning them over and observing their range of motion in the arms and legs.…”