Intelligent Personal Health Monitoring and Guidance Using Long Short-Term Memory

Rapid improvements in information technology have made everything in this world contemporary. The mobile phone plays a vital role in the day to day activities. Many mobile applications are developed by using deep learning models to give health guidance to people. We proposed intelligent personal health monitoring and guidance (IPHMG) using long short-term memory to assess the users’ overall health status to solve the mobile application performance problem. The main objective of the research work is to minimize the delay time of the user’s request and improve the accuracy of health predictions. The proposed system calculates scores using the IPHMG score model to find the health conditions of the users. IPHMG score model uses different time-series data to calculate scores such as environment data, body signal data, parent report data, emotion, and health report. Additionally, an Android application is a module that is designed for mobile users to feed their health data and check their health status. The proposed system was implemented. Results show that the proposed method provides better uploading time, processing time, and the user downloading time than simple RNN and ANN methods.

Personal Health Monitoring with Mobile Application Based on Blockchain Technologies

Personal health monitoring is especially necessary in a pandemic of COVID19 and based on objective and subjective data. Modern medicine uses numerous diagnostic devices, many of which are for personal health monitoring. Applications for mobile phones are becoming more widespread, they make a possibility constantly monitor vital signs for a person. However, the consolidation into a single personalized database of information on daily mobile monitoring and examination results from various doctors in various medical organizations not yet carried out. Proposed to build a blockchain from this data and results of data analysis add subjective sensations and indicators to it, which clarified during the conversation with the doctor and not always fully and correctly transmitted by the patient. Using an integrated approach to personal health monitoring, building a blockchain from official data and personal objective and subjective indicators makes it possible to identify at the early stages of the disease, to have a complete and reliable picture of the state of health.

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One-step 3D Printed Intelligent Silk Fibroin Artificial Skin with Built-In Electronic and Microfluidics

Rapid fabrication of artificial skin patches with multiple functions has attracted great attention in various research fields such as personal health monitoring, tissue engineering and robotics. The intertwined-network structures (blood...