Overall, this investigation developed a portable, lightweight fluorescence imaging device for the detection of traumatic brain injuries. To a sufficient extent, the arrangement of LED lights, increasing signal-to-noise-ratio and portability were optimized. Nevertheless, certain improvements can be made over the long term.
It is critical to assess the current strengths and weaknesses, as well as potential threats, of the existing device to identify further improvements to be made.
Since the device inherently is involved with compatibility to the camera of the mobile phones, specific specifications must be made to account for performance differences based on phone model. Thus, the effectiveness of the prototype may be limited to the phone the prototype is created for. Excitation and emission filters are designed for larger devices; therefore, it may be expensive and challenging to find miniature filters to use within our device. The prototype may offer low sensitivity or low accuracy in the detection of TBI due to a poor light source or inconsistent capture from mobile phones.
Moreover, fabrication of the device is heavily dependent on 3D printing. Disruptions, such as the COVID-19 pandemic, may hinder ability to deliver adequate units in a timely manner.
In addition, there is a lack of training data for the software algorithms thus decreasing reliability of TBI detection. Validation is limited by the ability to obtain large LFA samples from both control and TBI patients.
LFA samples require extraction of a blood sample from the patient via finger prick. It is critical to note that when dealing with blood prick/extraction, there is an increased risk of bloodborne viruses, and the procedure is invasive (could be painful). Thus, it is critical to ensure equipment is sterilized well and not contaminated. If not gathered directly by the team or mentor, the data will be given as a set of data taken from TBI patients. The need for a finger prick, however, hinders the ability to mass market this device.
The hardware itself does not pose a physical risk as the LEDs, filters, or 3D-printed case are all safe to handle, under the assumption that basic precaution has been taken during 3D-printed; all sharp edges have been filed down.
Online data collection and analysis may pose as a privacy and security threat for users. Thus, special care must be taken in enhancing data privacy. However, this is a greater concern for commercialization of the device as opposed to development of the prototype.
Prototype requires extensive testing. This may result in the team using large quantities of equipment to develop multiple devices. Furthermore, filters and LEDs with different characteristics will need to be tested. Thus, there might be large waste. This can be mitigated by returning or donating any items that remain. Our project involves testing on large amounts of LFA strips. The device does not contain a compartment to store or dispose of used strips. Thus, it is critical to throw away LFA strips or recycle them. Proper disposal is necessary, and enough instructions will be given with the device to promote proper disposal.
It is critical to remember that this diagnostic tool cannot be relied on solely, instead, a combination of quantitative and qualitative (cognitive) screening tools must be used to reliably diagnose brain injuries. It is essential to understand this device is simply a prototype that is meant to investigate the possible methods for quantifying TBI and analyzing biological processes inexpensively by testing for certain biomarkers.