Abstract

The current landscape of assistive robotics in digital healthcare faces significant challenges, particularly in ubiquitous environments. Existing systems need the necessary infrastructure to monitor and process data, hindering their effectiveness. Moreover, the arrangement and management of IoMT (Internet of Medical Things) data across various nodes present a new challenge, further complicating the deployment of assistive digital healthcare solutions. We propose a novel Assistive Robotics-Based Digital Healthcare System within a Ubiquitous IoMT Cloud network to address these challenges. This system supports various medical care applications, including digital wheelchair location tracking, artificial limbs, and remote surgical operations across different hospitals. Our contributions are as follows: We introduce the ARDTS (Assistive Robot Digital Healthcare Task Scheduling) algorithm to efficiently process data across multiple nodes; ensuring secure data handling based on the systems security protocols. We implement a convolutional neural network for data standardization, converting non-linear data into a linear form to predict relevant features accurately. We develop a socket-enabled cross-platform system to enhance interoperability for seamless data sharing and processing.