lab on a chip - the ozcan research...
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Lab on a Chip
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FRONTIER View Article OnlineView Journal
This journal is © The Royal Society of Chemistry 2014
Aydogan Ozcan
Dr. Aydogan Ozcan is theChancellor's Professor at UCLAleading the Bio- and Nano-Photonics Laboratory at theElectrical Engineering andBioengineering Departments.Dr. Ozcan holds 22 issuedpatents (all of which are licensed)and >15 pending patent appli-cations and is also the author ofone book and the co-author ofmore than 350 peer reviewedresearch articles in major scien-tific journals and conferences.
Dr. Ozcan is a Fellow of SPIE and OSA, and has received majorawards including the Presidential Early Career Award for Scientistsand Engineers (PECASE), SPIE Biophotonics Technology InnovatorAward, SPIE Early Career Achievement Award, ARO YoungInvestigator Award, NSF CAREER Award, NIH Director's NewInnovator Award, ONR Young Investigator Award, IEEE PhotonicsSociety Young Investigator Award and MIT's TR35 Award for hisseminal contributions to near-field and on-chip imaging, andtelemedicine based diagnostics.
a Electrical Engineering Department, University of California, Los Angeles, CA 90095,
USA. E-mail: [email protected]; Web: http://www.innovate.ee.ucla.edu,
http://org.ee.ucla.edu/; Tel: +1 (310) 825 0915b Bioengineering Department, University of California, Los Angeles, CA 90095, USAc California NanoSystems Institute (CNSI), University of California, Los Angeles,
CA 90095, USA
Cite this: DOI: 10.1039/c4lc00010b
Received 4th January 2014,Accepted 12th February 2014
DOI: 10.1039/c4lc00010b
www.rsc.org/loc
Mobile phones democratize and cultivatenext-generation imaging, diagnostics andmeasurement tools
Aydogan Ozcanabc
In this article, I discuss some of the emerging applications and the future opportunities and challenges
created by the use of mobile phones and their embedded components for the development of
next-generation imaging, sensing, diagnostics and measurement tools. The massive volume of mobile
phone users, which has now reached ~7 billion, drives the rapid improvements of the hardware, software
and high-end imaging and sensing technologies embedded in our phones, transforming the mobile
phone into a cost-effective and yet extremely powerful platform to run, e.g., biomedical tests, and
perform scientific measurements that would normally require advanced laboratory instruments. This
rapidly evolving and continuing trend will help us transform how medicine, engineering and sciences are
practiced and taught globally.
The history of wireless phones dates back to the beginningof the 20th century. Even in the 1940s, wireless phonesfor automobiles were commercially available.1 These earlierdesigns were much bulkier and more power hungry in additionto being analog, making them quite far away from our moderndigital cellphones that we carry in our pockets today. However,even then, it was predicted that mobile phones will be widespreadand carried by almost everyone. One interesting portrayal ofthis prediction was published in 1926 in a satirical magazineby Karl Arnold, a German painter, clearly showing that theidea of and the excitement around mobile phones have beenout there for almost a century now (see Fig. 1).1,2 Of course,these previous discussions and demonstrations were mostlylimited to wireless audio signal transmission and reception,and could not realistically portray the massive extent of today's“smartphones” together with their computational power, variousphysical sensors including high-end imagers/cameras and thedigital aspects of the “big” data that they can globally generateand share.3–6 For sure, at the beginning of the 20th century,it was extremely difficult, if not impossible, to predict the“internet” and without the internet it is very difficult to fullycomprehend the smartphone and what it globally enables.
In this article, I will focus on some of the emerginguses of mobile phones for imaging/microscopy, sensing anddiagnostics as well as general measurement science,7–41
which will fundamentally impact the future practices andeducation of medicine, engineering and sciences globally.There are several aspects that make today's mobile phonesrather unique for conducting sensing and diagnosticmeasurements/tests toward, for example, telemedicine, mobilehealth, point-of-care (POC) and environmental applications,
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Fig. 1 A cartoon published in 1926 portrays the future use of mobilephones.1,2
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among others, and below, I will detail some of these distinc-tive features.
