CISC 498
Information Technology Project

School of Computing

Proposed Projects 2017-2018

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This page lists potential projects proposed by customers from across the university and Kingston community. This year we have many anxious customers who can use your help! You may choose to pursue one of these projects, or find a customer and project of your own, possibly related to clubs or organizations you are involved with.

Projects from past years developed the Queen's Community Service Learning web portal, project management and secure reporting system, the Queen's squash court booking system, a particle size analysis system for Geology, an artifact archival and secure access system for Classics, and many other systems. Ideally your project should create a software system or product that can serve the customer for many years to come.

A good project will normally involve a human interface (such as a web portal), a persistent database, user roles, secure access isssues, and multiple technologies for you to learn about. But it can also be a challenging computational system or data management problem - it's up to you.

Each group must claim a different project inform the course coordinator as soon as possible. Before claiming a project, you can contact the corresponding customer of the project to better understand the software system needs.

1. iOS Patient Kiosk

Customer: Stephen LaHaye, Department of Medicine, Queen's University

The aim of this project is to develop a web application service that can be used by patients to enter their personal health information into an iPad, so as to facilitate point of care electronic entry of patient health information.  The application should allow the clinicians to create new questionnaires, that serve their particular clinical needs, by either customizing content from the existing library of questions, or by creating new content via templates.  The project will require the creation of a bidirectional API to allow for EMRs to “trigger” questions, and to allow the Patient Kiosk to report questionnaire results back to the EMR.  

2. The use of an electronic booking system for the optimization of cardiac procedures for patients 

Customer: BM Glover, Director, Heart Rhythm Services, Queen's University

Currently patients are booked in for cardiac procedures using a paper booking form which is filed in the patients chart by the doctor and sent to the secretary who then forwards this to a coordinator who uses a calendar to allocate times for the procedure. The allocation depends on a number of factors including the procedure type, symptoms, operator availability. The patient then waits for their procedure until they are called by telephone by the coordinator. The operator then receives a physical list of cases for the following week. This system has many problems including the ability to physically lose data, the lack of information available to the operator, the lack of live data in the clinic for the patient and the potential for cancellations on the day of the procedure due to these factors. We would therefore like to look at a computerized system which would help book the patient electronically, provide secure data transmission and storage and allow easy access for the operators. This would have a genuine impact on the efficacy of the service and would improve the overall quality of patient care.

3.  Morbidity and Mortality Database for the Division of General Surgery at Kingston Health Sciences Centre

Customer: Sunil Patel, Hotel Dieu Hospital, Kingston

Morbidity and Mortality documentation is an important aspect of quality assurance within the field of medicine. The purpose of this project is to develop an interactive database that will allow us to log and report on the morbidities and mortalities within our division.  This information is used to identify complications that could be preventable and institute individual and systemic changes to reduce complications in the future. The proposed project would be one that creates a database that would be accessible to a number of users.  Users would input data on the previous week’s complications, including patient information, surgeon information, type of procedure, type of complications and seriousness of the complication.  In addition, hospital administrators will upload data on the number and types of procedures done during the previous month.  Data will then be reported in the form of complication rates.

4. Colorectal Cancer Patient Triage Database

Customer: Sunil Patel, Hotel Dieu Hospital, Kingston

Colorectal Cancer is among the most common cancers diagnosed within Canada.  In Kingston, we receive between 10 – 20 new colorectal cancer referrals per month.  It is important that these patients are seen in a timely manner, have all appropriate tests completed and have surgery scheduled within an appropriate period. The proposed project would create an interactive, shared database to log new cancer referrals, identify which tests need to be arranged and document adherence to wait time benchmarks. The database needs to be accessible remotely and by a number of users.  Alerts should be generated when testing is incomplete or when proposed surgical dates fall outside of recommended benchmarks.

5. CHEM Time Reporting Database

Customer: Barbara Armstrong, Department of Chemistry, Queen's University

The Department of Chemistry is currently in need of a new system to track Time Reporting. Our current Time Reporting process involves gathering time reporting FIPPA sensitive reports for an excel spreadsheet, recording these preferences into an Human Resources database and reporting these results to the Head of the Department and Manager. Individual spreadsheets with unique formulas are required to handle the many different Union requirements in Queen’s . Ideally, the new system would be able to pre-fill the Time Reporting form, with information cascading down to other prefilled spreadsheets, with a web-based application. Also, a system that can easily be flipped to a start a new year would create both an important historical/departmental record and create a consistent and transparent Time Reporting process.

