Scientific (Phone) Applications and Mobile Devices

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We are pleased to announce that the Founding Editor-in-Chief's APD lab won Bronze in the inaugural Merck Connectivity Challenge, a new challenge by a large pharma recognizing the importance of smartphone apps and IoT devices in daily laboratories and how they can enable and improve them. A number of the apps in the winning solution are published in this journal itself! This demonstrates that the vision behind setting up the journal is now gaining traction and recognition after a good number of years.

For articles that were published before 31st March 2018, please refer to Springer Nature website at
New articles will be published here with effect from 1st April 2018.

Aims & Scope

Scientific (Phone) Applications and Mobile Devices is a peer-reviewed open access journal published under APD SKEG Pte Ltd. The first specialized journal in this field, it publishes highquality scientific reports on mobile apps and smartphone dependent devices such as add-on sensors or modifications. Allowing for not only academic recognition for the broader scientific community, it also brings awareness to the general public on the development of such tools.

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Latest Articles Browse all Articles

Research Article

Christopher Hui-Kang Nah,Weiling Wu , Samuel Ken-En Gan , Scott Wei-Gen Wong

‘Antigen Rapid Test’ Image-Processing based Machine Learning Algorithm for ART Buddy

Published on 28 March 2022

2021 witnessed subsequent waves of COVID-19 sweeping across the world. As the number of daily cases rose in many countries, many adopted the utilization of antigen rapid test (ART) kits for faster detection and isolation of the infected. However, the accuracy of the ART can be impacted by incorrect usage and self-reporting biases. Despite self-administration, image processing of submitted images could be leveraged for validation. Given the ubiquitous use of the smartphone camera, mobile applications that included features such as user uploading of ART kit result images, facilitate verification by backend servers against incorrect self-reported ART results while improving compliance rates. For this purpose, we describe an algorithm that was incorporated into the ‘ART Buddy’ app for the classification of submitted positive and negative ART images. The algorithm was based on machine learning using the Convolutional Neural Network (CNN) to achieve an accuracy of 97.57%, precision of 79.31%, and recall of 88.46%.

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Application Notes

Weiling Wu,Zealyn Shi-Lin Heng2, , Samuel Ken-En Gan

Application Notes: APD Handwash Android App – A tool for evaluating the effectiveness of handwashing

Published on 08 September 2021

Handwashing is a basic infection control practice that needs to be performed correctly to be effective. In the ongoing COVID-19 pandemic, its correct practice is emphasized by public health institutions. However, turning a practice into a habit requires acceptance for adoption of the twenty-second proper procedure to which difficulty remains. To promote and convince the average user, we developed the “APD Handwash app” as a home-use demonstration/education tool to the pitfalls and need of proper handwashing practices through the detection of assigned clean or dirty areas on the hand in a quantitative manner to provide a gauge to the effectiveness of washing when used before and after washing.

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Application Notes

Zhen-Yi Chew,Weiling Wu , Samuel Ken-En Gan

Application Notes - APD LAMP Diagnostic App: Automated Colorimetric Analysis and Documentation

Published on 17 March 2021

Amidst rapid diagnostic kits, reverse transcription loop-mediated isothermal amplification (RT-LAMP) has emerged as a rapid point-of-care testing (POCT) method during the COVID-19 pandemic. While many POCT kits rely on plate readers or visual classifications, these processes require experienced staff, and with the use of plate readers, the need for peripheral equipment and infrastructure as well. To address the gap and ensure objectivity in colorimetric POCT kits, the Automated Product Determination (APD) LAMP Diagnostic App was developed for automatic colorimetric analysis of single to multiple LAMP samples. Leveraging on the smartphone camera, barcode-based documentation feature, and a colour distance formula, the app algorithm calculates RGB values, labelling samples as “positive” when yellow, “negative” when pink, and “unknown” when orange. The APD Lamp diagnostic app for Android hereby demonstrates the integration of smartphone apps in POCT kits and ways the smartphone revolution changes laboratory processes to be timely and on-the-go.

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Application Notes

Khye-Chun Liew,Kenneth Wen-Jun Kui , Weiling Wu , Samuel Ken-En Gan

Application Notes: PsychVey Ver2 – Improving online survey data collection

Published on 17 September 2020

Surveys are an instrumental way in which researchers and scientists can gather data. With increasing reliance of digital solutions, manual surveys utilizing pen and paper are increasingly rare in the technologically connected world. Previously, we released the PsychVey web application platform to facilitate easy management of surveys for faster, more convenient and secure data collection. In the new PsychVey Ver.2, there is now a new user interface, automated email notification, auto-marking, display of pictures, uploading of documents and an improved search feature. To allow cross-platforms, PsychVey Ver2 has improved mobile-browser compatibility and speed.

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Samuel Ken-En Gan

“Set My Scientists Free” - Scientific Phone Apps and DIY equipment during lockdowns

Published on 14 April 2020

The SARS-CoV2 pandemic of year 2020 caused unprecedented disruptions globally. With lockdowns implemented in many countries, scientific research such as biomedical sciences, experienced major disruptions including in the supply chains of research materials.

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ISSN: 2364-4958