Massive volume, cost-effectivenessand connectivity
Cellphones are cost-effective mostly due to their massivevolume of users. We had approximately 7 billion cellphonesubscribers in the world by the end of 2013, and this enor-mous volume makes the cellphone hardware and softwareextremely cost-effective and yet rather powerful and reliable,working almost anywhere in the world (see Fig. 2). In termsof high-end consumer electronics devices, besides mobilephones, there is simply no other platform that one canbroadly rely on and cost-effectively utilize all around the
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Fig. 2 (Left) Mobile phone subscription rates (per 100 people) in the worl2000, approximately 15 billion mobile phones have been sold, which is mref. 3 and 4.
globe. While a significant majority of these cellphones arenot yet smartphones, the penetration rates for smartphonesare constantly increasing worldwide (e.g., by the end of 2013,it had reached more than 55% per inhabitant in the US),3 andwith the rapid accumulation of second hand phones, onecan expect further acceleration in adoption of smartphonesglobally. These mobile phones, with their cost-effective andseemingly simple infrastructure, provide data connectivityto >90% of the world population, which permits digitalsampling, processing, reporting and sharing of the acquiredinformation (whether it is an image, a sensor output, a diag-nostic test result, etc.) both locally and globally.
High-end components embedded inmobile phones – the building blocksof next-generation imagers, sensorsand diagnostic tools running onmobile phones
In addition to their massive volume, cost-effectiveness, cover-age and data connectivity, rapid improvements that we haveexperienced in cellphone related technologies and componentsover the last decade can provide important insights to someof the unique capabilities that our cellphones currently have(see Fig. 3). One of the most interesting features/componentsinstalled on mobile phones that has been rapidly advancingis the opto-electronic image sensor. As a matter of fact, themega-pixel count of cellphone cameras has been doublingalmost every two years over the last decade, following thefamous Moore's Law, and it has now reached to more than40 mega-pixels (Fig. 3a).
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d. (Right) Mobile phone sales in the world as a function of time. Sinceore than 2-fold larger than the population of the world. Data sources:
Fig. 3 (a) A comparison of the mega-pixel count of mobile phones with the transistor count in central-processing-units (CPUs) of PCs. Thiscomparison shows that the pixel count of cellphone cameras has been following the Moore's Law, i.e., doubling almost every 2 years. (b) Theprocessor speed comparison between mobile phones and PCs. (c) Mobile phone network speeds for 1G, 2G, 3G and 4G networks are comparedagainst the average internet speed in the US in 2013. (d) The global average cost of data transmission over cellular networks is reported as afunction of time. Data sources: ref. 3–6.
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These advanced optical imagers on our cellphones providevarious opportunities to utilize the cellphone as a general pur-pose microscope7,9,10,12,14,16,19,27,35 that can even detect singleviruses29,38 on a chip. Microscopy is one of the most widelyused tools in sciences, engineering and medicine, and thecreation of high-end optical microscopy and imaging platformsthat are integrated onto cellphones is rather important fornot only telemedicine (e.g., telepathology, remote diagnostics),mobile health, POC and environmental monitoring applica-tions, but also for the democratization of measurement scienceand higher education. By creating cost-effective and yet power-ful micro- and nano-imaging interfaces on the cellphone orusing cellphone parts such as CMOS imager chips, researchersin the developing world can also find solutions to various mea-surement and testing needs of their research laboratories andhigher education institutions. This has been the focus ofsome of the emerging efforts on creating, e.g., lens-free com-putational microscopes on a chip,14,27,29 where the spatialresolution and field of view are decoupled from each other
This journal is © The Royal Society of Chemistry 2014
so that improved resolution and higher-throughput can beachieved at the same time using some of these next generationimage sensor chips that are installed on our smartphones.This also means that such lens-free computational micro-scopes literally ride on the Moore's curve (Fig. 3a), wheretheir performance (e.g., space–bandwidth product) literallydoubles almost every two years – a very interesting phenome-non that we have been experiencing for the first time in thehistory of optical microscopy.
Besides microscopy, these advanced imaging and opto-electronic or electronic sensing/sampling technologies embeddedin our cellphones can also be utilized for various telemedicine,POC and mobile health related applications including butnot limited to blood analysis and cytometry,17,33 detection ofbacteria or viruses,22,34,38,39 diagnosis of infectious diseases,24
monitoring of chronic patients (e.g., by testing urinary albumin,30
cholesterol,40 etc.), sensing of allergens,26 label-free detection ofprotein binding events,36 ultra-sound imaging,13 micro-NMRfor molecular analysis of tumor samples,18 electrochemical
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detection of parasites,32 monitoring of electrocardiogramrhythms,28 estimation of human eye refractive errors as wellas detection of cataracts,15,20 among many other applicationsas further detailed in ref. 41. In most of these applications,sample preparation through smart microfluidic42–49 chipdesigns is the key enabler for the success of mobile phonebased sensing and detection platforms. In this regard,lab-on-a-chip research can be considered to be one of thecore pillars for mobile microanalysis, which provides cost-effective, field-portable and rapid solutions to complex sam-ple handling, preparation and delivery steps, assisting withthe specificity and sensitivity of mobile phone based micro-analysis, sensing and diagnostic platforms.