6. Mouse Colony Management Database

Customer: Cortney Haird, Department of Biomedical and Molecular Science & Anesthesiology, Queen's University

The Ghasemlou lab maintains one of the largest mouse colonies at Queen's University. Currently the information for over 400 mice is maintained on several different Google Docs and excel files. The revised system should track each mouse by the following: which cage it is in, its personal ID number assigned by animal care, its litter number, as well as its strain, genotype, gender, age, and more. It should also track a medical history and notes for each mouse, as well as who is using it for which experiment. Breeding pairs will also need to be tracked by all of the above, plus when they have had litters, when the litters will need to be weaned, and how many litters they have had. The new system should incorporate a way to track a history of all animals that have been euthanized for the past 5 years. All of this information should be combined into one user friendly place, while still being able to self update certain information, and offer full access to the information, as well as limited access to only certain information depending on the user. Bonus if you can incorporate a requisition form for students in the lab to request mice they need for current experiments!

7. games4science


Customer: Jordan Poppenk, Department of Psychology and Centre for Neuroscience Studies, Queen's University


Our laboratory has created a number of “gamesperiment” video games and other online tasks that participants can complete at home, and that transmit scientific data to us for use in Psychology research. In general, participant data are more valuable the more games and tasks that each player completes, as this allows us to see how completion of one task predicts completion of another. We can’t pay large numbers of players to participate, so instead we are counting on players to engage for entertainment and social status. Accordingly, we wish to engineer a website “games4science” featuring a social infrastructure that promotes and credits participation in multiple games and tasks.

The particular social-technical infrastructure would be up to the team to design. However, the website would, critically, involve some way of keeping track of which games/tasks participants have already completed, and encouraging them to either improve their score (if applicable), see if their answers have changed after some period of time (as for questionnaires), or to complete related new tasks (we would love it if you would next complete gamesperiment “X”). The website would also need a way for administrators to add new experiments and to tell the system how to handle a given experiment (e.g., downloadable game vs. survey, point value for this experiment, repeatable/not-repeatable/repeatable after a certain duration, related to game Y, etc).

The social-technical infrastructure would reward participants for their participation, such as some virtual currency such as points, achievements, etc. Perhaps the reward system could also be “spendable” in some way. Innovation is welcomed. Players’ achievements and completed tasks should somehow be automatically associated with their profiles in such a way that it enhances their status in facilitated social communication with other players (e.g., a web forum using existing freeware installed on our server).

Currently, our experiments consist of video games built in Unity and distributed to players’ computers that transmitting data back to us; and web surveys built in LimeSurvey and hosted on our server. We currently use HTTPS POST with a simple PHP script to log results, but would need to be supplied with an API to transmit critical information such as “task X complete for player Z” and have this feed into the database.

The player web interface should be “cool” enough to attract and retain players. The site/database should also be possible to run on our lab’s Ubuntu 16.04 LTS server and the latest apache/PHP. However, we will need directions for scaling up our server infrastructure if the website becomes popular, along with some idea of what traffic volumes would necessitate scaling up when working with a standard 100Mbit/s campus ethernet connection.

8. A Sensor Platform for Motion Evaluation in a Clinical Setting

Customer: Patrick Costigan, School of Kinesiology and Health Studies, Queen's University

Tools that can accurately measure human movement need to be integrated into clinical practice to support decision making, track rehabilitation progress, and improve outcomes. Low cost, feature rich wearable sensors are going to be a part of the solution. In our current work, a simple triaxial accelerometer provided objective information on human motion that tracked the rehabilitation progress of patients recovering from anterior cruciate ligament surgery. To integrate these devices into the clinic we need software that can be used anywhere, is easy to use, has flexible data collection protocols and stores the data in a persistent database that can be easily but securely accessed. Coupling the wearable sensors with effective software and storage will create a base system that can be customized to measure human motion for a wide range of clinical applications. At present we are examining the Bluetooth Low Energy sensors from Mbient Labs (MetaMotionR), an open platform with community support. The software must collect data from multiple of these sensors and the data should be stored in a secure cloud-based service where it can be accessed for later processing. The data collection software should be easily configurable (changing sample rate, data types, number of sensors) for different applications. The system need not be responsible for data analysis or reporting but this feature could be added if time permits.

