Technologies to Diagnose, Monitor, and Treat Long-COVID

Call for Papers: Special Issue on Technologies to Diagnose, Monitor, and Treat Long-COVID

Call for Papers: Special Issue on Technologies to Diagnose, Monitor, and Treat Long-COVID 789 444 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)

The COVID-19 pandemic has had a profound impact on healthcare, and technologies for healthcare. A rapid technological response for COVID-19 was mounted in 2020 to deliver modelling, tracking, and remote monitoring and provision of healthcare services. It is now widely accepted that the COVID-19 pandemic is being followed by a Long-COVID pandemic. Estimates indicate that 1-in-20 people have experienced persistent COVID-19 symptoms extending beyond 3 months after the initial infection, with some estimates substantially higher than this. A wide range of different symptoms are commonly reported, including fatigue, shortness of breath, and heart palpitations. These can have a debilitating impact on the quality of life for those affected and their care network with sleep disturbances, depression, and anxiety also widely reported. As a result, there is an urgent need for a technological response to Long-COVID.

Technology is contributing to the management of Long-COVID in many ways. Wearable devices are allowing longitudinal and out-of-the-clinic collection of physiological parameters to help inform aetiologies, causative/risk factors and to monitor changes in physical health. Data science and machine learning is allowing new insights to be gained from this data, providing insights to both clinicians and to service users. There is also the potential for technology-based interventions. For example ‘bioelectronic medicine’, where the nervous system is stimulated electrically for therapeutic effect, is emerging as one treatment route. The combination of these technologies can offer a compliment to pharmacological, behavioural, and other interventions, and allows ‘closed loop’ personalisation as support, rehabilitation, and treatment can be adjusted based upon measured data.

This Special Issue is being created to collect together the state-of-the-art in technologies for Long-COVID. The aim is to be both wide-ranging, covering technologies spanning diagnosing, monitoring, and treating, and inter-disciplinary, bringing together technologists with clinicians and user stakeholders to understand the field as it stands today and future needs. It will have a positive impact on the domain knowledge and practices for improving people’s quality of life.

Potential topics include, but are not limited to:

  • Wearable device and bio-sensor hardware or monitoring physiological parameters, including advances in stretchable/flexible electronics.
  • Sensor technology for Long-COVID relevant measurands.
  • Machine learning and data analytics for sensor and other data.
  • Digital twins and computational modelling approaches for predicting severity, and symptom time courses.
  • Technological intervention routes, such as bio-feedback and electrical stimulation.
  • ‘Closed loop’ interventions, combining sensing and actuation to provide personalised simulation (and similar).
  • Technology driven support, such as smart homes, peer support via social media mining.
  • Rehabilitation applications for Long-COVID.
  • Patient/public involvement and clinical views for co-design of technologies, including statements of unmet needs.

Guest Editor: Alex Casson, University of Manchester
Email: alex.casson@manchester.ac.uk 

Submission Information:
Deadline for paper submission: 20 November 2022