Clinical eHealth最新文献

The aim is to diagnose COVID-19 earlier and to improve its treatment by applying medical technology, the “COVID-19 Intelligent Diagnosis and Treatment Assistant Program (nCapp)” based on the Internet of Things. Terminal eight functions can be implemented in real-time online communication with the “cloud” through the page selection key. According to existing data, questionnaires, and check results, the diagnosis is automatically generated as confirmed, suspected, or suspicious of 2019 novel coronavirus (2019-nCoV) infection. It classifies patients into mild, moderate, severe or critical pneumonia. nCapp can also establish an online COVID-19 real-time update database, and it updates the model of diagnosis in real time based on the latest real-world case data to improve diagnostic accuracy. Additionally, nCapp can guide treatment. Front-line physicians, experts, and managers are linked to perform consultation and prevention. nCapp also contributes to the long-term follow-up of patients with COVID-19. The ultimate goal is to enable different levels of COVID-19 diagnosis and treatment among different doctors from different hospitals to upgrade to the national and international through the intelligent assistance of the nCapp system. In this way, we can block disease transmission, avoid physician infection, and epidemic prevention and control as soon as possible.

Introduction

Visuospatial neglect (VSN) is common after stroke and can seriously hamper everyday life. One of the most commonly used and highly recommended rehabilitation methods is Visual Scanning Training (VST) which requires a lot of repetition which makes the treatment intensive and less appealing for the patient. The use of eHealth in healthcare can increase options regarding improved treatment in the areas of patient satisfaction, treatment efficacy and effectiveness. One solution to motivational issues might be Augmented Reality (AR), which offers new opportunities for increasing natural interactions with the environment during treatment of VSN.

Aim

The development of an AR-based scanning training program that will improve visuospatial search strategies in individuals affected by VSN.

Method

We used a Design Research approach, which is characterized by the iterative and incremental use of prototypes as research instruments together with a strong human-centered focus. Several design thinking methods were used to explore which design elements the AR game should comply with. Seven patients with visuospatial neglect, eight occupational therapists, a game design professional and seven other healthcare professionals participated in this research by means of co-creation based on their own perspectives.

Results

Fundamental design choices for an AR game for VSN patients included the factors extrinsic motivation, nostalgia, metaphors, direct feedback, independent movement, object contrast, search elements and competition. Designing for extrinsic motivation was considered the most important design choice, because due to less self-awareness the target group often does not fully understand and accept the consequences of VSN.

Conclusion

This study produced a prototype AR game for people with VSN after stroke. The AR game and method used illustrate the promising role of AR tools in geriatric rehabilitation, specifically those aimed at increasing the independence of patients with VSN after stroke.