9. Data Secure Student Attendance Database

Customer:  Meghan E. Norris, Department of Psychology, Queen's University

The Queen’s University PSYC100 course has over 1900 students. These 1900 students each attend weekly labs. We have approximately 70 different lab sections. Attendance at the labs has been done in the past paper-and-pencil, resulting in a lot of sheets of paper. TAs then had to manually input attendance into OnQ, which adds extra administrative work to our teaching assistants. We are looking for a program where students could swipe their ID card to streamline attendance process. There are privacy concerns with this: ID cards contain other information beyond identity, data security is a concern.  As “consumers,” we want a way to electronically track lab attendance in a way that easily interfaces with OnQ, and that provides us with the level of data security acceptable to Queen’s University.

10. Developing an open source pharmacovigilance monitoring system for children and adolescents treated with antipsychotic medications

Customer: Katie Goldie and Sarosh Khalid-Khan, Faculty of Health Sciences (Psychiatry and Nursing), Queen's University

Despite drastic increases in antipsychotic medication prescribing in youth with psychiatric disorders, data is still limited regarding their safety in this vulnerable population, necessitating additional tools for capturing long-term, real world data. Software is needed to collect information about metabolic monitoring practices of children and adolescents taking SGAs to assist healthcare providers (both psychiatrists, primary care providers and nurses) enhance communication and medication safety. Interoperability with current EMRs and examination of existing platforms will be investigated.

11.  Automating Work Load Unit collection from an Access Genetics database within KGH

Customer:  Harriet Feilotter, Dept of Path and Mol Med, Queen's University

In the clinical laboratory at KGH, we are required to submit monthly metrics that measure the amount of working being done in the laboratory. The metric collected is known as a work load unit (WLU). Each activity that is done in the lab has been associated with a specific number of units.  Each individual working in the lab is expected to complete a minimum number of units per month.  Therefore, on a monthly basis, we collect information so we can submit the total number of work units completed.  These numbers are used by finance and the Ministry of Health to ensure a balance is maintained between our human resources, our budget and our incoming work.  Currently, we store information about the tests that we run in the hospital laboratory in an Access database known as Shire.  In order to extract the monthly WLUs, an individual in the laboratory must manually count the Access entries, calculate which activities they correspond to, calculate the WLUs associated with each activity, and then submit a total.  This takes an average of 3 full working days per month to complete.  We are interested in having an individual who can help us automate this process. 

12.  Designing a pipeline for storing variant information on patient samples to create a variant database that is searchable and exportable

Customer:  Harriet Feilotter, Dept of Path and Mol Med, Queen's University

In the clinical molecular laboratory at KGH, we frequently are asked to identify sequence variants in genes of interest using patient DNA.  Once variants are identified in a patient sample, we analyze the clinical impact of the variant using a number of databases and other sources of information.  The final output is information about the variant itself as well as the clinical impact of the variant and the evidence used to make that determination. Over the years, we have identified a large number of mutations in many individuals who have had samples sent to the laboratory. However, we have not developed a database that allows us to easily store, access and query the genetic information across all of our patients.  Currently, the information is stored in a variety of places, none of which are easily accessible.  Therefore, we have a limited ability to perform queries.  For instance, if we identify a mutation in a gene from a patient sample, it is not easy for us to determine whether we might have seen a similar or identical mutation earlier in another patient.  This can be important because it would ensure that we are reporting information consistently across patients.  It is also important to be able to identify all patients that may have had a specific variant in case the clinical interpretation of a variant changes over time, which happens not infrequently.  Therefore, we are looking for an individual who could design an accessible platform that would allow us to hold, visualize and query genetic data that we have generated on patient samples.

13. ICU Flowsheet: Bringing patient data from the bedside to the cloud

Customer: David Maslove, Depts. of Medicine & Critical Care Medicine, Queen’s University & Kingston General Hospital

Health informatics is currently one of the fastest growing fields in both medicine and computer science. According to, there are more than 17,000 startups working in the field of health care, with an average valuation of $4.4 million. The average salary at these companies is approaching six figures, with nearly 3,500 job openings currently posted. These jobs require skills in data analytics and software development; experience with data collected in medical settings is a strong asset.

