Smartphone-based Human Hemoglobin Level Measurement Analyzing Pixel Intensity of a Fingertip Video on Different Color Spaces

Hasan, Kamrul; Haque, Munirul; Sakib, Nazmus; Love, Richard R.; Ahamed, Sheikh Iqbal

doi:10.1016/j.smhl.2017.11.003

Cited by 28 publications

(13 citation statements)

References 32 publications

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“…The patient sample considered has been considerably expanded and a new experiment has been presented by the same authors in [49]: people from different areas of the world have been taken into consideration to try to outline a general model that allows to better estimate the anemia. The same authors, in [50] present a prediction model of the hemoglobin level which demonstrates an accuracy of 95%. In this research work, RGB information extracted from a fingertip video, converted into different color spaces, and considering the hue, saturation, value, brightness, a*, b* and gray components were used.…”

Section: Estimation Of Anemia Through Fingertip Analysismentioning

confidence: 99%

Estimate of Anemia with New Non-Invasive Systems—A Moment of Reflection

et al. 2020

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Anemia is a global public health problem with major consequences for human health. About a quarter of the world population shows a hemoglobin concentration that is below the recommended thresholds. Non-invasive methods for monitoring and identifying potential risk of anemia and smartphone-based devices to perform this task are promising in addressing this pathology. We have considered some well-known studies carried out on this topic since the main purpose of this work was not to produce a review. The first group of papers describes the approaches for the clinical evaluation of anemia focused on different human exposed tissues, while we used a second group to overview some technologies, basic methods, and principles of operation of some devices and highlight some technical problems. Results extracted from the second group of papers examined were aggregated in two comparison tables. A growing interest in this topic is demonstrated by the increasing number of papers published recently. We believe we have identified several critical issues in the published studies, including those published by us. Just as an example, in many papers the dataset used is not described. With this paper we wish to open a discussion on these issues. Few papers have been sufficient to highlight differences in the experimental conditions and this makes the comparison of the results difficult. Differences are also found in the identification of the regions of interest in the tissue, descriptions of the datasets, and other boundary conditions. These critical issues are discussed together with open problems and common mistakes that probably we are making. We propose the definition of a road-map and a common agenda for research on this topic. In this sense, we want to highlight here some issues that seem worthy of common discussion and the subject of synergistic agreements. This paper, and in particular, the discussion could be the starting point for an open debate about the dissemination of our experiments and pave the way for further updates and improvements of what we have outlined.

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Section: Estimation Of Anemia Through Fingertip Analysismentioning

confidence: 99%

Estimate of Anemia with New Non-Invasive Systems—A Moment of Reflection

et al. 2020

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“…In terms of analysis, common functions for SBI systems include image review/consultation, 91 , 95 region of interest selection, 19 , 96 colorimetric quantification, 73 , 97 intensity measurements, 6 , 98 , 99 diagnostic classification, 65 , 71 , 90 , 100 and segmentation of tissue structures. 14 , 15 , 55 , 101 However, implementing custom image analysis routines on smartphone operating systems requires substantial programming expertise, leading researchers to continue to rely on manual image processing workflows.…”

