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The classifier of support vector machine (SVM) learning for assessing the quality of arteriovenous fistulae (AVFs) in hemodialysis (HD) patients using a new photoplethysmography (PPG) sensor device is presented in this work. In clinical practice, there are two important indices for assessing the quality of AVF: the blood flow volume (BFV) and the degree of stenosis (DOS). In hospitals, the BFV and DOS of AVFs are nowadays assessed using an ultrasound Doppler machine, which is bulky, expensive, hard to use, and time consuming. In this study, a newly-developed PPG sensor device was utilized to provide patients and doctors with an inexpensive and small-sized solution for ubiquitous AVF assessment. The readout in this sensor was custom-designed to increase the signal-to-noise ratio (SNR) and reduce the environment interference via maximizing successfully the full dynamic range of measured PPG entering an analog–digital converter (ADC) and effective filtering techniques. With quality PPG measurements obtained, machine learning classifiers including SVM were adopted to assess AVF quality, where the input features are determined based on optical Beer–Lambert’s law and hemodynamic model, to ensure all the necessary features are considered. Finally, the clinical experiment results showed that the proposed PPG sensor device successfully achieved an accuracy of 87.84% based on SVM analysis in assessing DOS at AVF, while an accuracy of 88.61% was achieved for assessing BFV at AVF.

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In this study, wearable devices are made using wireless vertical-type light-emitting diode (LED) packages of a transparent conductive film coated on flexible colorless polyimide (PI) with 50 μm thickness. The low-stress ultrathin transparent conductive multilayers are deposited on the PI using high-power impulse magnetron sputtering at 65 °C. It can be used as the electrode in an ultraflexible photoplethysmography (PPG) biosensor. The nearly stress-free multilayer, consisting of a Ag layer with 20 nm thickness sandwiched between indium tin oxide (ITO) layers with 30 nm thickness, is transparent to infrared (940 nm) and exhibits a sheet resistance and resistivity of 5.7 Ω/sq. and 4.57 × 10 −5 Ω•cm, respectively. We fabricate a PPG biosensor with a vertical-type infrared LED bonded onto the flexible ITO/Ag/ITO/PI. We demonstrate that our PPG biosensor is a sensitive and accurate screening tool for the detection of pulsation signals and the heart rate (HR). The standard deviation of HR detections is as low as 2.6 bpm, satisfying the standard of <5% for approximately 3.5 bpm set by the AAMI SP10/ISO 81060-2:2009. This kind of a PPG biosensor can be applied to wearable devices for healthcare monitoring applications.