Correlation of bioimpedance changes after compressive loading of murine tissues in vivo.

Objective: Rises in the incidence of pressure ulcers are increasingly prevalent in an aging population. Pressure ulcers are painful, are associated with increased morbidity and mortality, increase the risk for secondary infections and inpatient stay, and adds $26.8 billion annually to the healthcare costs of the USA.

Wireless Pressure Ulcer Sensor: Validation in an Animal Model.

Pressure ulcers are increasingly prevalent in an aging population. The most commonly used method of pressure ulcer prevention is pressure off-loading achieved by physically turning bedbound patients or by using expensive, single application devices such as wheelchair cushions. Our aim is to approach the problem of pressure ulcer prevention in a new way: a wireless sensor worn by the patient at locations susceptible to pressure injury.

A New Vision for Preventing Pressure Ulcers: Wearable Wireless Devices Could Help Solve a Common-and Serious-Problem.

With an aging population, the incidence and prevalence of wound problems is on the rise. Bedsores (also known as pressure ulcers or decubitus ulcers) are painful, take months to heal, and, for many patients, never do, leading to other health problems. The condition has become so acute that treating bedsores is now a significant burden on the healthcare system.

Evaluation of key design parameters for mitigating motion artefact in the mobile reflectance PPG signal to improve estimation of arterial oxygenation.

Objective: Pulse oximetry, a widely accepted method for non-invasive estimation of arterial oxygen saturation (SpO) and pulse rate (PR), is increasingly being adapted for mobile applications. Previous work in mitigating motion artefact, which corrupts the photoplethysmogram (PPG) used in pulse oximetry, has focused on reducing noise using signal processing algorithms or through sensor design that controlled only one variable at a time. In this work, we have investigated the effect of several variables such as sensor weight, relative motion, placement, and contact force against the skin that can impact motion artefact independently or by interacting with each other.

Using support vector machines on photoplethysmographic signals to discriminate between hypovolemia and euvolemia.

Identifying trauma patients at risk of imminent hemorrhagic shock is a challenging task in intraoperative and battlefield settings given the variability of traditional vital signs, such as heart rate and blood pressure, and their inability to detect blood loss at an early stage. To this end, we acquired N = 58 photoplethysmographic (PPG) recordings from both trauma patients with suspected hemorrhage admitted to the hospital, and healthy volunteers subjected to blood withdrawal of 0.9 L.

A Robust Motion Artifact Detection Algorithm for Accurate Detection of Heart Rates From Photoplethysmographic Signals Using Time-Frequency Spectral Features.

Motion and noise artifacts (MNAs) impose limits on the usability of the photoplethysmogram (PPG), particularly in the context of ambulatory monitoring. MNAs can distort PPG, causing erroneous estimation of physiological parameters such as heart rate (HR) and arterial oxygen saturation (SpO2). In this study, we present a novel approach, "TifMA," based on using the time-frequency spectrum of PPG to first detect the MNA-corrupted data and next discard the nonusable part of the corrupted data.

Improving Pulse Rate Measurements during Random Motion Using a Wearable Multichannel Reflectance Photoplethysmograph.

Photoplethysmographic (PPG) waveforms are used to acquire pulse rate (PR) measurements from pulsatile arterial blood volume. PPG waveforms are highly susceptible to motion artifacts (MA), limiting the implementation of PR measurements in mobile physiological monitoring devices. Previous studies have shown that multichannel photoplethysmograms can successfully acquire diverse signal information during simple, repetitive motion, leading to differences in motion tolerance across channels.

A Novel Time-Varying Spectral Filtering Algorithm for Reconstruction of Motion Artifact Corrupted Heart Rate Signals During Intense Physical Activities Using a Wearable Photoplethysmogram Sensor.

Accurate estimation of heart rates from photoplethysmogram (PPG) signals during intense physical activity is a very challenging problem. This is because strenuous and high intensity exercise can result in severe motion artifacts in PPG signals, making accurate heart rate (HR) estimation difficult. In this study we investigated a novel technique to accurately reconstruct motion-corrupted PPG signals and HR based on time-varying spectral analysis.

Photoplethysmograph signal reconstruction based on a novel hybrid motion artifact detection-reduction approach. Part I: Motion and noise artifact detection.