Some of the other key components and technologiesembedded in mobile phones that we have seen dramaticimprovements over the last decade include faster processorsand higher bandwidth data transmission/receiver units(see Fig. 3) which altogether make the cellphone functionas a portable super-computer, with ample opportunities forparallel processing of the acquired data even locally, at yourpalm. Obviously, the connectivity and the rapidly improvingbandwidth of mobile phone telecommunication networks alsoenable data processing to be performed over remote serversthrough, e.g., cloud computing, which might especially besuitable for lower-end cellphones, i.e., only the processed finalresults could be communicated back to the phone users.In any case, the cellphone with its core-processors, dataconnectivity and bandwidth brings a remarkable computa-tional power to its users, which can be utilized for advancedimaging, sensing and diagnostics applications, among others.For telemedicine and field use of these cellphone based mea-surement/testing devices, this last feature is quite importantand essential; however, for POC and mobile health applica-tions that involve, e.g., home monitoring of chronic patients,other forms of data communication and signal processingmethods that involve local PCs and/or tablets could also beutilized in addition to the cellphone processors or the cloud.
Cost-effectiveness of this data exchange between a cell-phone based measurement tool and a remote server (e.g., forarchiving of test results or for advanced signal processingand further analysis) is also an important parameter to con-sider. Fortunately, while the mobile phone data rates havebeen getting significantly faster (Fig. 3c), the cost of wirelessdata transfer has also been globally reducing as illustrated inFig. 3d. This trend is likely to continue within the nextdecade which will give us further opportunities for radicalsimplification of our measurement and sensing tools runningon mobile phones and mitigating this simplicity with high-end computation that is performed on the cloud (in additionto the phone). This, I believe, will form an important stepin the democratization and cultivation of next-generationsensing and diagnostics technologies globally.
The above presented summary of the unique featuresand components of mobile phones is not meant to be acomprehensive list, and in fact there are other importantcomponents, including for example the digital screen, the
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accelerometer, the IR sensor, the projector, etc. that are alsobeing used in innovative ways to convert the mobile phonesinto advanced sensing and measurement platforms.15,41,50 Allof these emerging application areas of mobile phone basedplatforms in biomedicine and other fields of engineering andapplied sciences create a set of exciting prospects in additionto the challenges that await us in the future, some of whichwill be highlighted in the following sub-sections.
Big data created by mobile phonebased imaging, sensing anddiagnostic tools – the internet ofthe microworld
In addition to various applications discussed earlier, thesemobile phone based field-portable measurement tools arealso digitally connected to each other, forming a rapidlyexpanding network. Based on the advances in the broad useof cellphones for micro-analysis, imaging, and sensing,within the next decades, we can expect several orders of mag-nitude increase in the number of personal microscope anddiagnostic tool users globally. All of these cost-effective andubiquitous cellphone enabled devices designed for field-portable imaging, sensing and testing would generate highquality, sensitive and specific data from wherever they arebeing used, forming a global network, which I term as themicro-Internet (i.e., μ-Internet). This reminds me of the trans-formation that we have experienced from PCs to the internet:once made cost-effective and compact enough, PCs wereconnected to each other through telecommunication protocols,creating the backbone of the modern internet. Together withcrowd sourcing and social networks, today's internet canbe considered as a highly sophisticated “living and learning”system, where we have more than 180 billion email messagesevery day, together with >850 million unique websites, withhighly dynamic content.
Once fully scaled-up, this smart network of imagers, micro-analysis systems and diagnostic tools, i.e., the μ-Internet,might deliver a paradigm shift for, e.g., medical, environ-mental, and biological sciences, among others, through inno-vative uses of this network and its constantly expandingdatabase. For instance, by creating massive libraries of variousspecimens (e.g., microbial communities, parasites, pathologyslides, blood/sputum/pap smears, etc.), we would be able todynamically track both temporal and spatial evolution of dif-ferent species, diseases or infectious outbreaks, and be ableto better investigate and identify the cause–effect relationshipsof these spatio-temporal patterns at a much larger scale, pro-viding an important tool for especially epidemiology. Such arobust platform could even lead to better policy making locallyand globally for, e.g., health-care and environmental issues.
