The bilateral photoplethysmography (PPG) analysis for arteriovenous fistula (AVF) dysfunction screening with a fractional-order feature and a cooperative game (CG)-based embedded detector is proposed. The proposed detector uses a feature extraction method and a CG to evaluate the risk level for AVF dysfunction for patients undergoing haemodialysis treatment. A Sprott system is used to design a self-synchronisation error formulation to quantify the differences in the changes of blood volume for the sinister and dexter thumbs’ PPG signals. Bilateral PPGs exhibit a significant difference in rise time and amplitude, which is proportional to the degree of stenosis. A less parameterised CG model is then used to evaluate the risk level. The proposed detector is also studied using an embedded system and bilateral optical measurements. The experimental results show that the risk of AVF stenosis during haemodialysis treatment is detected earlier.

Currently accepted input parameter limitations in entropy-based, non-linear signal processing methods, for example, sample entropy (SampEn), may limit the information gathered from tested biological signals. The ability of quadratic sample entropy (QSE) to identify changes in electroencephalogram (EEG) signals of 11 patients with a diagnosis of Alzheimer's disease (AD) and 11 age-matched, healthy controls is investigated. QSE measures signal regularity, where reduced QSE values indicate greater regularity. The presented method allows a greater range of QSE input parameters to produce reliable results than SampEn. QSE was lower in AD patients compared with controls with significant differences (p < 0.01) for different parameter combinations at electrodes P3, P4, O1 and O2. Subject- and epoch-based classifications were tested with leave-one-out linear discriminant analysis. The maximum diagnostic accuracy and area under the receiver operating characteristic curve were 77.27 and more than 80%, respectively, at many parameter and electrode combinations. Furthermore, QSE results across all r values were consistent, suggesting QSE is robust for a wider range of input parameters than SampEn. The best results were obtained with input parameters outside the acceptable range for SampEn, and can identify EEG changes between AD patients and controls. However, caution should be applied because of the small sample size.

With the aim of reducing cost and power consumption of the receiving terminal, compressive sensing (CS) framework is applied to on-body ultra-wideband (UWB) channel estimation. It is demonstrated in this Letter that the sparse on-body UWB channel impulse response recovered by the CS framework fits the original sparse channel well; thus, on-body channel estimation can be achieved using low-speed sampling devices.