Abstract
The problem of providing rehabilitation assistance to the population has been repeatedly discussed in the global community. One of the important events in recent years was the meeting of participants in Rehabilitation 2030: Call to Action, where the problem of increasing dissatisfaction in rehabilitation services worldwide, especially in low- and middle-income countries, was discussed. The upward trend in the need for rehabilitation activities will increase in line with global trends in demographic change associated with the aging population and an increase in the number of people living with sequellae of diseases and injuries. The prevalence of health conditions associated with severe functional limitations, of which many are caused by non-communicable diseases, increased by 9.9% and affected almost 14 million people from 2006 to 2016 in the World Health Organization European Region. Devices for monitoring vital signs can become one of the potentially important components of effective rehabilitation with an increased number of technical means of rehabilitation. The constant transfer of these parameters to the cloud storage, followed by machine learning algorithm processing, will determine the prescribed drug therapy efficiency and determine the need for timely hospitalization for a medical organization. This study aimed to assess the needs of patients with a chronic consciousness impairment, and relatives caring for them, using the possibilities of remote monitoring. The study showed that the use of hospital-replacing outpatient equipment that records the vital signs of patients opens up new opportunities for consolidating the information into a big data archive to assess the treatment efficiency and the characteristics of patient rehabilitation with the implementation of the most optimal measures to influence the rehabilitation process approach.
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