The Intensive Care unit of the Kingston Health Sciences Centre is a 33 bed unit caring for critically ill patients with severe infections, massive strokes, trauma, and other life-threatening conditions. Physiologic signals are continuously measured at 240 Hz, including arterial and venous pressures, cardiac electrical activity, and blood oxygen saturation. All of this generates a tremendous amount of data, the correct, realtime interpretation of which is vital in order to ensure the best possible outcomes for the sickest patients in the hospital.

As part of a multiyear project, a large amount of high frequency physiological data is collected on critically ill patients admitted to the intensive care unit at KGH. At the moment this dataset exceeds 10 TB and is growing by approximately 16 GB per day. This dataset is being mined for novel physiological signatures which have the potential to better predict the evolution or development of disease states as well as measure and predict response to therapy. The major limitation in interpreting these data is that many key inputs such as infusion rates of intravenous fluids and vasoactive medications is currently recorded in analog on paper lowsheets at the bedside. It can be very difficult to interpret subtle changes in physiologic signals without having an accurate, contemporaneous record of changes in medications which are in fact intended to change these parameters.
The completion of this project will allow for more detailed exploitation of our physiology data and will provide the development team with one-of-a-kind experience in working with relational databases in a secure, multiuser environment focusing on medical data and hospital care. This work will also allow valuable exposure to the unique requirements for developing software for use in a healthcare/biomedical research context.

Deliverables: The goal of this project is to develop a secure application capable of recording patient care information for critically ill patients including:
• All infusion medications
• Intravenous fluids, blood products, etc
• Urine and nasogastric tube output
• Output from chest tubes and other surgical drains
• Agitation/sedation scoring
• Ventilator settings
• Temperature

At a minimum the application should be web-based on a secure server but a mac/PC based client application suitable for faster bulk data entry would be a bonus.

14. Open-source analysis software for functional MRI of the spinal cord and brainstem

Cutomer: Patrick Stroman, Centre for Neuroscience Studies, Dept of Biomedical and Molecular Sciences, Dept of Physics, Queen's University

Functional magnetic resonance imaging (fMRI) has become one of the most powerful tools available for neuroscience research, and is continually progressing toward clinical use. While fMRI is most commonly used for the brain, it has also been adapted for the brainstem and spinal cord in order to study processes such as motor control and pain, and to investigate a wide range of conditions such as traumatic injuries or multiple sclerosis or lower back pain. However, after two decades of development, in many ways functional MRI is still in its infancy because it presents many technical challenges that span from physics and engineering, to physiology and anatomy, to psychology.

In order to speed the development of fMRI in the brainstem and spinal cord, and to enable more widespread use, an easy to use, open-source, data analysis software package is needed. This project is to take an existing software package that has been developed over many years in MATLAB, and has been extensively validated, and completely redesign it as needed and write it in Python. Ideally, this software would be structured to provide ease of future expansion and free sharing of new developments. The key functions to be provided by the software package are 1) definition and organization of local databases for ease of accessing data from many research participants, across multiple studies if needed, 2) data pre-processing to identify and remove noise and physiological motion, and for spatial normalization of image data, 3) data analysis using general linear models, and connectivity analysis using structural equation modeling, and 4) display of the results. At present, the end-users would be scientists from a wide range of disciplines.

15. Single particle analysis

Customer: Diane Beauchemin, Department of Chemistry, Queen's University

Nanoparticles are found everywhere, including in food, clothing and the environment.  To assess their impact, their composition and size must be measured.  A powerful approach in its infancy, which can be applied to particles suspended in aqueous solution, is single particle inductively coupled plasma mass spectrometry.  If the suspension is dilute enough, then only one particle is measured at a time.  Because each particle is minuscule, very fast data acquisition is required to see it.  This means repetitive sub-millisecond measurements of the signal of elements while a suspension of nanoparticles is being introduced, which generates a huge amount of data (7000-400,000 data points per file).  To decipher particle events from the background signal, an iterative statistical process is used, where every signal larger than 3 standard deviations from the overall average signal is taken as being caused by a particle and accumulated separately.  This 3 standard deviations test is applied to the remaining signals and the process is repeated until no more particle event can be identified.   Processing of the particle events data must then be performed, which involves a calibration using a series of standard solutions, regression analysis to find the line of best fit and application of the equation of this line to the data to convert signal into particle mass, which is then converted into a size if the shape and density of the particles is known.   Finally, binning of the resulting particle sizes is done to create a histogram, from which the average particle size with it standard deviation are calculated.  At the moment, everything is done manually with a spreadsheet, which takes an inordinate amount of time.  If software could be written to automate most of the above process, a substantial increase in sample throughput would result. The software needs to be able to use the .csv files generated by the instrument.

