Deep Mobile Linguistic Therapy for Patients with ASD.

Autistic spectrum disorder (ASD) is one of the most complex groups of neurobehavioral and developmental conditions. The reason is the presence of three different impaired domains, such as social interaction, communication, and restricted repetitive behaviors. Some children with ASD may not be able to communicate using language or speech. Many experts propose that continued therapy in the form of software training in this area might help to bring improvement. In this work, we propose a design of software speech therapy system for ASD. We combined different devices, technologies, and features with techniques of home rehabilitation. We used TensorFlow for Image Classification, ArKit for Text-to-Speech, Cloud Database, Binary Search, Natural Language Processing, Dataset of Sentences, and Dataset of Images with two different Operating Systems designed for Smart Mobile devices in daily life. This software is a combination of different Deep Learning Technologies and makes Human-Computer Interaction Therapy very easy to conduct. In addition, we explain the way these were connected and put to work together. Additionally, we explain in detail the architecture of software and how each component works together as an integrated Therapy System. Finally, it allows the patient with ASD to perform the therapy anytime and everywhere, as well as transmitting information to a medical specialist.

An intelligent knowledge-based and customizable home care system framework with ubiquitous patient monitoring and alerting techniques.

This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

[In vivo identification of radix panacis quinquefolii by spectral imaging technology].

Radix Panacis quinquefolii pieces coming from different drug stores were tested by crystal liquid spectral imaging instrument, and a new method for quality control was presented. The spectral resolution is 5 nm, the spectral range is from 405 to 680 nm, and the spatial resolution is 50 lp x mm(-1). The characteristic spectrum from spectral cube was used to construct the fingerprint of Radix Panacis quinquefolii, and the fingerprint was analyzed by principal method to identify the counterfeit and to evaluate the quality. The result is fully consistent with biological character and chemical analysis result. So the technology is suitable for fingerprint construction and quality evaluation of traditional Chinese medicine. The whole testing process is noninvasive, fast and convenient.