Photoplethysmography Fast Upstroke Time Intervals Can Be Useful Features for Cuff-Less Measurement of Blood Pressure Changes in Humans.

OBJECTIVE: Photoplethysmography (PPG) waveform analysis is being increasingly investigated for continuous, non-invasive, and cuff-less blood pressure (BP) measurement. However, the efficacy of this approach and the useful features and models remain largely unclear. The objectives were to develop easy-to-understand models relating PPG waveform features to BP changes (after a cuff calibration) and to determine their value in BP measurement accuracy. METHODS: The study data comprised finger, toe, and ear PPG waveforms, an ECG waveform, and reference manual cuff BP measurements from 32 human subjects (25% hypertensive) before and after slow breathing, mental arithmetic, cold pressor, and nitroglycerin administration. Stepwise linear regression was employed to create parsimonious models for predicting the intervention-induced BP changes from popular PPG waveform features, pulse arrival time (PAT, time delay between ECG R-wave and PPG foot), and subject demographics. Leave-one-subject-out cross validation was applied to compare the BP change prediction root-mean-squared-errors (RMSEs) of the resulting models to reference models in which PPG waveform features were excluded. RESULTS: Finger b-time (PPG foot to minimum second derivative time interval) and ear "STT" (PPG amplitude divided by maximum derivative), when combined with PAT, reduced the systolic BP change prediction RMSE of reference models by 6-7% (p 0.022). Ear STT together with pulse width reduced the diastolic BP change prediction RMSE of the reference model by 13% (p = 0.003). CONCLUSION: The two PPG fast upstroke time intervals can offer some added value in cuff-less BP trending. SIGNIFICANCE: This study offers important information towards achieving non-invasive and passive BP monitoring without a cuff.

Assessment of Calibration Models for Cuff-Less Blood Pressure Measurement After One Year of Aging.

OBJECTIVE: Many calibration models for cuff-less blood pressure (BP) measurement must be periodically updated with cuff BP values to account for vascular aging. However, the time period required for these "cuff re-calibrations" is largely unknown. The impact of one year of aging on several calibration models was assessed. METHODS: Ten humans (6 males, 57±18 years, 3 hypertensives) were studied during multiple recording sessions that occurred one year apart. In each session, electrocardiography (ECG), ear photoplethysmography (PPG), finger PPG, and toe PPG waveforms and manual cuff BP were recorded before and after slow breathing, mental arithmetic, cold pressor, and nitroglycerin. Linear models based on each PPG waveform, which were previously shown to offer value in predicting the intervention-induced BP changes in a larger subject cohort, were employed. The model coefficients were determined for each subject via one session, and the fully-defined, subject-specific calibration models were then evaluated in the corresponding subjects via the session one year later. RESULTS: Only a linear model relating toe pulse arrival time (PAT) - time delay between ECG R-wave and toe PPG foot - to systolic BP (SBP) remained useful. After the year, this model changed little on average (root-mean-squared-error (RMSE) = 1.5 mmHg) and predicted the cuff BP values better than the average of the initial cuff BP values of the subject (RMSE = 9.6±0.8 mmHg vs. 12.7±1.0 mmHg; p < 0.05). CONCLUSION: These results suggest annual cuff recalibrations for the toe PAT-SBP model. SIGNIFICANCE: Toe PAT may offer a practical recalibration period that fosters user adherence.

Conventional pulse transit times as markers of blood pressure changes in humans.

Pulse transit time (PTT) represents a potential approach for cuff-less blood pressure (BP) monitoring. Conventionally, PTT is determined by (1) measuring (a) ECG and ear, finger, or toe PPG waveforms or (b) two of these PPG waveforms and (2) detecting the time delay between the waveforms. The conventional PTTs (cPTTs) were compared in terms of correlation with BP in humans. Thirty-two volunteers [50% female; 52 (17) (mean (SD)) years; 25% hypertensive] were studied. The four waveforms and manual cuff BP were recorded before and after slow breathing, mental arithmetic, cold pressor, and sublingual nitroglycerin. Six cPTTs were detected as the time delays between the ECG R-wave and ear PPG foot, R-wave and finger PPG foot [finger pulse arrival time (PAT)], R-wave and toe PPG foot (toe PAT), ear and finger PPG feet, ear and toe PPG feet, and finger and toe PPG feet. These time delays were also detected via PPG peaks. The best correlation by a substantial extent was between toe PAT via the PPG foot and systolic BP [- 0.63 ± 0.05 (mean ± SE); p < 0.001 via one-way ANOVA]. Toe PAT is superior to other cPTTs including the popular finger PAT as a marker of changes in BP and systolic BP in particular.

