Examination results of leukocytes and nitrites in the early detection of Urinary Tract Infection

Sarno, Riyanarto; Christian, Kevin; Ginardi, Raden Venantius Hari; Sunaryono, Dwi

doi:10.1109/ic3ina.2015.7377744

Cited by 1 publication

(1 citation statement)

References 3 publications

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“…Recently there has been an amount of work published regarding point-of-care devices. These include the novel use of capacitive touch screens to detect urinary tract infection (UTI) to create a point-of-care device [74] , the use of a long-range surface plasmon-polariton (LRSPP) waveguide biosensor for UTI detection [75] , the use of Surface enhanced Raman Spectroscopy (SERS) to test for UTIs [76] , a number of smartphone-based strip colorimetric detection systems used to remove the subjectivity of results interpretation [77] – [79] (although these are inherently affected by ambient light conditions and require significant post processing), etc.…”

Section: Introductionmentioning

confidence: 99%

A Community-Based IoT Personalized Wireless Healthcare Solution Trial

Catherwood

Steele

Little³

et al. 2018

IEEE J. Transl. Eng. Health Med.

118

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This paper presents an advanced Internet of Things point-of-care bio-fluid analyzer; a LoRa/Bluetooth-enabled electronic reader for biomedical strip-based diagnostics system for personalized monitoring. We undertake test simulations (technology trial without patient subjects) to demonstrate potential of long-range analysis, using a disposable test ‘key’ and companion Android app to form a diagnostic platform suitable for remote point-of-care screening for urinary tract infection (UTI). The 868 MHz LoRaWAN-enabled personalized monitor demonstrated sound potential with UTI test results being correctly diagnosed and transmitted to a remote secure cloud server in every case. Tests ranged over distances of 1.1–6.0 Km with radio path losses from 119–141 dB. All tests conducted were correctly and robustly received at the base station and relayed to the secure server for inspection. The UTI test strips were visually inspected for correct diagnosis based on color change and verified as 100% accurate. Results from testing across a number of regions indicate that such an Internet of Things medical solution is a robust and simple way to deliver next generation community-based smart diagnostics and disease management to best benefit patients and clinical staff alike. This significant step can be applied to any type of home or region, particularly those lacking suitable mobile signals, broadband connections, or even landlines. It brings subscription-free long-range bio-telemetry to healthcare providers and offers savings on regular clinician home visits or frequent clinic visits by the chronically ill. This paper highlights practical hurdles in establishing an Internet of Medical Things network, assisting informed deployment of similar future systems.

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