Towards a low-cost mobile subcutaneous vein detection solution using near-infrared spectroscopy

Abstract

Excessive venipunctures are both time- and resource-consuming events, which cause anxiety, pain, and distress in patients, or can lead to severe harmful injuries. We propose a low-cost mobile health solution for subcutaneous vein detection using near-infrared spectroscopy, along with an assessment of the current state of the art in this field. The first objective of this study was to get a deeper overview of the research topic, through the initial team discussions and a detailed literature review (using both academic and grey literature). The second objective, that is, identifying the commercial systems employing near-infrared spectroscopy, was conducted using the PubMed database. The goal of the third objective was to identify and evaluate (using the IEEE Xplore database) the research efforts in the field of low-cost near-infrared imaging in general, as a basis for the conceptual model of the upcoming prototype. Although the reviewed commercial devices have demonstrated usefulness and value for peripheral veins visualization, other evaluated clinical outcomes are less conclusive. Previous studies regarding low-cost near-infrared systems demonstrated the general feasibility of developing cost-effective vein detection systems; however, their limitations are restricting their applicability to clinical practice. Finally, based on the current findings, we outline the future research direction.

Figure 1

PubMed search strategy and literature selection process.

Figure 2

IEEE Xplore database search strategy and literature selection process.

Figure 3

High level conceptual model and architecture of the prototype, embedded in a wireframe of one of the target devices (smartphone). (1) Attachment which comprises a standard (converted to be NIR sensitive) USB camera and 4 NIR LEDs for the illumination of the target area (e.g., hand). (2) Illustration of 1 NIR LED illumination distribution, with the most luminous intensity around the center. (3) Micro-USB connection cable (data transmission and power supply for the attachment). (4) Software libraries (camera usage and management, image processing) written in the native Android layer (for performance optimizations). (5) User interface software components. Both (4) and (5) will be developed as a single Android-based mobile application applicable to mobile devices running Android OS version 4.0.3 (ICS) or above.

Figure 4

Current result of the ongoing feasibility studies applying the proposed model to the target platform (standard mobile device). The first image shows the acquired image (converted to grayscale) using the initial version of the prototype (based on Figure 3). Subsequent images present the interim results of applying digital signal processing strategies in order to enhance and additionally visualize the vein pattern.