Evaluation of efficacy of thermographic breast imaging in breast cancer: A pilot study.

BACKGROUND: Thermographic imaging is a non-invasive and radiation free imaging modality that measures the infrared radiation released by the body. Recently, there is a renewed interest regarding the scope of thermal imaging for breast cancer. OBJECTIVE: To evaluate the efficacy of thermographic breast imaging in detecting breast cancer. METHODS: A Prospective observational study was carried out from January 2014 to December 2014 at Kasturba Hospital, Manipal, India. Patients in whom breast cancer was confirmed on FNAC or biopsy, were included in the study and further evaluated with thermographic imaging of the breast. RESULTS: 65 patients with FNAC or biopsy proven breast carcinoma were included in the study. Using thermographic imaging, malignancy was accurately detected in 60 patients (92.31%). Mammography was able to detect malignancy in 62 out of the 65 patients (95.38%). Thermography was able to detect malignancy in all 3 cases in which conventional mammography missed it. CONCLUSION: Thermography may have a role in detection of breast cancer. However, it is too early to recommend thermographic imaging as a standard imaging modality for breast cancer. Larger studies are required to evaluate the usefulness of thermography in diagnosis and/or screening of breast cancer.

A study of the effect of subject motion to pulse rate estimation.

We presented a systematic study of how subject head motion affects pulse rate estimation using photoplethysmography from the subject's face. We evaluated the performance at various steps in the process, including object tracking, skin blob detection, pulse signal extraction and pulse rate estimation. We demonstrated that the signal-to-noise ratio of the power spectrum is a good indicator of signal artifacts induced by subject motion, thus can be used as a quantitative metric in continuous pulse rate monitoring to reduce estimation errors.

Toward Ubiquitous Blood Pressure Monitoring via Pulse Transit Time: Theory and Practice.

Ubiquitous blood pressure (BP) monitoring is needed to improve hypertension detection and control and is becoming feasible due to recent technological advances such as in wearable sensing. Pulse transit time (PTT) represents a well-known potential approach for ubiquitous BP monitoring. The goal of this review is to facilitate the achievement of reliable ubiquitous BP monitoring via PTT. We explain the conventional BP measurement methods and their limitations; present models to summarize the theory of the PTT-BP relationship; outline the approach while pinpointing the key challenges; overview the previous work toward putting the theory to practice; make suggestions for best practice and future research; and discuss realistic expectations for the approach.

Detection of atrial fibrillation using contactless facial video monitoring.

BACKGROUND: It is estimated that 33.5 million people in the world have developed atrial fibrillation (AF), and an estimated 30% of patients with AF are unaware of their diagnosis (silent AF). OBJECTIVE: The purpose of this study was to test a new technology for contactless detection of AF based on facial video recordings. METHODS: The proposed technique uses a camera to record an individual's face and extract the subtle beat-to-beat variations of skin color reflecting the cardiac pulsatile signal. In a group of adults referred for electrical cardioversion, we recorded the ECG and the video of the subjects' face before and after electrical cardioversion. We extracted the beat-to-beat pulse rates expressed as pulses per minute (ppm) from the videoplethysmographic (VPG) signal acquired using a standard web camera. We introduce a novel quantifier of pulse variability called the pulse harmonic strength (PHS) and report its ability to detect the presence of AF. RESULTS: Eleven subjects (8 male; age 65 ± 6 years) were included in the study. The VPG and ECG-based rates were statistically different between the AF and sinus rhythm periods: 72 ± 9 ppm vs 57 ± 7 ppm (P < .0001) for VPG and 80 ± 17 bpm vs 56 ± 7 bpm (P < .0001) for ECG signals. Among the 407 epochs of 15 seconds of synchronized ECG and VPG signals, PHS was associated with a 20% detection error rate, and the error rates of the automatic ECG-based measurements ranged between 17% and 29%. CONCLUSION: Our preliminary results support the concept that contactless video-based monitoring of the human face for detection of abnormal pulse variability due to AF is feasible.

Semi-automated breast cancer tumor detection with thermographic video imaging.

