Enhanced illumination sensing using multiple harmonics for LED lighting systems

This paper considers frequency division multiplexing (FDM) based illumination sensing in light emitting diode (LED) lighting systems. The purpose of illumination sensing is to identify the illumination contributions of spatially distributed LEDs at a sensor location, within a limited response time. In the FDM scheme, LEDs render periodical illumination pulse trains at different frequencies with prescribed duty cycles. The problem of interest is to estimate the amplitudes of the individual illumination pulse trains. In our previous work, an estimation approach was proposed using the fundamental frequency component of the sensor signal. The number of LEDs that can be supported by this estimation approach is limited to around 100 LEDs at a response time of 0.1 s. For future LED lighting systems, however, it is desirable to support many more LEDs. To this end, in this paper, we seek to exploit multiple harmonics in the sensor signal. We first derive upper limits on the number of LEDs that can be supported in the presence of frequency offsets and noise. Thereafter, we propose a low complexity successive estimation approach that effectively exploits the multiple harmonics. It is shown that the number of the LEDs can be increased by a factor of at least five, compared to the estimation approach using only the fundamental frequency component, at the same estimation error

Parameter estimation of multiple pulse trains for illumination sensing

We consider illumination sensing in a light emitting diode (LED) lighting system based on frequency division multiplexing (FDM). In the FDM scheme, LEDs render periodical illumination pulses at different frequencies with prescribed duty cycles. The purpose of illumination sensing is to identify the illumination contributions of different LEDs at a target location, within a limited response time. With the use of a photosensor at the target location, the problem of interest is to estimate the amplitude of the sensor signal component due to each LED. In this paper, we propose a successive estimation approach exploiting higher order harmonics of the sensor signal. We show that a larger number of LEDs can be supported using the proposed approach, as compared to our previous approach using only the fundamental frequency component, at the same estimation error

Hierarchical probabilistic framework for fetal R-peak detection, using ECG waveform and heart rate information

The abdominal fetal electrocardiogram (fECG) can provide valuable information about fetal well-being. However, fetal R-peak detection in abdominal fECG recordings is challenging due to the low signal-to-noise ratio (SNR) and the nonstationary nature of the fECG waveform in the abdominal recordings. In this paper, we propose a multichannel hierarchical probabilistic framework for fetal R-peak detection that combines predictive models of the ECG waveform and the heart rate. The performance of our method was evaluated on set-A of the 2013 Physionet/Computing in Cardiology Challenge and compared to the performance of several methods that have been proposed in the literature. The hierarchical probabilistic framework presented in this study outperforms other methods for fetal R-peak detection with a mean overall detection accuracy for set-A of 99.6%. Even for recordings with low SNR our method enables reliable fetal R-peak detection (Ac 99.4%)

An extended Kalman filter for fetal heart location estimation during Doppler-based heart rate monitoring

Fetal heart rate (fHR) monitoring using the Doppler ultrasound (US) is a standard clinical practice for assessing fetal well-being before and during labor. For continuous fHR measurements, the US transducer is positioned on the maternal abdomen using a flexible belt. Due to fetal movement, the relative fetal heart location (fHL) with respect to the US transducer can change, leading to frequent periods of signal loss hampering the clinical assessment of fetal health. Consequently, the clinical staff has to repeatedly reposition the US transducer--a cumbersome task affecting clinical workflow. We propose a method to estimate the fHL during fHR monitoring to support clinicians in efficiently repositioning the US transducer. Unlike typical US transducers, which do not provide any information on the spatial fHL, we exploit the fact that multiple transducer elements are present in the array aperture of the US transducer. We developed a novel model that relates the measured Doppler power in the individual transducer elements to the fHL and use it within the probabilistic framework of an extended Kalman filter (EKF). The performance of the EKF algorithm was evaluated in simulations and in in vitro experiments using a dedicated setup of a beating fetal heart. Both simulations and in vitro experiments showed that the fHL can be determined with an accuracy of 4 mm. Furthermore, we demonstrate that when the fetal heart is drifting out of the US beam, the EKF algorithm accurately estimates the fHL up to a radial distance of $34$ mm

Respiratory activity extracted from wrist-worn reflective photoplethysmography in a sleep-disordered population

