A Pilot Study Using AI Algorithms and PPG Technology for the Detection of Venous Diseases

This clinical research aims to evaluate the effectiveness of using Photoplethysmography (PPG) signals combined with Artificial Intelligence (AI) algorithms, for the precise classification and diagnosis of Venous Diseases of the lower limb. This study invites a group of participants who currently undergoing investigations for venous disease at The Whiteley Clinic (hereinafter referred to as TWC). The Participants will be classified into control (healthy individuals with no significant venous disease) and chronic venous disease (CVD) (diagnosed with proven venous disease) groups. Prospective participants who express an interest in being included in the study will be given a patient information sheet and will undergo a briefing of the pilot study. If they consent and sign the relevant consent forms, the participants will perform a series of standardized exercises under the supervision of a consultant vascular surgeon. Throughout the exercises, a data acquisition device attached to the ankle records the PPG signals, capturing the changes in blood volume due to the reflected PPG signals from the red blood cells during the movement. Thus, once the data is collected and recorded, this allows for the analysis of the data of the control group and CVD group against each other. During the analysis of the two groups' PPG signals, the objective lies within the capability to detect subtle nuances in the patterns of the PPG signals during the performed movements using AI algorithms. The AI algorithms will distinguish patterns or features indicating the presence or absence of venous disease. This study seeks to contribute valuable insights into enhancing the diagnosis of venous disease using PPG and AI algorithms, paving novel approaches to Venous healthcare.