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1. An Accurate Non-accelerometer-based PPG Motion Artifact Removal Technique using CycleGAN

   https://doi.org/10.1145/3563949  

   Zargari, Amir Hosein; Aqajari, Seyed Amir; Khodabandeh, Hadi; Rahmani, Amir M.; Kurdahi, Fadi (January 2022, ACM Transactions on Computing for Healthcare)

   A photoplethysmography (PPG) is an uncomplicated and inexpensive optical technique widely used in the healthcare domain to extract valuable health-related information, e.g., heart rate variability, blood pressure, and respiration rate. PPG signals can easily be collected continuously and remotely using portable wearable devices. However, these measuring devices are vulnerable to motion artifacts caused by daily life activities. The most common ways to eliminate motion artifacts use extra accelerometer sensors, which suffer from two limitations: i) high power consumption and ii) the need to integrate an accelerometer sensor in a wearable device (which is not required in certain wearables). This paper proposes a low-power non-accelerometer-based PPG motion artifacts removal method outperforming the accuracy of the existing methods. We use Cycle Generative Adversarial Network to reconstruct clean PPG signals from noisy PPG signals. Our novel machine-learning-based technique achieves 9.5 times improvement in motion artifact removal compared to the state-of-the-art without using extra sensors such as an accelerometer, which leads to 45% improvement in energy efficiency. 

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2. Methods for Extraction of Respiration Rate From Wrist-Worn PPG Sensor and Doppler Radar: (Invited Paper)

   https://doi.org/10.23919/APMC55665.2022.9999902  

   Stankaitis, Grant; Boric-Lubecke, Olga (November 2022, 2022 Asia-Pacific Microwave Conference (APMC))

   Respiration rate and heart rate variability (HRV) due to respiratory sinus arrhythmia (RSA) are physiological measurements that can offer useful diagnostics for a variety of medical conditions. This study uses a wrist-worn wearable development platform from Maxim Integrated and Doppler radar sensor developed by Adnoviv, Inc. to non-invasively measure these physiological signals. Six datasets are recorded comprising of five different individuals in varying physical environments breathing at different respiration rates. First, respiration rates are extracted from photoplethysmography (PPG) and accelerometer data and compared to Doppler radar. The average maximum and minimum difference between Doppler radar extracted RR and PPG, HRV RSA, and accelerometer extracted RR is 0.342 b/m and 0.171 b/m, respectively. Then, waveforms for Doppler radar, PPG, and HRV RSA signals are plotted in time domain and an analysis discusses the physical phenomena associated with the phase alignment of the signals. 

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3. Near-Infrared Imaging Photoplethysmography During Driving

   https://doi.org/10.1109/TITS.2020.3038317  

   Nowara, Ewa M.; Marks, Tim K.; Mansour, Hassan; Veeraraghavan, Ashok (December 2020, IEEE Transactions on Intelligent Transportation Systems)

   null (Ed.)

   Imaging photoplethysmography (iPPG) could greatly improve driver safety systems by enabling capabilities ranging from identifying driver fatigue to unobtrusive early heart failure detection. Unfortunately, the driving context poses unique challenges to iPPG, including illumination and motion. First, drastic illumination variations present during driving can overwhelm the small intensity-based iPPG signals. Second, significant driver head motion during driving, as well as camera motion (e.g., vibration) make it challenging to recover iPPG signals. To address these two challenges, we present two innovations. First, we demonstrate that we can reduce most outside light variations using narrow-band near-infrared (NIR) video recordings and obtain reliable heart rate estimates. Second, we present a novel optimization algorithm, which we call AutoSparsePPG, that leverages the quasi-periodicity of iPPG signals and achieves better performance than the state-of-the-art methods. In addition, we release the first publicly available driving dataset that contains both NIR and RGB video recordings of a passenger's face with simultaneous ground truth pulse oximeter recordings. 

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4. RobustPPG: camera-based robust heart rate estimation using motion cancellation

   https://doi.org/10.1364/BOE.465143  

   Maity, Akash Kumar; Wang, Jian; Sabharwal, Ashutosh; Nayar, Shree K. (January 2022, Biomedical Optics Express)

   Camera-based heart rate measurement is becoming an attractive option as a non-contact modality for continuous remote health and engagement monitoring. However, reliable heart rate extraction from camera-based measurement is challenging in realistic scenarios, especially when the subject is moving. In this work, we develop a motion-robust algorithm, labeled RobustPPG, for extracting photoplethysmography signals (PPG) from face video and estimating the heart rate. Our key innovation is to explicitly model and generate motion distortions due to the movements of the person’s face. We use inverse rendering to obtain the 3D shape and albedo of the face and environment lighting from video frames and then render the human face for each frame. The rendered face is similar to the original face but does not contain the heart rate signal; facial movements alone cause pixel intensity variation in the generated video frames. Finally, we use the generated motion distortion to filter the motion-induced measurements. We demonstrate that our approach performs better than the state-of-the-art methods in extracting a clean blood volume signal with over 2 dB signal quality improvement and 30% improvement in RMSE of estimated heart rate in intense motion scenarios. 

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5. A new principle of pulse detection based on terahertz wave plethysmography

   https://doi.org/10.1038/s41598-022-09801-w  

   Rong, Yu; Theofanopoulos, Panagiotis C.; Trichopoulos, Georgios C.; Bliss, Daniel W. (December 2022, Scientific Reports)

   Abstract This study presents findings in the terahertz (THz) frequency spectrum for non-contact cardiac sensing applications. Cardiac pulse information is simultaneously extracted using THz waves based on the established principles in electronics and optics. The first fundamental principle is micro-Doppler motion effect. This motion based method, primarily using coherent phase information from the radar receiver, has been widely exploited in microwave frequency bands and has recently found popularity in millimeter waves (mmWave) for breathe rate and heart rate detection. The second fundamental principle is reflectance based optical measurement using infrared or visible light. The variation in the light reflection is proportional to the volumetric change of the heart, often referred as photoplethysmography (PPG). Herein, we introduce the concept of terahertz-wave-plethysmography (TPG), which detects blood volume changes in the upper dermis tissue layer by measuring the reflectance of THz waves, similar to the existing remote PPG (rPPG) principle. The TPG principle is justified by scientific deduction, electromagnetic wave simulations and carefully designed experimental demonstrations. Additionally, pulse measurements from various peripheral body parts of interest (BOI), palm, inner elbow, temple, fingertip and forehead, are demonstrated using a wideband THz sensing system developed by the Terahertz Electronics Lab at Arizona State University, Tempe. Among the BOIs under test, it is found that the measurements from forehead BOI gives the best accuracy with mean heart rate (HR) estimation error 1.51 beats per minute (BPM) and standard deviation 1.08 BPM. The results validate the feasibility of TPG for direct pulse monitoring. A comparative study on pulse sensitivity is conducted between TPG and rPPG. The results indicate that the TPG contains more pulsatile information from the forehead BOI than that in the rPPG signals in regular office lighting condition and thus generate better heart rate estimation statistic in the form of empirical cumulative distribution function of HR estimation error. Last but not least, TPG penetrability test for covered skin is demonstrated using two types of garment materials commonly used in daily life. 

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