While these opportunities are endless and all very exciting,there is also a major challenge which is related to the fact thatour experts (e.g., medical doctors, diagnosticians, health-caretechnicians, micro-biologists, etc.) do not increase their
This journal is © The Royal Society of Chemistry 2014
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characterization, diagnosis and labeling throughput as muchas digital technologies increase their imaging/sensing andmeasurement throughput. As an example of the ultra-highthroughput that some of the emerging mobile phoneenabled technologies have, recently introduced computationalon-chip microscopes can routinely generate images that have1–2 billion useful pixels, where even single viruses can bedetected over large sample areas of, e.g., >0.2–10 cm2.27,29
This throughput mismatch between emerging digital mea-surement tools and human expertise creates a bottlenecksince more and more data that need to be classified/sortedand diagnosed will start to pile up as human expertise doesnot scale up as our digital tools do. This challenge, however,can potentially be mitigated by coupling μ-Internet databasewith machine-learning, crowd-sourcing and smart gamingstrategies (see, e.g., ref. 51–52), which might lead to a self-learning hybrid network (machine + human) that gets muchbetter in automated identification, classification and diagnosticanalysis of new generated data of various specimens, whetherit is, e.g., a bodily fluid, a histopathology slide or water/foodsample. Once successful and scaled-up, this self-learning net-work of cellphone enabled micro-analysis tools and its con-stantly expanding database could be a priceless global assetfor a variety of medical, environmental and biological appli-cations for both the developed and the developing world.
The future of Moore's Law andstandardization of mobile phonebased diagnostic and measurementtools
Moore's Law at its origin is related to the dimensions of atransistor in an integrated circuit. Since we are approachingthe physical limits in terms of the size that can still governreliable switching operation in a transistor design, thereare heated debates on how long Moore's Law can effectivelycontinue. This technical discussion is beyond the scope ofthis article, and as far as this manuscript is concerned, weare broadly using the term Moore's Law to refer to the rapidadvances in digital technologies, even extending it to, forexample, the mega-pixel count of mobile phone cameras asdepicted in Fig. 3a. For us, the important and relevant ques-tion is: Can this rapid trend and its impact on different compo-nents in consumer electronics devices including cellphonescontinue in the next decades?
There may not be a clear and globally correct answer to thisquestion covering all the embedded technologies/componentsin mobile phones and other electronics devices. However,the consumer electronics market has been one of the maindrivers and the economic forces behind Moore's Law and itsdirect impact on the rapid evolution of mobile phones. There-fore, with the increasing buying power globally, a continuinggrowth in the number of mobile phones in the world can beexpected, which will also create a very large pool of second-hand phones (see, e.g., the global evolution of mobile phone
This journal is © The Royal Society of Chemistry 2014
sales reported in Fig. 2, which illustrates that since 2000,approximately 15 billion mobile phones have been sold). Allof these factors will most likely continue to lower the overallcosts for mobile phone based technologies, despite the majortechnological improvements that they go through almostevery year.
On the other hand, this rapid pace of advances in the con-sumer electronics market also creates major challenges forstandardization of mobile phone based imaging, sensing anddiagnostics tools and technologies. Considering the fact thatthe regulatory approval processes in biomedical device indus-try are rather cumbersome, costly and time consuming, theserapid changes in the hardware and/or software of our mobilephones can become a major limitation for commercializationefforts toward, e.g., telemedicine, POC and mobile healthrelated applications of cellphone based tools. This obstaclecan be potentially addressed by new business ideas that turnthe challenge into an opportunity; for example, a consortiumthat is formed to provide the industry with standardized andregulated supply of certain mobile phones and/or mobilephone components could be a possible solution. Anotherpotential solution toward this challenge could be the system-atic development and standardization of open software andhardware platforms for mobile phones, such as the AndroidOS and the recently announced Project Ara53 (through thecollaboration of Motorola and Phonebloks54), respectively.
