# Paper and Fiber-Based Bio-Diagnostic Platforms: Current Challenges and Future Needs
## 2 Major Challenges and Opportunities
### Readout Outcomes  
One of the critical steps in working with paper-/fiber-based devices is the ability to quantify the analytes of interest with minimal requirements. The major challenge, particularly when EPOC in remote/rural areas is the aim, is to achieve reasonably accurate bio-diagnosis without needing centralized clinical facilities and sophisticated, expensive equipment. In the context of on-site diagnosis, reliable quantitative or semi-quantitative readouts are anticipated to dictate the treatment by a simple \"yes/no\" or \"normal/abnormal\" responses [2; 120]. In this path, significant progress has been made. A variety of techniques, including colorimetry [120; 121; 122; 123], fluorescent [29; 123; 124; 125; 126; 127], luminescent [128], chemiluminiscent [128; 129], photo-electro-chemiluminiscent, electrochemical [130; 131], electro-chemiluminiscent [132; 133], and photo-electrochemical [134] detections have been reported for paper and/or fiber-based bio-diagnostic platforms [2; 3; 4; 135; 136]. In the case of fluorescence readout, an important question is: \"To what extent does the whiteness of the paper play a role in producing a background signal or perhaps participating in the bleaching effect?\". The most commonly-used analytical detection technique for paper/fiber-based devices is colorimetric (Table 2) [2; 3]. This analysis is known to be relatively straightforward; the color intensity is proportional to the concentration of the analyte; the operating time is relatively short, and the detectors are normally portable and inexpensive, while the technique is mainly compatible with smart devices [2]. The likelihood of telemedicine using digital cameras, cell phones, and smart devices was demonstrated since 2008 for glucose detection in artificial urine [137; 138]. Detection via smart devices has rapidly penetrated the worldwide market introducing tremendous opportunities for the on-site processing of data, instead of sample transfer to a centralized clinical facility (Table 2) [2; 57; 58; 59; 60; 61; 128; 139]. With their storage capacity, smart devices serve clinical practice well, enabling information to be collected and stored to a much greater extent than previously possible. Modern smart devices possess both a light source (LED flash) and a digital camera for detection; therefore they are capable of performing tasks that are normally performed by expensive techniques, such as fluorometers, spectrophotometers, or silicon photodetectors [140]. Novel attempts have also been dedicated to non-instrumented analysis or equipment-free detection techniques for fabricating easy-to-use paper-based devices that can play vital roles in EPOC [121]. Such strategies would reduce the cost of bio-diagnosis, while increasing the portability of the devices that do not require external readout instrumentation [141; 142]. One approach to perform equipment-free analysis relies upon color intensity comparators using an external calibration or standard calibration integrated within the device [143; 144]. [PERSON] et al. reported a cost-effective \"color barcode\" test for the rapid screening and quality control of pharmaceutical drugs [145]. The fabricated device was divided into twelve individual lanes, on which the solid pharmaceutical product was mounted and the edge dipped into the chosen media. Each lane specifically reacted to one type of analyte (e.g., ampicillin, amoxicillin, and rifampicin) and a corresponding colored lane, visually compared with the reference was indicative of a \"positive I.D.\" [145]. Another interesting study by [PERSON] et al. reported a self-calibrating sensor for glucose measurement. The tree-shaped, branched structure of the designed platform minimized the ambient effects, such as temperature and humidity [146]. [PERSON] et al. reported self-calibration of the device based on alteration of the incubation time [147]. This study suggests that the sensitivity of the device was in an acceptable range (84%), even though the readout outcome was semi-quantitative [147].