Description:
The University of Texas at Dallas presents a technique that addresses the inaccuracy of skin-mounted photoplethysmographic (PPG) biosensor measurements by separating the arterial and venous signals - enabling extraction of other medically-relevant features, including: respiration rate, heart rate, and SpO2. The effective removal of various motion artifacts (e.g. tissue effects, venous effects) permits high-quality signal acquisition that is independent of the site of measurement – a common issue for skin-mounted PPG biosensors.
PPG biosensors capture changes in optical density that are recorded as voltage/current signals, and these PPG signals are known to be sensitive to pulsatile blood flow and capture peripheral pulses. It has been clinically-reported that the venous signal has a significant effect on the shape of the PPG signal and the pulse oximeter oxygen saturation (SpO2) readings. Additional studies have demonstrated that placement of the biosensor has an impact on SpO2 readings, as the power of the venous signal differs in various sensor sites. At the site of measurement, the tissues will expand or contract during systole and diastole, respectively – periodically changing the optical path length.
Technical Summary:
The presented technology includes a model and formulation for arterial-venous separation (called instantaneous arterial venous mixing model or IAV) that can be solved mathematically. This includes an ambiguity resolution algorithm to identify arterial and venous signals when the blind source separation technique extracts two indistinguishable output signals.
A cardiac gating approach is used to find the best sampling time interval that the blood flow in veins has the minimum effect on extracting respiratory information, which accurately extracts the breathing rate without using other non-optical reference signals. Every major vessel in the human body has a flow pattern characteristic that is visible in the time domain signal, providing a time coherence and structure reflected in the second order statistics (e.g. autocorrelation) of the source signals and thus can be considered as a second order stationary signal in the time interval of measurement. This technique uses the second order statistics of the arterial and venous signals to separate them. Unique time domain characteristics of arterial and venous components are used to automatically identify the individual components after separation.
Value Proposition:
This technology enables wearable PPG biosensor systems to provide accurate, real-time, non-invasive acquisition of heart rate, oxygen saturation, and respiratory-related information without additional non-optical sensors. The technology provides an effective model for IAV to provide high-quality signal acquisition that is independent of the site of measurement.
Applications:
- Computational model for arterial-venous separation (IAV): to improve functionality of existing PPG biosensors
- Non-invasive monitoring devices & wearables
- Real-time monitoring: of arterial signal and central venous pressure in anesthesia, preoperative and postoperative care
- Diagnostic applications: Hypoxemia, blood pressure, sleep apnea, heart abnormalities, lung function test, hemodynamic monitoring, venous capacity, fluid responsiveness, seizure alerts, wound healing
- Continuous tissue perfusion monitoring: for implanted organs after surgery
Key Benefits:
- Accurate – Optimized, adaptive removal of motion artifact prevents the deterioration of signal integrity for PPG biosensors, enabling their use wherever motion is present
- Robust – Provides adaptive removal of tissue and venous effect (noise) to produce reliable computation of SpO2 and heart rate; demonstrates more reliable SpO2 with higher accuracy and correlation than commercial solution (DST method)
- Tunable – May be adjusted, based on features meant to be extracted from enhanced output signals, to further reduce effect of rhythm irregularities on reference noise
Publication:
Yousefi, Rasoul, et al., “Separating Arterial and Venous-Related Components of Photoplethysmographic Signals for Accurate Extraction of Oxygen Saturation and Respiratory Rate,” IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 3, pp. 848-857, May 2015, doi: 10.1109/JBHI.2014.2334697.
IP Status: US patent 10,206,612 issued.
Licensing Opportunity: This technology is available for exclusive or non-exclusive licensing.
ID Number: MP-14035
Contact: otc@utdallas.edu