Reisner A, Shaltis PA, McCombie D, Asada HH. Utility of the photoplethysmogram in circulatory monitoring

Department of Medicine, Division of Emergency Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Anesthesiology (Impact Factor: 5.88). 06/2008; 108(5):950-8. DOI: 10.1097/ALN.0b013e31816c89e1
Source: PubMed


The photoplethysmogram is a noninvasive circulatory signal related to the pulsatile volume of blood in tissue and is displayed by many pulse oximeters and bedside monitors, along with the computed arterial oxygen saturation. The photoplethysmogram is similar in appearance to an arterial blood pressure waveform. Because the former is noninvasive and nearly ubiquitous in hospitals whereas the latter requires invasive measurement, the extraction of circulatory information from the photoplethysmogram has been a popular subject of contemporary research. The photoplethysmogram is a function of the underlying circulation, but the relation is complicated by optical, biomechanical, and physiologic covariates that affect the appearance of the photoplethysmogram. Overall, the photoplethysmogram provides a wealth of circulatory information, but its complex etiology may be a limitation in some novel applications.

84 Reads
  • Source
    • "Transthoracic impedance (TTI) measurements [13]–[15] and near-infrared spectroscopy (NIRS) [16], [17] are noninvasive methods, but TTI is strongly influenced by compressions and NIRS responds slowly upon ROSC. Generally, photoplethysmography (PPG) is an easy to use and noninvasive technique to continuously measure a spontaneous pulse [18], [19]. Its potential to measure a spontaneous pulse during compressions has been observed in an automated-CPR animal study [20]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Detecting return of spontaneous circulation (ROSC) during cardiopulmonary resuscitation (CPR) is challenging, timeconsuming, and requires interrupting chest compressions. Based on automated-CPR porcine data, we have developed an algorithm to support ROSC detection, which detects cardiogenic output during chest compressions via a photoplethysmography (PPG) signal. The algorithm can detect palpable and impalpable spontaneous pulses. A compression-free PPG signal which estimates the spontaneous pulse waveform, was obtained by subtracting the compression component, modeled by a harmonic series. The fundamental frequency of this series was the compression rate derived from the trans-thoracic impedance signal measured between the defibrillation pads. The amplitudes of the harmonic components were obtained via a least mean-square algorithm. The frequency spectrum of the compression-free PPG signal was estimated via an autoregressive model, and the relationship between the spectral peaks was analyzed to identify the pulse rate (PR). Resumed cardiogenic output could also be detected from a decrease in the baseline of the PPG signal, presumably caused by a redistribution of blood volume to the periphery. The algorithm indicated cardiogenic output when a PR or a redistribution of blood volume was detected. The algorithm indicated cardiogenic output with 94% specificity and 69% sensitivity compared to the retrospective ROSC detection of nine clinicians. Results showed that ROSC detection can be supported by combining the compression-free PPG signal with an indicator based on the detected PR and redistribution of blood volume.
    IEEE transactions on bio-medical engineering 11/2014; 62(3). DOI:10.1109/TBME.2014.2370649 · 2.35 Impact Factor
  • Source
    • "Photoplethysmography has been reported to be a suitable method for evaluation of the pulsating blood volume [32], and it has been applied in migraine [19]. However, traditional contact methods have limitations e.g. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Asymmetrical changes in blood perfusion and asynchronous blood supply to head tissues likely contribute to migraine pathophysiology. Imaging was widely used in order to understand hemodynamic variations in migraine. However, mapping of blood pulsations in the face of migraineurs has not been performed so far. We used the Blood Pulsation Imaging (BPI) technique, which was recently developed in our group, to establish whether 2D-imaging of blood pulsations parameters can reveal new biomarkers of migraine. BPI characteristics were measured in migraineurs during the attack-free interval and compared to healthy subjects with and without a family history of migraine. We found a novel phenomenon of transverse waves of facial blood perfusion in migraineurs in contrast to healthy subjects who showed synchronous blood delivery to both sides of the face. Moreover, the amplitude of blood pulsations was symmetrically distributed over the face of healthy subjects, but asymmetrically in migraineurs and subjects with a family history of migraine. In the migraine patients we found a remarkable correlation between the side of unilateral headache and the direction of the blood perfusion wave. Our data suggest that migraine is associated with lateralization of blood perfusion and asynchronous blood pulsations in the facial area, which could be due to essential dysfunction of the autonomic vascular control in the face. These findings may further enhance our understanding of migraine pathophysiology and suggest new easily available biomarkers of this pathology.
    PLoS ONE 12/2013; 8(12):e80189. DOI:10.1371/journal.pone.0080189 · 3.23 Impact Factor
  • Source
    • "In the developed device, operating in the reflectance mode, a light-emitting diode illuminates the finger of the user with infrared light (wavelength 890 nm). The light from the LED, entering the tissue, is partially scattered, partially absorbed by the hemoglobin in the erythrocytes, and partially reflected by deeper structures, " backlighting " superficial blood vessels [1]. Then, as the blood vessels in the finger fill with more blood, they absorb more light returning from the deeper tissues, and photodetector light intensity diminishes, following the Lambert–Beer law. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Pulse wave (PW) is a physiological event, observable and measurable in the arterial system during blood circulation. One of characteristics that can be determined from a PW record is heart rate variability (HRV), an indication of beat-to-beat alterations in the heart rate. HRV is an accurate and reliable reflection of several physiological factors modulating the normal rhythm of the heart. HRV has escalated in use as an important diagnostic tool which indicates the balance between sympathetic and parasympathetic branches of the autonomous nervous system (ANS) and the synchronization between them. HRV patterns are also sensitive to changes in emotional state and can be used to distinguish positive and negative emotions. However, HRV is just one of characteristics that can be extracted from a good quality pulse wave record. Other characteristics of the PW in the time and frequency domains can serve as an indication of the status of a cardio-vascular system. Modern personal health monitoring tools, which use data processing capability of smartphones and personal computers, make daily or even continuous HRV analysis available for users who are affected by sedentary life style, high stress, and fatigue. The practical application of the PW monitoring requires, besides software and electronic, selection of clinically meaningful characteristics of the pulse wave and communicating them to a non-medical user. For this purpose, it is proposed to use, in addition to HRV, to use the characteristics based on duration of the four phases of the pulse wave, and compare them with the baseline level obtained for the same user under non-stressed conditions. Deviations from the baseline are presented to the user. Correlation of these readings with objective parameters of the cardio-vascular system is supported by clinical data. Key words: heart rate variability, pulse wave characteristics, personal health monitoring. INTRODUCTION While sensitivity and specificity of the characteristics derived from a pulse wave may not meet clinical requirements, they are adequate for daily or periodic monitoring by users who are affected by sedentary life style, high stress, and fatigue. A personal health monitoring tool, measuring pulse wave, can employ the data processing capability of a smartphone or a notebook. Sample embodiments in a consumer product include a computer mouse or a standalone device, connected with a notebook via USB port (fig. 1, a, b). The pulse wave signal can also be generated by a built-in camera in a smartphone or by a web camera (fig. 1, c), by analyzing the variations in the light flow caused by pulsation of blood in a finger held next to the camera. These variations reach up to 1% of the total light flow.
    ASME 2012 International Mechanical Engineering Congress & Exposition, Houston; 11/2012
Show more


84 Reads
Available from