Low-cost subcutaneous vein detection system using ARM9 based single board computer

Chakravorty, Tanushri; Sonawane, Dayaram; Sharma, Suchakrapani Datt; Patil, Tushar

doi:10.1109/icectech.2011.5941714

Cited by 19 publications

(11 citation statements)

References 4 publications

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“…A basic prototype vein finder is composed of a high power NIR-LED as the light source, a compact infrared-sensitive camera, sensor that will capture and format the image and a filter to remove unwanted impurities [29,30,31,32,33,34] (see Figure 2). Other prototypes were incorporated with additional parts by the researchers for enhancement purposes, like the use of a Digital Light Processing (DLP) projector that allows vein image on the surface of the skin [35].…”

Section: Results and Analysismentioning

confidence: 99%

“…This is to primarily address the estimated cost of available commercial vein finder using NIR technology for about 4500 USD (portable) to 27,000 USD (non-portable) [38]. Moreover, the most significant reason is the challenges that the physician, nurse, emergency medical technician and other medical practitioners encountered during venipuncture [37], intravenous (IV) drug delivery [32] and cannulation. This is usually due to the following reasons; veins are either very small, and/or deep, the patient’s age (elderly or pediatrics), skin color [37], and obesity level [32,35].…”

Section: Results and Analysismentioning

confidence: 99%

“…Moreover, the most significant reason is the challenges that the physician, nurse, emergency medical technician and other medical practitioners encountered during venipuncture [37], intravenous (IV) drug delivery [32] and cannulation. This is usually due to the following reasons; veins are either very small, and/or deep, the patient’s age (elderly or pediatrics), skin color [37], and obesity level [32,35]. It often results in multiple attempts in needle insertion leading to pain, discomfort, dissatisfaction, delayed treatment [37], hematoma, swell in the skin, cuts on the bone [39], bleeding, and even infection.…”

Section: Results and Analysismentioning

confidence: 99%

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Vein Pattern Locating Technology for Cannulation: A Review of the Low-Cost Vein Finder Prototypes Utilizing near Infrared (NIR) Light to Improve Peripheral Subcutaneous Vein Selection for Phlebotomy

Pan

Francisco

Yen

et al. 2019

Sensors

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One of the most common means for diagnosis is through medical laboratory testing, which primarily uses venous blood as a sample. This requires an invasive method by cannulation that needs proper vein selection. The use of a vein finder would help the phlebotomist to easily locate the vein, preventing possible pre-analytical error in the specimen collection and even more discomfort and pain to the patient. This paper is a review of the scientific publications on the different developed low-cost vein finder prototypes utilizing camera assisted near infrared (NIR) light technology. Methods: Electronic databases were searched online, these included PubMed (PMC), MEDLINE, Science Direct, ResearchGate, and Institute of Electrical and Electronics Engineers (IEEE) Xplore digital library. Specifically, publications with the terms vein finder prototype, NIR technology, vein detection, and infrared imaging were screened. In addition, reference lists were used to further review related publications. Results: Cannulation challenges medical practitioners because of the different factors that can be reduced by the utilization of a vein finder. A limited number of publications regarding the assessment of personnel performing cannulation were observed. Moreover, variations in methodology, number of patients, type of patients according to their demographics and materials used in the assessment of the developed prototypes were noted. Some studies were limited with regard to the actual human testing of the prototype. Conclusions: The development of a low-cost effective near infrared (NIR) vein finder remains in the phase of improvement. Since, it is being challenged by different human factors, increasing the number of parameters and participants/human for actual testing of the prototypes must also be taken into consideration for possible commercialization. Finally, it was noted that publications regarding the assessment of the performance of phlebotomists using vein finders were limited.

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Section: Results and Analysismentioning

confidence: 99%

Section: Results and Analysismentioning

confidence: 99%

Section: Results and Analysismentioning

confidence: 99%

See 1 more Smart Citation

Vein Pattern Locating Technology for Cannulation: A Review of the Low-Cost Vein Finder Prototypes Utilizing near Infrared (NIR) Light to Improve Peripheral Subcutaneous Vein Selection for Phlebotomy

Pan

Francisco

Yen

et al. 2019

Sensors

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show abstract

“…Biometric systems for recognizing people are shown in Fig. 1, which incorporate fingerprint, iris, and face recognition, are pulling in consideration in light of the fact that customary strategies, for example, keys, passwords, and PIN numbers convey the dangers of being forgotten, stolen, or lost [11].…”

Section: Methodsmentioning

confidence: 99%

Enhanced Finger Vein Based Recognition System

Jumaah

Hussein

Rashad

2016

IJICIS

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Robust Recognition systems become more complicated over time. These systems are derived from features which can be extracted from different body members using extractor methods. Finger vein is suitable member that could be used to violate the weakness of finger print. Conventional extractor methods like matched filter and morphological methods can extricate patterns if the widths of veins are steady whereas repeated line tracking method extract vein patterns from a hazy picture. These strategies can't remove veins that are smaller extensive than the accepted widths which corrupts the precision of the individual recognizable proof or can't adequately extricate flimsy veins on the grounds. In turn, we have proposed a system that tackles these issues by checking the shape of the picture profiles and stressing just the centerlines of veins. Our system for distinguishing the most extreme bend positions is hearty against transient vacillations in vein width and splendor. This paper introduces a finger vein recognition system based on using histogram of gradient and multi class support vector machine and finger vein recognition is powered by using Gabor filter with classifier powered by multi class support vector machine. The proposed have great enhancement impact over relative to accuracy, sensitivity, F-measure and precision during evaluation.

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“…This property is exploited by different systems for the vascular detection, either by the transillumination or by reflectometry techniques. The first one consists to expose the forearm to an infrared light source to measure its transparence, however it has the inconvenience that the regions to process need to have the enough thickness to be traversed by the light, restricting its use to the hands and fingers [2][3]. For the reflectometry technique the infrared light is impinged to the exploring surface, which allows to be used regardless of the forearm complexion [4][5].…”

Section: Introductionmentioning

confidence: 99%

Forearm and Hand Vein Detection System for an Infrared Image Database

Azueto-Ríos¹,

Hernández-Gómez²,

Hernández-Santiago³

2016

RCS

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This paper presents a system that allows defining the vein patterns of a person's forearm and hand. In order to accomplish this, infrared (IR) images of the region of interest were registered. The main goal is to help in vein detection, to aid in procedures like intravenous catheter or venipuncture, in a non-invasive way. In the image acquisition protocol, the anterior and posterior compartments of the left and right forearms of each subject were considered to create an image database each one containing the anthropometric data of the subject. A GUI was developed to allow recording an image by gender, age, weight, high and blood group and to allow two filtering options; the standard histogram equalization or fuzzy equalization. Finally, the user is able to choose and apply one of the two classification methods: one using the Fuzzy C-means algorithm, and the other using a Bayesian probabilistic model.

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Low-cost subcutaneous vein detection system using ARM9 based single board computer

Cited by 19 publications

References 4 publications

Vein Pattern Locating Technology for Cannulation: A Review of the Low-Cost Vein Finder Prototypes Utilizing near Infrared (NIR) Light to Improve Peripheral Subcutaneous Vein Selection for Phlebotomy

Vein Pattern Locating Technology for Cannulation: A Review of the Low-Cost Vein Finder Prototypes Utilizing near Infrared (NIR) Light to Improve Peripheral Subcutaneous Vein Selection for Phlebotomy

Enhanced Finger Vein Based Recognition System

Forearm and Hand Vein Detection System for an Infrared Image Database

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