Wearable computers
In addition to mobile phones, other emerging consumerelectronics devices, especially wearable computers such asGoogle Glass, Samsung Smartwatch and others, might alsoplay important roles in the future practices and designs ofnext-generation mobile health, telemedicine and POC tools.Most of these wearable computers and telecommunicationdevices will share similar embedded components and tech-nologies as found in our smartphones. However, their userand data collection/sharing interfaces might provide newprospects that mobile phones do not currently have. Onesuch example is Google Glass (Fig. 4), where its hands-freeaugmented reality environment can be explored in variousbiomedical and/or environmental imaging and sensing appli-cations including, for example, pathological investigation ofsamples. One of the first examples of this exciting opportunityhas been recently demonstrated through the use of GoogleGlass for digital reading and quantification of nanoparticlebased immunochromatographic diagnostic tests where acustom-written Glass application was created to image oneor more of these diagnostics tests labelled with QuickResponse (QR) code identifiers using the hands-free andvoice-controlled user interface of Google Glass (see Fig. 4).The acquired Glass images are then transmitted to a serverfor rapid digital processing and quantification of testresults with, e.g., a few parts per billion (ppb) level ofdetection limit.56
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Fig. 4 (Top) Components of Google Glass.55 (Bottom) Google Glassbased imaging and quantification of immuno-chromatographic diagnostictests. For more details, refer to ref. 56.
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As another possibility, in addition to the medical expert'sprofessional opinion, computer vision and machine learningtools running on the Google Glass platform can create real-time digital “flags” or “virtual maps” on the sample (e.g., apathology slide or live tissue) field of view assisting and guid-ing the medical personnel in their routine practice, makingthem more efficient and accurate in their professional assess-ments. Likewise, the same interface provided by Google Glassor similar wearable computers could also be utilized for real-time sharing of and consultation on medical images, alongwith additional related data, with other experts for remotediagnosis and telemedicine. These emerging opportunitiesprovided by wearable computers could be quite valuable forsurgeons (during surgery), pathologists, micro-biologists,diagnosticians, among other professionals.
In addition to experts, such wearable computers couldalso create new interfaces for individuals to self-monitor orroutinely test/measure their own health status, behaviour orthe environmental conditions (e.g., pollution). In this regard,I highly value all of these recently emerging smart consumerelectronics devices, following the successful footsteps of
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mobile phones, since they will continue to bring highlysophisticated digital technologies to the masses within cost-effective and compact platforms with the potential to radi-cally transform the future practices of medicine, engineeringand sciences globally.
Democratization of science,engineering and medical researchand education
As detailed earlier, the use of cellphones for the developmentof next generation imaging, sensing and diagnostics toolsopens up numerous opportunities and new applications,partially bringing the functions of advanced laboratoryinstruments to field conditions, resource limited settings andeven to homes within compact and cost-effective embodiments.While this is very exciting, another major impact that this direc-tion will generate is the democratization of science, engineeringand medical research and education. Through these next gener-ation technologies and measurement devices/tools that rely onmobile phones as well as other consumer electronics hardwareand/or software, researchers and educators will find new pros-pects to conduct scientific experiments that would normallybe beyond their reach. This might result in better research out-comes in developing countries by empowering their researchlabs and institutions with much more cost-effective and yetquite powerful measurement and analysis tools. Furthermore,the same consumer electronics driven cost-effective scientificmeasurement modules could also assist educators to improvethe quality of higher education by providing various hands-onlearning experiences to their students, significantly enrichingthe existing curriculum. This might considerably boost theoverall quality of the training and the education that the stu-dents in medicine, engineering and sciences receive in thedeveloping world, potentially helping to democratize and culti-vate research and education globally.
In summary, mobile phones will change the way thatimaging, sensing and diagnostic measurements/tests areconducted, fundamentally impacting the existing practices inmedicine, engineering and sciences, while also creating newones. This transformation will also democratize high-endmeasurement and testing tools worldwide, which might sig-nificantly improve research and education institutions, espe-cially in developing countries.
Conflicts of interest statement
A. O. is the co-founder of a start-up company (Holomic LLC)that aims to commercialize computational microscopy anddiagnostics tools.
Acknowledgements
Ozcan Research Group at UCLA gratefully acknowledges thesupport of the Presidential Early Career Award for Scientists
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and Engineers (PECASE), the Army Research Office (ARO) LifeSciences Division, the ARO Young Investigator Award, theNational Science Foundation (NSF) CAREER Award, the NSFCBET Division Biophotonics Program, the NSF EmergingFrontiers in Research and Innovation (EFRI) Award, the Officeof Naval Research (ONR) and the National Institutes of Health(NIH) Director's New Innovator Award DP2OD006427 fromthe Office of the Director, National Institutes of Health. A.O.also acknowledges Wei Luo, Faizan Shabbir, Jiarui Renandand Steve Feng of UCLA for their assistance with the figuresand the data.
Notes and references
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