16. Customer Relationship Management (CRM) for Executive Training

Cutomer: Bahman Kashi, Department of Economics, Queen's University
Department of Economics requires a tailored CRM system for running executive programs. The relationship must cover three primary areas: 1) application and admissions, 2) participation and performance tracking, and 3) alumni relations. The system requires interaction interfaces with other existing services such as the website's application form, alumni portfolios (website), online training platform, and newsletter mailing application. Security, privacy, and ease of access through mobile platforms are essential. There is a preference for building the program within an existing secure app echo systems, such as Google Apps for Business. As an optional requirement, mobile apps can be developed for customers, administrators, or faculty to serve specific needs such as scheduling, information verification, consent signature collection, etc.

17. Proposal Development Platform

Customer: Bahman Kashi, Department of Economics, Queen's University

The program needs to maintain information and package a subset of it within a selected style in MS Word. The information falls into two categories: 1) CV of academics, and 2) relevant experience. The objective is to speed up the process of proposal development. Where the user can select the included academics in a proposal, choose the format of the document based on the RFP-issuing organization (World Bank, UN, etc.), and export the content to MS Word.

18. Waveform visualization tool for Critical Care Medicine

Customer: David Maslove, Depts. of Medicine & Critical Care Medicine, Queen’s University & Kingston General Hospital

Health informatics is currently one of the fastest growing fields in both medicine and computerscience. According to, there are more than 17,000 startups working in the field of health care, with an average valuation of $4.4 million. The average salary at these companies is approaching six figures, with nearly 3,500 job openings currently posted. These jobs require skills in data analytics and software development; experience with data collected in medical settings is a strong asset. The Intensive Care unit of the Kingston Health Sciences Centre (KHSC) is a 33 bed unit caring for critically ill patients with severe infections, massive strokes, trauma, and other lifethreatening conditions. Physiologic signals are continuously measured at 240 Hz, including arterial and venous pressures, cardiac electrical activity, and blood oxygen saturation. All of this generates a tremendous amount of data, the correct, realtime interpretation of which is vital in order to ensure the best possible outcomes for the sickest patients in the hospital.
As part of a multiyear project, a large amount of high frequency physiological data is collected on critically ill patients admitted to the intensive care unit at KGH. At the moment this dataset exceeds 10 TB and is growing by approximately 16 GB per day. This dataset is being mined for novel physiological signatures which have the potential to better predict the evolution or development of disease states as well as measure and predict response to therapy.
Deliverables: The goal of this project is to develop a suite of visualization tools which will allow for exploration of the physiological waveforms. There may be potential to continue development as a real-time clinical monitoring tool for multiple critical care units.
1. The tool should be sufficiently flexible to accept multiple data sources (eg the KHSC data mentioned above as well as MIMIC format data).
2. The tool should be cross-platform, ideally web-based such that it can be used from secured computers at KHSC.
3. The tool should allow for overview of an entire record with the ability to zoom in on regions of interest.
4. The tool should support animation of historical signals leading up to marked events of interest.
5. The tool should support automated flagging/feature detection of interesting events and signals. The algorithms for this will be supplied by the research team but the developers should be able to build a visualization platform that is sufficiently flexible to accommodate multiple detection algorithms and filters as they are developed over the course of the project
6. The user interface should allow for the selection of various channels for display as well as the selection of different filters and processing algorithms.

Architecture:Development would preferably be in Python in order to integrate with other applications in use and in development by the lab.

