Digital monitoring for integrated progression assessment of myalgic encephalomyelitis / chronic fatigue syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic condition with an unclear aetiology and a lack of diagnostic and progression biomarkers. Even with a multitude of studies investigating various biomedical aspects of the ME/CFS, the questions of recovery, reversibility, and progression remain obscure. At the same time recent studies point to biomarker patterns characteristic for severity classes, however due to the up-down behaviour and most of the markers not leaving normal range or a normal range not established, the diagnostic and predictive power has severe limitations and reduced prospect of the integration into the healthcare system. A digital assistant following the patients during various phases and integrated into functional areas of the healthcare system could fill the gap. The intended study will develop a digital integrated assistance solution based on digital phenotype, connecting digital biomarkers with the best possible serum biomarker set. The outcomes will be ready to integrate into symptom checker apps, and, via the proposal of the corresponding ontology, into generative artificial intelligence systems. An important enabler for the digital assistant in combination with digital health is the coaching to improve the patient's self-management skills.