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Osteoarthritis (OA) is a degenerative disease frequently encountered clinically, which can lead to loss of joint function in the late stage and is associated with a high disability rate. There is still no available cure for OA. Therefore, early diagnosis and precise treatment are the key to improving the therapeutic effect. Being an interdisciplinary research focus, artificial intelligence (AI) has been increasingly used in the diagnosis and treatment of OA recently, as it improves the diagnostic accuracy as well as clinical treatment and prognosis of OA. We summarized and systematically reviewed the literature on the application of AI in the diagnosis and treatment of OA, in which the application potential in assisting imaging diagnosis, surgical treatment, progression prediction and postoperative rehabilitation of OA was indicated, yet some limitations including non-standardized data collection and unstable algorithmic system were also identified. In the future, it is expected to establish a standardized clinical sample database and continuously optimize the algorithmic model, so as to better incorporate AI technologies in the diagnosis and treatment process of OA.

Chronic diseases seriously affect the health of residents in China and increase the burden on families and society. In China, the mortality rate caused by chronic diseases accounts for about 86% of the mortality rate of all related diseases, so as that the prevention and treatment situation is in a difficult situation. How to achieve real-time health monitoring and establish convenient and fast medical access to improve the quality of life in patients with chronic disease who live at home for a long time and have difficulty moving is the focus of chronic disease rehabilitation. Studies have shown that early identifications of changes in cardiopulmonary function in patients with chronic diseases is one of the ways for timely and effective rehabilitation intervention. In view of the development status of "Internet + medicine" and the practical needs of patients with chronic diseases, through reviewing and sorting out the relevant literature and materials on home-based rehabilitation of chronic diseases, the research trends of home-based rehabilitation of chronic diseases at home and abroad as well as the advantages and disadvantages of the current management modes were analyzed and summarized. On this footing, a closed-loop and full-cycle intelligent rehabilitation diagnosis and treatment platform for real-time monitoring, health guidance, online training and on-site diagnosis of health conditions of patients with chronic diseases at home could be constructed based on the monitoring of their cardiopulmonary function changes and supported by the network information center of tertiary hospitals. The diagnosis and treatment platform is a home-based intelligent and comprehensive rehabilitation comprehensive service platform which integrates service, management and operation and uses wearable devices, a network platform and mobile phone applications as media and utilizes variety of internet resources. By synchronizing data of the computer or mobile terminal platform, doctors and family members can grasp that the life, health, safety and other conditions of patients in time. A comprehensive rehabilitation service system for patients with chronic diseases featuring the interaction of doctors in tertiary hospitals, community doctors, patients and their families, including in-home, online and on-site services, could be constructed, and a bridge should be built between tertiary hospitals, community healthcare centers, home-based patients and medical insurance institutions to dynamically manage the health conditions of patients with chronic diseases. At the same time, the concept of traditional Chinese medicine (TCM) could be integrated to construct a new intelligent management model for home-based rehabilitation of chronic diseases, which is supposed to be an integration of TCM and Western medicine and a multidisciplinary approach, so as to provide decision-making reference for health management of chronic diseases in China.

The use of mobile internet applications (APPs) has become an indispensable part of daily life and has been applied in clinical rehabilitation. APPs assist rehabilitation to expand the rehabilitation scene. It makes rehabilitation assessment more simple and convenient, and makes trainings more intelligent and diversified. APPs-assisted rehabilitation has been applied in rehabilitation assessment, rehabilitation training and improvement of social activity participation. This review summarizes the application of APPs in rehabilitation field at home and abroad in order to maximize efficiency of the combination of APPs and rehabilitation training, and provide the evidence basis for further development of mobile internet rehabilitation services in the future. In rehabilitation assessment, APPs can be used to assist in the assessment of joint range of motion, balance and gait, speech and cognition, and psychological function. In rehabilitation training, APPs can be used to assist upper limb function training, chronic pain rehabilitation training, balance and gait training, cognitive psychological function training and other functional training. In the improvement of patients' participation in social activities, APPs can be used to assist activities of daily living, improve participation in work and study, and facilitate recreational activities. The application of APPs in rehabilitation can simplify the process of rehabilitation assessment and treatment, expand the scene of rehabilitation training, make the ways of rehabilitation more intelligent and diversified, improve the motivation and compliance of patients during training, and promote the rapid development of rehabilitation treatment. However, there are still many difficulties in the application of APPs in rehabilitation profession, such as lack of universal applicability, limited functions, and unstandardized software design and use. In the future, it is necessary to conduct research on the combination of internet mobile APPs and rehabilitation, to find and develop the comprehensive APPs suitable for people with different functional disabilities, in order to maximize efficiency of the APPs in assisting rehabilitation.

