BackgroundWorldwide, at least 200 million people are affected by peripheral vascular diseases (PVDs), including peripheral arterial disease (PAD), chronic venous insufficiency (CVI) and deep vein thrombosis (DVT). The high prevalence and serious consequences of PVDs have led to the development of several diagnostic tools and clinical guidelines to assist timely diagnosis and patient management. Given the increasing number of diagnostic methods available, a comprehensive review of available technologies is timely in order to understand their limitations and direct future development effort.Main bodyThis paper reviews the available diagnostic methods for PAD, CVI, and DVT with a focus on non-invasive modalities. Each method is critically evaluated in terms of sensitivity, specificity, accuracy, ease of use, procedure time duration, and training requirements where applicable.ConclusionThis review emphasizes the limitations of existing methods, highlighting a latent need for the development of new non-invasive, efficient diagnostic methods. Some newly emerging technologies are identified, in particular wearable sensors, which demonstrate considerable potential to address the need for simple, cost-effective, accurate and timely diagnosis of PVDs.Electronic supplementary materialThe online version of this article (10.1186/s12938-018-0494-4) contains supplementary material, which is available to authorized users.

A reliable system that can simultaneously and accurately monitor respiration and cardiac output would have great utility in healthcare applications. In this paper we present a novel approach to creating such a system. This noninvasive, low power, low cost, contactless sensor is suitable for continuous monitoring of respiration (tidal volume) and cardiac stroke volume. Furthermore, it is capable of delivering this data in true volume (i.e., mL). The current embodiment, specifically designed for sleep monitoring applications, requires only 100 mW when powered by a 4.8 V battery pack and is based on the use of a single electroresistive band embedded in a T-shirt. Here, we describe the implementation of the device, explaining the rational and design choices for the electronic circuit and the physical garment together with the preliminary tests performed using one volunteer subject. Comparison of the device with a commercially available spirometer demonstrates that tidal volume can be monitored over extended periods with a precision of ±10%. We further demonstrate the utility of the device to measure cardiac output and respiration effort.

Since the invention of the 12-lead Electrocardiography (ECG) it is taught that only eight out of the twelve signals recordable from the nine exploring electrodes are linearly independent. It is also accepted practice the use of other four linearly dependent signals to add diagnostic efficacy. Unfortunately, quality and usefulness of the 12-lead signals is directly correlated with electrode placement precision and concerns have been raised around intentional misplacements of limb electrodes also for resting ECG. In this paper we show that with a simple modification to the recording front-end, nine independent signals (one per recording electrode) can be recorded. These signals can be used to reconstruct precisely the 12-lead signals (without information loss) and a plethora of other linearly dependent new signals that can open an unexplored frontier in cardiac illnesses diagnosis. While we need to carefully evaluate the clinical implications of our findings, we present here the proposed circuit and a case study (healthy subject) showing the number of signals achievable and we quantify the effect upon the ECG signals of one of the most common intentional misplacement of electrodes

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Abstract:The use of wearable sensors in health monitoring is increasing dramatically, largely due to their convenience and low-cost. Understanding the accuracy of any given sensor is paramount to avoid potential misdiagnosis. Commercially available electro-resistive band (ERB) sensors have been integrated into several newly developed wearable devices with a view to using these sensors to monitor a range of respiratory and cardiovascular metrics. Quantification of the ERBs is a necessary to step towards validation of these prototypes, as it provides valuable information, which could be exploited for compensation and ultimately, for improvement of their performance. Here, we present an analysis of the ERB sensors using an expansion/contraction simulator machine. Using the developed rig, the characteristics of four ERBs were compared with a linear displacement sensor (string potentiometer) during continuous use over the course of four-and-a-half days to investigate the error and nonlinearity of the ERBs. The analysis of the recorded data includes calculation and comparison of the total harmonic distortions of the two sensors to quantify ERB nonlinearity. Moreover, comparisons between the peak-to-peak voltages and signal-to-noise ratios of the ERB and string potentiometer demonstrate the effect nonlinearity on these factors. This paper demonstrates the nonlinearity of ERBs and highlights the implications for their use in practice.