ABSTRACT
The growing and aging of the world population have driven the shortage of medical resources in recent years, especially during the COVID-19 pandemic. Fortunately, the rapid development of robotics and artificial intelligence technologies help to adapt to the challenges in the healthcare field. Among them, intelligent speech technology (IST) has served doctors and patients to improve the efficiency of medical behavior and alleviate the medical burden. However, problems like noise interference in complex medical scenarios and pronunciation differences between patients and healthy people hamper the broad application of IST in hospitals. In recent years, technologies such as machine learning have developed rapidly in intelligent speech recognition, which is expected to solve these problems. This paper first introduces IST's procedure and system architecture and analyzes its application in medical scenarios. Secondly, we review existing IST applications in smart hospitals in detail, including electronic medical documentation, disease diagnosis and evaluation, and human-medical equipment interaction. In addition, we elaborate on an application case of IST in the early recognition, diagnosis, rehabilitation training, evaluation, and daily care of stroke patients. Finally, we discuss IST's limitations, challenges, and future directions in the medical field. Furthermore, we propose a novel medical voice analysis system architecture that employs active hardware, active software, and human-computer interaction to realize intelligent and evolvable speech recognition. This comprehensive review and the proposed architecture offer directions for future studies on IST and its applications in smart hospitals.
Subject(s)
COVID-19 , Robotics , Humans , Artificial Intelligence , Speech , Pandemics , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19 TestingABSTRACT
Coreopsis tinctoria Nutt. was used to extract oleoresin through supercritical CO2 extraction technology. The extraction conditions were optimized using response surface methodology, and the chemical composition of C. tinctoria Nutt. oleoresin (CTO) was analyzed. Under the optimal conditions, the antioxidant activity of oleoresin was determined using 1,1-diphenyl-2-picrylhydrazyl (DPPHË) and 2,2'-azino-bis-(3-ethylbenzo-thiazoline-6-sulphonic acid)diammonium salt (ABTSË+) free radical scavenging assays. The optimal extraction conditions were a 27.5 MPa extraction pressure, a 45°C extraction temperature, and a 3 h extraction time. Under these extraction conditions, oleoresin yield was up to 3.163%. Compared to steam distillation extraction, the CTO extracted using supercritical CO2 had more abundant components. The EC50 of CTO for DPPHË and ABTSË+ free radical scavengers was 1.54 and 1.07 mg/mL, respectively.