Screening for breast cancer enables early detection by which curative treatment can be possible. While mammography is the current gold standard for screening, it has low sensitivity in younger women and its harmful X-rays in frequent screening can increase the risk of cancer. Incidence rates are rising in younger women, causing a relook at thermography for low cost and non-harmful screening. In this paper, thermography is compared to mammography correlated with sono-mammography in 65 FNAC/biopsy proven cancer subjects in India. Thermography is comparable to mammography correlated with sono-mammography, having 94% and 95% sensitivity, respectively. A novel semi-automated thermographic tumor detection and location algorithm used in this paper also provides 97% sensitivity. This shows the promise of automated thermographic screening for reaching large populations in a cost effective manner in low resource settings in countries like India. Further studies in a large scale need to be done to evaluate the specificity to enable such solutions.

Method for classifying cardiac arrhythmias using photoplethysmography.

Advances in mobile computing and miniature devices have contributed to the accelerated development of wearable technologies for clinical applications. The new trend of wearable technologies has fostered a growth of interest for sensors that can be easily integrated into wearable devices. In particular, photoplethysmography (PPG) is especially suitable for wearable sensing, as it is low-cost, noninvasive, and does not require wet electrodes like the electrocardiogram. Photoplethysmograph signals contain rich information about the blood pulsating variation which is strongly related to the electrical activities of the heart. Therefore, in this paper we hypothesize that the ambulatory PPG monitoring could be employed for arrhythmia detection and classification. This paper presents a method for classifying ventricular premature contraction (VPC) and ventricular tachycardia (VT) from normal sinus rhythm (NSR) and supraventricular premature contraction (SVPC) recorded in patients going through ablation therapy for arrhythmia. Although occasional VPCs are benign, the increase in the frequency of VPC events may lead to VT, which in turn,could evolve into ventricular fibrillation and sudden cardiac death. Therefore the accurate measurement of VPC frequency and early detection of VT events becomes essential for patients with cardiac disease.

Towards continuous monitoring of pulse rate in neonatal intensive care unit with a webcam.

We describe a novel method to monitor pulse rate (PR) on a continuous basis of patients in a neonatal intensive care unit (NICU) using videos taken from a high definition (HD) webcam. We describe algorithms that determine PR from videoplethysmographic (VPG) signals extracted from multiple regions of interest (ROI) simultaneously available within the field of view of the camera where cardiac signal is registered. We detect motion from video images and compensate for motion artifacts from each ROI. Preliminary clinical results are presented on 8 neonates each with 30 minutes of uninterrupted video. Comparisons to hospital equipment indicate that the proposed technology can meet medical industry standards and give improved patient comfort and ease of use for practitioners when instrumented with proper hardware.

Vascular pattern localization via temporal signature.

Accurate vascular pattern localization has many applications in the diverse scientific and application domains. For example, vascular patterns not only have been widely used as a biometric-based human identification method that is inexpensive, secure and easy to use, but also have produced more accurate heart-rate estimation using conventional RGB camera by defining regions of interest along the vascular patterns instead of the entire exposed skin area. In addition, extracting temporal activity along vascular patterns can further enable targeted monitoring of other physiological parameters, such as blood flow and blood pulse transition time. This paper presents a method for robust and accurate vascular pattern localization using conventional RGB imaging systems. Our approach overcomes current limitations of systems that use still RGB images for vascular pathway localization - which produce low contrast between areas of vascular patterns and skin tissues and are sensitive to skin color variations - by capturing the temporal differences between these two areas from RGB videos.

Constrained independent component analysis approach to nonobtrusive pulse rate measurements.

Nonobtrusive pulse rate measurement using a webcam is considered. We demonstrate how state-of-the-art algorithms based on independent component analysis suffer from a sorting problem which hinders their performance, and propose a novel algorithm based on constrained independent component analysis to improve performance. We present how the proposed algorithm extracts a photoplethysmography signal and resolves the sorting problem. In addition, we perform a comparative study between the proposed algorithm and state-of-the-art algorithms over 45 video streams using a finger probe oxymeter for reference measurements. The proposed algorithm provides improved accuracy: the root mean square error is decreased from 20.6 and 9.5 beats per minute (bpm) for existing algorithms to 3.5 bpm for the proposed algorithm. An error of 3.5 bpm is within the inaccuracy expected from the reference measurements. This implies that the proposed algorithm provided performance of equal accuracy to the finger probe oximeter.