A novel methodology for the synchronous collection and multimodal visualisation of continuous neurocardiovascular and neuromuscular physiological data in adults with long COVID

Reports suggest that adults with post-COVID-19 syndrome or long COVID may be affected by orthostatic intolerance syndromes, with autonomic nervous system dysfunction as a possible causal factor of neurocardiovascular instability (NCVI). Long COVID can also manifest as prolonged fatigue, which may be linked to neuromuscular function impairment (NMFI). The current clinical assessment for NCVI monitors neurocardiovascular performance upon the application of orthostatic stressors such as an active (i.e. self-induced) stand or a passive (tilt table) standing test. Lower limb muscle contractions may be important in orthostatic recovery via the skeletal muscle pump. In this study, adults with long COVID were assessed with a protocol that, in addition to the standard NCVI tests, incorporated simultaneous lower limb muscle monitoring for NMFI assessment. To accomplish such an investigation, a wide range of continuous non-invasive biomedical technologies were employed, including digital artery photoplethysmography for the extraction of cardiovascular signals, near-infrared spectroscopy for the extraction of regional tissue oxygenation in brain and muscle, and electromyography for assessment of timed muscle contractions in the lower limbs. With the novel technique described and exemplified in this paper, we were able to integrate signals from all instruments used in the assessment in a precisely synchronized fashion. We demonstrate that it is possible to visualize the interactions between all different physiological signals during the combined NCVI/NMFI assessment. Multiple counts of evidence were collected, which can capture the dynamics between skeletal muscle contractions and neurocardiovascular responses. The proposed multimodal data visualization can offer an overview of the functioning of the muscle pump during both supine rest and orthostatic recovery and can conduct comparison studies with signals from multiple participants at any given time in the assessment. This could help researchers and clinicians generate and test hypotheses based on the multimodal inspection of raw data, in long COVID and other clinical cohorts.