Piloting the Clinical Value of Wearable Cardiorespiratory Monitoring for People with Cystic Fibrosis

Abstract

Introduction. Cystic Fibrosis (CF) is a disease without a primary cure that requires lifelong care and is characterized by pulmonary exacerbations (PEx). Wearable devices could provide a way for long-term monitoring of disease progression and early signs of PEx to intervene as early as possible, thereby improving long-term outcomes. Methods. In-hospital feasibility study (n = 26) to 1) assess the ability of Byteflies Sensor Dot to collect relevant cardiorespiratory data in people with CF and its compatibility with clinical workflows, 2) identify candidate digital biomarkers, and 3) collect user feedback from patients and healthcare providers. Results. Collected sample-level biopotential, bioimpedance and actigraphy data were of high quality. Sensor Dot heart rate (HR) correlated with hospital HR, whereas respiratory rate (RR) did not. HR and RR were associated with CF severity, and HR and coughing with PEx. Willingness to use the device was very high with CF patients and study coordinators considered the device easy-to-use. Conclusion. Determining if a wearable is fit-for-purpose is a long and multidisciplinary process that requires involvement from all stakeholders as early as possible in the development process. Our pilot identified interesting correlations between cardiorespiratory parameters as measured by the wearable, and CF severity and PEx. Together with the usability data, this will inform the next steps in the clinical development process.

Multimodal biometric monitoring technologies drive the development of clinical assessments in the home environment

“…To ensure reliable data capture under a broad set of conditions, sensor redundancy is important. Two approaches exist: 1) redundancy can be achieved by using more than one sensor modality to sample a physiologic measure, e.g., measuring respiratory rate via a bioimpedance and accelerometer sensor simultaneously [27]; and 2) the same sensor modality can be measured more than once in the same BioMeT, e.g., measure two leads of ECG instead of one.…”