Objective: Respiratory activity is an essential parameter to monitor healthy and disordered sleep, and unobtrusive measurement methods have important clinical applications in diagnostics of sleep-related breathing disorders. We propose a respiratory activity surrogate extracted from wrist-worn reflective photoplethysmography validated on a heterogeneous dataset of 389 sleep recordings. Approach: The surrogate was extracted by interpolating the amplitude of the PPG pulses after evaluation of pulse morphological quality. Subsequent multistep post-processing was applied to remove parts of the surrogate with low quality and high motion levels. In addition to standard respiration rate performance, we evaluated the similarity between surrogate respiratory activity and reference inductance plethysmography of the thorax, using Spearman's correlations and spectral coherence, and assessed the influence of PPG signal quality, motion levels, sleep stages and obstructive sleep apnea. Main results: Prior to post-processing, the surrogate already had a strong similarity with the reference (correlation=0.54, coherence=0.81), and reached respiration rate estimation performance in line with the literature (estimation error=0.76±2.11 breaths/min). Detrimental effects of low PPG quality, high motion levels and sleep stage-dependent physiological phenomena were significantly mitigated by the proposed post-processing steps (correlation=0.62, coherence=0.88, estimation error=0.53±1.98 breaths/min). Significance: Wrist-worn PPG can be used to extract respiratory activity, thus allowing respiration monitoring in real-world sleep medicine applications using (consumer) wearable devices

Sinus or not: a new beat detection algorithm based on a pulse morphology quality index to extract normal sinus rhythm beats from wrist-worn photoplethysmography recordings

OBJECTIVE: Wrist-worn photoplethysmography (PPG) can enable free-living physiological monitoring of people during diverse activities, ranging from sleep to physical exercise. In many applications, it is important to remove the pulses not related to sinus rhythm beats from the PPG signal before using it as a cardiovascular descriptor. In this manuscript, we propose an algorithm to assess the morphology of the PPG signal in order to reject non-sinus rhythm pulses, such as artefacts or pulses related to arrhythmic beats. APPROACH: The algorithm segments the PPG signal into individual pulses and dynamically evaluates their morphological likelihood of being normal sinus rhythm pulses via a template-matching approach that accounts for the physiological variability of the signal. The normal sinus rhythm likelihood of each pulse is expressed as a quality index that can be employed to reject artefacts and pulses related to arrhythmic beats. MAIN RESULTS: Thresholding the pulse quality index enables near-perfect detection of normal sinus rhythm beats by rejecting most of the non-sinus rhythm pulses (positive predictive value 98%-99%), both in healthy subjects and arrhythmic patients. The rejection of arrhythmic beats is almost complete (sensitivity to arrhythmic beats 7%-3%), while the sensitivity to sinus rhythm beats is not compromised (96%-91%). SIGNIFICANCE: The developed algorithm consistently detects normal sinus rhythm beats in a PPG signal by rejecting artefacts and, as a first of its kind, arrhythmic beats. This increases the reliability in the extraction of features which are adversely influenced by the presence of non-sinus pulses, whether related to inter-beat intervals or to pulse morphology, from wrist-worn PPG signals recorded in free-living conditions

Fetal heart rate monitoring implemented by dynamic adaptation of transmission power of a flexible ultrasound transducer array

Fetal heart rate (fHR) monitoring using Doppler Ultrasound (US) is a standard method to assess fetal health before and during labor. Typically, an US transducer is positioned on the maternal abdomen and directed towards the fetal heart. Due to fetal movement or displacement of the transducer, the relative fetal heart location (fHL) with respect to the US transducer can change, leading to frequent periods of signal loss. Consequently, frequent repositioning of the US transducer is required, which is a cumbersome task affecting clinical workflow. In this research, a new flexible US transducer array is proposed which allows for measuring the fHR independently of the fHL. In addition, a method for dynamic adaptation of the transmission power of this array is introduced with the aim of reducing the total acoustic dose transmitted to the fetus and the associated power consumption, which is an important requirement for application in an ambulatory setting. The method is evaluated using an in-vitro setup of a beating chicken heart. We demonstrate that the signal quality of the Doppler signal acquired with the proposed method is comparable to that of a standard, clinical US transducer. At the same time, our transducer array is able to measure the fHR for varying fHL while only using 50% of the total transmission power of standard, clinical US transducers