A water ecosystem is a dynamic balance system with a certain structure and function, which is composed of aquatic organism community and water environment interaction and mutual restriction through material circulation and energy flow. Living in an urban environment for a long time can make people suffer from ‘urban disease’, which can seriously affect their physical and mental health. Forest rehabilitation is a new form of outdoor activity in many countries, which has been gradually promoted by society in recent years. Many studies have confirmed that forest environments have positive impacts on the human body and mind, so forest healthcare and treatment are crucial to the prevention and treatment of ‘urban diseases’. This study is based on artificial intelligence (AI) to carry out the planning and design of the forest health base. According to sensory design theories including air factor, somatosensory factor, and audiovisual factor, this paper proposed different landscape configuration methods to enhance health and well-being. Finally, it was found that in the planning and design of the health base, when the human comfort index is greater than 85 and less than 20, it is very uncomfortable for the human body.

In order to solve the shortcomings of the current clinical scale assessment for stroke patients, such as excessive time consumption, strong subjectivity, and coarse grading, this study designed an intelligent rehabilitation assessment system based on wearable devices and a machine learning algorithm and explored the effectiveness of the system in assessing patients' rehabilitation outcomes. The accuracy and effectiveness of the intelligent rehabilitation assessment system were verified by comparing the consistency and time between the designed intelligent rehabilitation assessment system scores and the clinical Fugl–Meyer assessment (FMA) scores. A total of 120 stroke patients from two hospitals participated as volunteers in the trial study, and statistical analyses of the two assessment methods were performed. The results showed that the R2 of the total score regression analysis for both methods was 0.9667, 95% CI 0.92–0.98, p < 0.001, and the mean of the deviation was 0.30, 95% CI 0.57–1.17. The percentages of deviations/relative deviations falling within the mean ± 1.96 SD of deviations/relative deviations were 92.50% and 95.83%, respectively. The mean time for system assessment was 35.00% less than that for clinician assessment, p < 0.05. Therefore, wearable intelligent machine learning rehabilitation assessment has a strong and significant correlation with clinician assessment, and the time spent is significantly reduced, which provides an accurate, objective, and effective solution for clinical rehabilitation assessment and remote rehabilitation without the presence of physicians. [ABSTRACT FROM AUTHOR]

To achieve the goal of building a well-off society in an all-round way, attention should be paid to the survival needs of special groups. Rehabilitation assistive technology and equipment can effectively improve the living conditions of disabled groups. In recent years, assistive devices have been included in China's career development plan, and its development is increasingly perfect. Nowadays, new vitality has been introduced to rehabilitation assistance because of the large-scale application of artificial intelligence technology. In this paper, the existing achievements of rehabilitation assistive technology are summarized. The advancement and practicability of introducing artificial intelligence and 5G technology into rehabilitation assistive technology are analyzed and discussed in detail. At the same time, the existing problems of rehabilitation assistive technology under the current technical background are described and the feasible solutions are proposed. Finally, the broad prospects of intelligent rehabilitation assistive technology in 5G era are prospected. [ABSTRACT FROM AUTHOR]

With the development of Internet of things, the healthcare service is getting intelligent and wearable devices have become the focus of healthcare. In the field of healthcare, wearable devices are mainly applied in health monitoring, motion sensing, big health analysis, and so on. All these applications make wearable devices a good tool to achieve the ultimate goal of rehabilitation medicine, which is function recovery and health promotion, thus wearable devices are meant to play an important role in rehabilitation medicine. The users will have a high demand for the comforts and designs of the wearable devices because the wearable devices need to be worn for a long period in the skin; however, traditional devices are unable to satisfy the demand so that novel materials are needed. Nowadays, the wearable devices sold in the market such as smart watches and smart glasses are made of rigid materials, which have poor ductility and high density, thus they are difficult to satisfy the demand of users for comforts and convenience. Flexible materials are novel materials with good portability, high ductility, and could keep stable physicochemical properties even if in the process of extension. The wearable devices made of flexible materials inherit the advantages of flexible materials so that they might make up for the shortcomings of traditional wearable devices and then be widely applied in the field of rehabilitation medicine. As is shown in the domestic and foreign literature, flexible wearable devices have the potential for clinical application. Compared with traditional devices, flexible wearable devices not only improve user experience but also offer more powerful functions to meet a variety of clinical demands. In this review, we briefly introduce the principle and classification of flexible wearable devices and review the research progress of the application of flexible wearable devices in the field of rehabilitation medicine from six aspects: health monitoring, motion monitoring, swallow-speech monitoring, home rehabilitation, fall warning, and intelligent rehabilitation. Finally, we summarize current challenges and recent development trends of flexible wearable devices to provide a theoretical basis for future clinical applications