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REFLECTIONS
                                                                                                                   Hypertension
     Hypertension Global Newsletter #10 2026



     MEASUREMENT                                                                                                   Hypertension


     Cuffless devices for the measurement of blood pressure: A scientific statement
     from the American Heart Association.
     Cohen JB, et al. Hypertension. 2026 Mar;83(3):e00254.

     Conventional BP monitoring relies on arm cuff-based measurements, which have several limitations including patient
     discomfort, inconvenience, and infrequent readings. Over the past decade, a surge of cuffless BP devices has entered the
     market, promising continuous, passive monitoring and greater accessibility for users. These modern devices aim to overcome
     traditional barriers, potentially improving BP tracking for specialized groups like children, hospitalized patients, and under-
     resourced communities. However, the rapid growth of these technologies has outpaced standard accuracy testing, leaving
     clinicians and consumers uncertain about their safety and reliability.

     This AHA Scientific Statement provides a comprehensive review of the current literature on cuffless BP monitoring
     technologies. The authors synthesized existing data to assess the physical mechanisms behind various cuffless sensors,
     evaluated their theoretical clinical applications, and compared existing international validation standards (such as International
     Organization for Standardization [ISO] and Institute of Electrical and Electronics Engineers [IEEE] protocols) against the unique
     characteristics of cuffless devices. The primary objective of this review was to identify crucial technological and regulatory gaps
     that must be addressed before these devices can be safely integrated into clinical practice.

                                           Mechanism of cuffless BP measurement
































     Cuffless devices rely on machine learning applied to waveform features obtained from cardiac or pulsatility sensors, such as
     photoplethysmography (PPG) or tonometry. These devices do not measure absolute BP directly; instead, they measure pulse
     arrival time (PAT) or pulse transit time (PTT) to track changes in BP over time. Consequently, most cuffless devices require
     periodic user calibration with a traditional cuff-based device or demographic inputs to translate these waveforms into standard
     BP values (mmHg).

     A major concern is the high susceptibility of these devices to measurement errors due to human physiology. For instance,
     PPG sensors use light to measure blood volume oscillations, meaning their accuracy can be compromised by melanin
     levels, ambient temperatures, and obesity. Furthermore, measurements based on PAT or PTT can be heavily distorted by



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