3D-Printed Portable Robotic Mobile Microscope for Remote Diagnosis of Global Health Diseases

García-Villena, Jaime; Torres, J.E.; Aguilar, C.; Lin, Lin; Bermejo-Peláez, David; Dacal, Elena; Mousa, Adriana; Ortega, María del Pilar Santacruz; Martínez, Álvaro; Vladimirov, A. P.; Cuadrado, Daniel; Postigo, Milagros; Ordi, Jaume; Bassat, Quique; Salamanca, Javier; Rodríguez‐Peralto, José Luis; Linares, María; Ortuño, Juan E.; Ledesma-Carbayo, María J.; Santos, A.; Luengo-Oroz, Miguel

doi:10.3390/electronics10192408

Cited by 12 publications

(6 citation statements)

References 36 publications

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“…On the other hand, in remote high burden settings, mobile phone and SMS-based technologies are emergent enabling tools to increase the rate of case detection by improving the efficacy of specimen collection and reporting results of acid-fast bacilli (AFB) microscopy, or to improve reporting and management for rapid diagnostic testing of HIV and malaria [ 12 , 13 ]. Such system could be operationalized obtaining images from a mobile microscope system [ 14 , 15 ] and the distribution of images through the internet via the mobile network, provided that there is connectivity which might not be the case in remote and rural environments. Moreover, it would be necessary to include a step to identify color blindness, or develop alternative representations for wider accessibility, as the analysis could be altered if this disease is considered.…”

Section: Resultsmentioning

confidence: 99%

Remote analysis of sputum smears for mycobacterium tuberculosis quantification using digital crowdsourcing

Delgado

Postigo²,

Cuadrado³

et al. 2022

PLoS ONE

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Worldwide, TB is one of the top 10 causes of death and the leading cause from a single infectious agent. Although the development and roll out of Xpert MTB/RIF has recently become a major breakthrough in the field of TB diagnosis, smear microscopy remains the most widely used method for TB diagnosis, especially in low- and middle-income countries. This research tests the feasibility of a crowdsourced approach to tuberculosis image analysis. In particular, we investigated whether anonymous volunteers with no prior experience would be able to count acid-fast bacilli in digitized images of sputum smears by playing an online game. Following this approach 1790 people identified the acid-fast bacilli present in 60 digitized images, the best overall performance was obtained with a specific number of combined analysis from different players and the performance was evaluated with the F1 score, sensitivity and positive predictive value, reaching values of 0.933, 0.968 and 0.91, respectively.

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Section: Resultsmentioning

confidence: 99%

Remote analysis of sputum smears for mycobacterium tuberculosis quantification using digital crowdsourcing

Delgado

Postigo²,

Cuadrado³

et al. 2022

PLoS ONE

Self Cite

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“…These available hardware and software environments provide the base condition for developing computational, portable and low-cost microscopes. Briefly, this is the best era for POCT and tele-diagnosis [ 124 , 125 , 126 , 127 ]. It is believable that more ideas and innovations for developing computational, portable and low-cost microscopes for POCT and tele-diagnosis would boom.…”

Section: Discussionmentioning

confidence: 99%

Computational Portable Microscopes for Point-of-Care-Test and Tele-Diagnosis

Bian

Xing

Jiao

et al. 2022

Cells

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In bio-medical mobile workstations, e.g., the prevention of epidemic viruses/bacteria, outdoor field medical treatment and bio-chemical pollution monitoring, the conventional bench-top microscopic imaging equipment is limited. The comprehensive multi-mode (bright/dark field imaging, fluorescence excitation imaging, polarized light imaging, and differential interference microscopy imaging, etc.) biomedical microscopy imaging systems are generally large in size and expensive. They also require professional operation, which means high labor-cost, money-cost and time-cost. These characteristics prevent them from being applied in bio-medical mobile workstations. The bio-medical mobile workstations need microscopy systems which are inexpensive and able to handle fast, timely and large-scale deployment. The development of lightweight, low-cost and portable microscopic imaging devices can meet these demands. Presently, for the increasing needs of point-of-care-test and tele-diagnosis, high-performance computational portable microscopes are widely developed. Bluetooth modules, WLAN modules and 3G/4G/5G modules generally feature very small sizes and low prices. And industrial imaging lens, microscopy objective lens, and CMOS/CCD photoelectric image sensors are also available in small sizes and at low prices. Here we review and discuss these typical computational, portable and low-cost microscopes by refined specifications and schematics, from the aspect of optics, electronic, algorithms principle and typical bio-medical applications.

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“…System features were represented in Table 4. Several state-of-the-art published systems were selected in order to be compared with our purpose in terms of: pieces materials, image acquisition, autofocus, cost, camera settings, point of care design and power requirements [13,[17][18][19][20].…”

Section: Plos Onementioning

confidence: 99%

Development of a low-cost robotized 3D-prototype for automated optical microscopy diagnosis: An open-source system

Dantas de Oliveira,

Rubio Maturana,

Zarzuela Serrat

et al. 2024

PLoS ONE

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In a clinical context, conventional optical microscopy is commonly used for the visualization of biological samples for diagnosis. However, the availability of molecular techniques and rapid diagnostic tests are reducing the use of conventional microscopy, and consequently the number of experienced professionals starts to decrease. Moreover, the continuous visualization during long periods of time through an optical microscope could affect the final diagnosis results due to induced human errors and fatigue. Therefore, microscopy automation is a challenge to be achieved and address this problem. The aim of the study is to develop a low-cost automated system for the visualization of microbiological/parasitological samples by using a conventional optical microscope, and specially designed for its implementation in resource-poor settings laboratories. A 3D-prototype to automate the majority of conventional optical microscopes was designed. Pieces were built with 3D-printing technology and polylactic acid biodegradable material with Tinkercad/Ultimaker Cura 5.1 slicing softwares. The system’s components were divided into three subgroups: microscope stage pieces, storage/autofocus-pieces, and smartphone pieces. The prototype is based on servo motors, controlled by Arduino open-source electronic platform, to emulate the X-Y and auto-focus (Z) movements of the microscope. An average time of 27.00 ± 2.58 seconds is required to auto-focus a single FoV. Auto-focus evaluation demonstrates a mean average maximum Laplacian value of 11.83 with tested images. The whole automation process is controlled by a smartphone device, which is responsible for acquiring images for further diagnosis via convolutional neural networks. The prototype is specially designed for resource-poor settings, where microscopy diagnosis is still a routine process. The coalescence between convolutional neural network predictive models and the automation of the movements of a conventional optical microscope confer the system a wide range of image-based diagnosis applications. The accessibility of the system could help improve diagnostics and provide new tools to laboratories worldwide.

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3D-Printed Portable Robotic Mobile Microscope for Remote Diagnosis of Global Health Diseases

Cited by 12 publications

References 36 publications

Remote analysis of sputum smears for mycobacterium tuberculosis quantification using digital crowdsourcing

Remote analysis of sputum smears for mycobacterium tuberculosis quantification using digital crowdsourcing

Computational Portable Microscopes for Point-of-Care-Test and Tele-Diagnosis

Development of a low-cost robotized 3D-prototype for automated optical microscopy diagnosis: An open-source system

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