Clinical Correlation of Smart IoT-Enabled Point-Of-Care wIT Jacket with Plethysmograph

Background: Conventional pulmonary function tests, often considered the gold standard, are time-consuming, typically yield only graphical or numerical data, and requiring significant effort from patients and often require clinical setups. Purpose: To develop an Industry 4.0 ready IoT-enabled, AI-assisted, point-of-care impedance tomography based jacket featuring wireless connectivity (wIT) for dynamic monitoring the human lung functions via an android smartphone interface and clinically evaluate its diagnostic performance against standard PFT modalities. Methods: A total of forty-six individuals (23 control and 23 patients) were included in this study, registered under the clinical trial registry of India, and two involved IHEC Committees. Standard pulmonary physiological parameters, including primary lung volumes (Functional Residual Capacity, Inspiratory Capacity, Total Lung Capacity, and Residual Volume), as well as secondary volumes (Expiratory Reserve Volume and Vital Capacity), were obtained from Plethysmography, Spirometry, and the wIT jacket. The wIT measurements were recorded simultaneously with these PFT, and results obtained by AI trained model were statistically compared to assess correlation and diagnostic performance. Results: The wIT system achieved a sensitivity of 78%, a specificity of 86%, a positive predictive value of 86%, and a negative predictive value of 80%, as derived from the confusion matrix. In comparison, the corresponding values for spirometry were 23%, 90%, 22%, and 91%, and for plethysmography were 95.2%, 81.7%, 66.4%, and 97.8%. Matthew’s correlation coefficient of 0.6547 further confirmed the classification reliability of the wIT jacket. Conclusion: The developed wIT system exhibited the ability to reliably classify subjects as healthy or not healthy. It established agreement with body plethysmography measurements. A frequency-based imaging biomarker for wIT is developed. The study demonstrated devices’ potential that may be used as a non-invasive: (a) point-of-care device in non-clinical environment and/or (b) add-on with existing gold standard clinical setups, for pulmonary assessment and long-term respiratory monitoring.