BIOSENSOR VALIDATION

Optical Integration without Compromises

Dr. Janos Palhalmi (PhD) and Jan-Hein Broeders Analog Devices Instruments, Technical Articles

Abstract

Photoplethysmography (PPG) is a common technology for measuring oxygen saturation (SPO 2 ) levels in blood. Light is sent by a light emitter into the body, and the amount of reflective or unabsorbed light is measured with a photoreceiver. Depending on the ratio between two wavelengths, the amount of oxygenated haemoglobin can be measured. Comparable technologies are also used to measure heart rate with an optical technology or heart rate variability. All these systems require one or more photoemitters, which need to be controlled, and a photodetector to measure the amount of photocurrent as a measure for the received light. This receive signal finally needs to be amplified, conditioned, and digitized. Such an optical system might sound straightforward; however, with a missing dose of optical knowledge, it is very easy to retrieve an optical signal, which doesn’t have anything to do with the signals the user is looking for. To help companies achieve their optical objectives, a new, fully integrated optical module has been introduced. It has been tested and compared to a well-proven discrete optical system with outstanding results. You will read more about the results and methodologies behind this exercise.

Download full paper:

https://www.analog.com/media/en/technical-documentation/tech-articles/optical-integration-without-compromises.pdf

A Statistical Metrology Approach to Compare the Quality of Optical Pulse Wave Signals

Dr. Janos Palhalmi (PhD) and Jan-Hein Broeders

Computing in Cardiology 2019

Abstract

Biometric metrology is becoming increasingly important as the wearable application specific biosensors are capable of generating accurate raw signals representing certain vital states. A comparative statistical approach has been worked out to answer questions arising from a biosensor testing measurement technology perspective. In this specific work two high quality optical solutions (Analog Devices’ ADPD107 and ADPD188GGZ) were compared to analyse the deep data level similarities or differences between the photo-plethysmography (PPG) raw biomedical signals generated by the two individual systems.
Two minutes long parallel recordings were carried out with the evaluation boards of both optical systems (EVAL-HCRWATCH and EVAL-ADPD188GGZ) on 11 healthy human subjects. Recordings were repeated on both wrists to avoid side specific influence. Both systems have been controlled by Analog Devices’ user-interface called “Application WaveTool”. For the test, configuration settings were optimized to achieve the highest signal quality and lowest power consumption (5.1 mW at 100 Hz sampling frequency). The physiologically and biometrically irrelevant frequency bands (<0.25 Hz,>40 Hz) were filtered before the data analysis.
A wavelet coherence-based method was worked out to compare the relevant frequency bands and two different correlation-based methods were developed to compare the wave-to-wave stability and similarity of the two compared signals. Magnitude squared coherence values were above 0.9 in all the explored frequency bands (0.25-40 Hz). Correlation coefficients were never under 0.9 while p values were always under 0.001 in case of the PPG wave-to-wave comparisons. Based on the results we can conclude, that the quality of the PPG signal recorded by the new ADPD188GGZ integrated optical module, reaches the same performance level as the ADPD107 discrete module, with key benefits such as small PCB area, ease of use (especially for companies with limited Optical expertise) and shorter Time to Market.

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http://www.cinc.org/archives/2019/pdf/CinC2019-165.pdf

A Computationally Efficient Method to Quantify the Biometric Properties of Ventricular Repolarization Irregularities in Healthy and Diseased Human Subjects</4>

Dr. Janos Palhalmi (PhD)

Computing in Cardiology 2018

Abstract

Repolarization heterogeneityexpressed by QT interval prolongation and abnormal temporal dynamics of the QT intervaltime seriesisan important factorin relation to coronary heart disease and lethal arrhythmias.
Based on our observations, the calculation of window correlation between the mean and varianceof featuresextracted from QTinterval time series can reveal natural and disease specific fluctuationpatterns. Our algorithm is potentially a sensitive biometric measure to quantifypersonalized differences and the propertiesof repolarization heterogeneity,andalso a potential biomarker to characterize disease specific QT interval temporal dynamics.

Download abstract:
https://ieeexplore.ieee.org/document/8744048/authors#authors

Download full paper:

http://www.cinc.org/archives/2018/pdf/CinC2018-080.pdf