Motion and noise artifacts (MNA) are a serious obstacle in utilizing photoplethysmogram (PPG) signals for real-time monitoring of vital signs. We present a MNA detection method which can provide a clean vs. corrupted decision on each successive PPG segment.

Photoplethysmograph signal reconstruction based on a novel motion artifact detection-reduction approach. Part II: Motion and noise artifact removal.

We introduce a new method to reconstruct motion and noise artifact (MNA) contaminated photoplethysmogram (PPG) data. A method to detect MNA corrupted data is provided in a companion paper. Our reconstruction algorithm is based on an iterative motion artifact removal (IMAR) approach, which utilizes the singular spectral analysis algorithm to remove MNA artifacts so that the most accurate estimates of uncorrupted heart rates (HRs) and arterial oxygen saturation (SpO2) values recorded by a pulse oximeter can be derived.

Statistical approach for the detection of motion/noise artifacts in Photoplethysmogram.

Motion and noise artifacts (MNA) have been a serious obstacle in realizing the potential of Photoplethysmogram (PPG) signals for real-time monitoring of vital signs. We present a statistical approach based on the computation of kurtosis and Shannon Entropy (SE) for the accurate detection of MNA in PPG data. The MNA detection algorithm was verified on multi-site PPG data collected from both laboratory and clinical settings.

Physiological parameter monitoring from optical recordings with a mobile phone.

We show that a mobile phone can serve as an accurate monitor for several physiological variables, based on its ability to record and analyze the varying color signals of a fingertip placed in contact with its optical sensor. We confirm the accuracy of measurements of breathing rate, cardiac R-R intervals, and blood oxygen saturation, by comparisons to standard methods for making such measurements (respiration belts, ECGs, and pulse-oximeters, respectively). Measurement of respiratory rate uses a previously reported algorithm developed for use with a pulse-oximeter, based on amplitude and frequency modulation sequences within the light signal.

A novel approach using time-frequency analysis of pulse-oximeter data to detect progressive hypovolemia in spontaneously breathing healthy subjects.

Accurate and early detection of blood volume loss would greatly improve intraoperative and trauma care. This study has attempted to determine early diagnostic and quantitative markers for blood volume loss by analyzing photoplethysmogram (PPG) data from ear, finger and forehead sites with our high-resolution time-frequency spectral (TFS) technique in spontaneously breathing healthy subjects (n = 11) subjected to lower body negative pressure (LBNP). The instantaneous amplitude modulations present in heart rate (AM HR) and breathing rate (AMBR) band frequencies of PPG signals were calculated from the high-resolution TFS.

A comparative evaluation of adaptive noise cancellation algorithms for minimizing motion artifacts in a forehead-mounted wearable pulse oximeter.

Wearable physiological monitoring using a pulse oximeter would enable field medics to monitor multiple injuries simultaneously, thereby prioritizing medical intervention when resources are limited. However, a primary factor limiting the accuracy of pulse oximetry is poor signal-to-noise ratio since photoplethysmographic (PPG) signals, from which arterial oxygen saturation (SpO2) and heart rate (HR) measurements are derived, are compromised by movement artifacts. This study was undertaken to quantify SpO2 and HR errors induced by certain motion artifacts utilizing accelerometry-based adaptive noise cancellation (ANC).

Reflectance forehead pulse oximetry: effects of contact pressure during walking.

Steady progress has been made towards the development of a reliable wearable pulse oximeter to aid first responders in remote monitoring and triage operations. This study was undertaken to assess how varying contact pressures affects the photoplethysmographic (PPG) signal, and arterial oxygen saturation (SpO2) and heart rate (HR) measurement errors during motion artifact inducing activity. The study revealed that contact pressures ranging from 8-12 kPa resulted in the largest PPG amplitude for a reflectance sensor attached to the forehead region above the eye, although the signal-to-noise ratio (SNR) did not improve significantly.

Multi-wavelength reflectance pulse oximetry.

The performance of current reflectance pulse oximeters is hindered by poor signal-to-noise ratio. To overcome this problem a new reflectance oximeter has been developed with a sensor which consists of three LEDs and two continuous photodetector rings placed equidistant from the center of the LEDs. In addition, ultra low noise electronics and adaptive algorithm assure improved performance.