Section: System Interface Designmentioning

confidence: 99%

Smartphone-based imaging systems for medical applications: a critical review

2021

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. Significance: Smartphones come with an enormous array of functionality and are being more widely utilized with specialized attachments in a range of healthcare applications. A review of key developments and uses, with an assessment of strengths/limitations in various clinical workflows, was completed. Aim: Our review studies how smartphone-based imaging (SBI) systems are designed and tested for specialized applications in medicine and healthcare. An evaluation of current research studies is used to provide guidelines for improving the impact of these research advances. Approach: First, the established and emerging smartphone capabilities that can be leveraged for biomedical imaging are detailed. Then, methods and materials for fabrication of optical, mechanical, and electrical interface components are summarized. Recent systems were categorized into four groups based on their intended application and clinical workflow: ex vivo diagnostic, in vivo diagnostic, monitoring, and treatment guidance. Lastly, strengths and limitations of current SBI systems within these various applications are discussed. Results: The native smartphone capabilities for biomedical imaging applications include cameras, touchscreens, networking, computation, 3D sensing, audio, and motion, in addition to commercial wearable peripheral devices. Through user-centered design of custom hardware and software interfaces, these capabilities have the potential to enable portable, easy-to-use, point-of-care biomedical imaging systems. However, due to barriers in programming of custom software and on-board image analysis pipelines, many research prototypes fail to achieve a prospective clinical evaluation as intended. Effective clinical use cases appear to be those in which handheld, noninvasive image guidance is needed and accommodated by the clinical workflow. Handheld systems for in vivo , multispectral, and quantitative fluorescence imaging are a promising development for diagnostic and treatment guidance applications. Conclusions: A holistic assessment of SBI systems must include interpretation of their value for intended clinical settings and how their implementations enable better workflow. A set of six guidelines are proposed to evaluate appropriateness of smartphone utilization in terms of clinical context, completeness, compactness, connectivity, cost, and claims. Ongoing work should prioritize realistic clinical assessments with quantitative and qualitative comparison to non-smartphone systems to clearly demonstrate the value of smartphone-based systems. Improved hardware design to accommodate the rapidly changing smartphone ecosystem, creation of open-source image acquisition and analysis pipelines, and adoption of robust calibration techniques to address phone-to-phone variability are three high priority areas to move SBI research forwar...

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“…With air pollution getting critical and series of technological advances over the years have allowed individuals to set up their own monitoring system that too at affordable cost and have been able to play a defining role in the way in which air pollution is being monitored. Amalgamation of smart phones with IoT has further cemented the role of IoT and has taken unmeasurable strides in the field of Bio medical applications [13], [14]. Private monitoring station have moved the perspective of air pollution monitoring to a micro level with a capacity to map whole of the world and have also allowed researchers to predict the climate pattern and have been able generate data which has allowed specific measures to be taken toward mitigating climate change.…”

Section: B the Socio-economic Side Of The Issuementioning

confidence: 99%

A Forecasting tool for Air Quality Monitoring Built up on Cloud and IoT

Hasan¹,

Chourasia²,

Asutkar³

2019

IJITEE

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Air pollution has turned to no less than a monster and is becoming notorious with every passing day. The human race has been solely responsible for taking the world to such a state. With ill effects of pollution becoming glaringly evident it has been instrumental in forcing the world to get up from the deep slumber and act out. Air quality monitoring is a process in which the quality of air is monitored and on the basis of recorded information, it is conveyed to general public about the quality of air they are breathing. Air pollution poses serious problems to persons suffering respiratory disorders and there is a necessity to provide such target group with a tool which helps them to be aware about the pollution scenario and also alarms them with the impending critical situation well in advance. It is elementary for them to avoid situations where in lies a chance of exposure to pollutants leading to attacks which could prove to be fatal at times. This advance information will go a long way in helping such target audience to minimize their exposure to pollutants and thereby helping them to mitigate their ordeal on exposure to pollutants. Apart from getting predictive alarm, it gives a fair idea of the existing pollution scenario to the targeted stakeholders. This work discusses the implementation of cloud based IoT system for air quality monitoring which is available as a web interface as well as in a form of an android application.The developed system uses Nitrogen Dioxide, Sulphur dioxide, Particulate Matter 10 micrometers or less in diameter (P.M.10) sensors along with the temperature and the humidity sensors to form a wireless sensor node. An android application has also been developed which can be installed by the user. Once registered the user can access the data from the application which allows the users to observe the data of sensors along with the air quality index (AQI) and also provide the registered user with an alarm notification one day in advance about the probable level of pollutants as well as the AQI.a

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Smartphone-based Human Hemoglobin Level Measurement Analyzing Pixel Intensity of a Fingertip Video on Different Color Spaces

Cited by 28 publications

References 32 publications

Estimate of Anemia with New Non-Invasive Systems—A Moment of Reflection

Estimate of Anemia with New Non-Invasive Systems—A Moment of Reflection

Smartphone-based imaging systems for medical applications: a critical review

A Forecasting tool for Air Quality Monitoring Built up on Cloud and IoT

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