19. Digitizing research article collections through automated article retrieval from web-accessible archives.

Customer: Neil Renwick, Department of Pathology and Molecular Medicine, Queen's University

Many senior investigators are interested in digitizing their research article collections but are discouraged by the time commitment. The goal of this project is to save time by automating as much of this process as possible. Potential steps involve (i) end user scanning and collating the front page of each article into a pdf file (potentially in batches of 100), (ii) visual parsing of each page/article for citation details, (iii) automated search for each article in an appropriate web-accessible library, such as PubMed, and (iv) automated retrieval of available articles in pdf format with a list of articles that were or were not found.

20. Motorola Barcode Scanner Software Development

Customer:  Jeremy Babcock and Kim Garrison, School of Medicine, Queen's University

The 8,000 square foot Queen's University Clinical Simulation Center is a medical simulation lab located in the Medical School Building. The proposed project would be to develop custom inventory software to track and maintain our capital equipment and thousands of consumable supplies purchased per year. We currently do this tracking completely manually.

We have purchased two Motorola Symbol LS4278 Cordless Bluetooth Laser Barcode Scanners with cradles (Possibility of cell phone scans) and a DYMO label maker and would be willing to purchase server space that the staff would log into linked to our NetID’s. Our staff would then have access to this database with the ability to view online (Scan read-only) and have only specific staff act as the admins (scan and edit the database).

Ideally, if a piece of capital equipment is scanned (Label/barcode/QR code), the program (GUI) would show maintenance records, a picture of the item, where the item is located and other metrics kept on that item. If a consumable item is scanned, the program would show the user our current stock, incoming orders, the average cost ($), location in the lab, picture of the item, item supplier, etc.

21. Web-based Virtual Microscopy Pathology Laboratory

Customer: Jim Farmer and Isabella Irrcher, Department of Ophthalmology, Queen's

The aim of this project is to develop a web-based virtual microscopy laboratory (+ database) for current and future learners on the topic of ophthalmic pathology. The audience includes medical students, ophthalmology residents, and practicing ophthalmologists. The general format of the laboratory is a case-based, problem-solving format with scenarios similar to what one encounters in the clinic. Cases will be subdivided into topic-specific modules: normal, eyelid conjunctiva, cornea, glaucoma, retina, uveal tract, nasolacrimal sac, orbit, infection, and inflammation. The system will initially be developed with the cornea module and will include 5 cases. Each case consists of a patient history with corresponding clinical photograph and digital pathology slide with hidden annotations. Cases and corresponding photographs and digital slides will be provided by the customer. The primary aim for each case and the module as a whole is for the learner to select the correct diagnosis from a list of 4-5 possibilities. From an analytical standpoint, the system will need to be able to track individual users for the purposes of educational analytics.

The system will need be to be dynamic (can easily add and remove information) and user-friendly (for non-computing experts). Other system requirements: 1) Tracking API (Tracking is to analyze learner movements within the digital slide), 2) interface with GoogleMaps API to navigate through the digital slides , 2) Educational Analytics (tracking users, 3) Reliable and secure storage, 4) ability to abstract information from the database into Excel for statistical analysis.

22. From madness to method – keeping track of the systematic review process

Customer: Christina Godfrey, School of Nursing, Queen's University

The mantra of the systematic review process is ‘to be thorough’, ‘to be transparent’ and ‘to make the process replicable’.  To enact these directives is a task that requires careful attention to many iterative sequences of searching and screening followed by the appraisal, extraction and synthesis of data from multiple articles. Throughout this process there are also important decisions that are being made that shape the final review product. To the uninitiated, keeping track of both the vast amounts data and the synthesis process itself can be challenging and even somewhat overwhelming at times.

The Review Nanny is resource that will assist in keeping track of the systematic review process. The Review Nanny has two major components: a) support – information about each stage of the review process, what needs to be done at each stage and what decisions need to be made; and b) project management – a feature that allows you to track the progress of the review through each stage. If you are an administrator or have several students completing reviews you can track several reviews at once, identifying which are on target and which may be running a bit behind. The Review Nanny resource is not a depository for the systematic review data and does not serve to duplicate the various software programs available that either keep track of citations (such as a reference management software program) or that act as a placeholder for the multiple articles used during the synthesis process. The Review Nanny resource is a project management or tracking tool that helps guide the reviewer through the review process, indicating where they are along a specified timetable. The basic timetable that guides the resource is taken from specific recommendations for the completion of systematic review projects. In addition to the tracking feature, the Review Nanny resource also contains detailed methodological support screens that indicate task details for each step, issues to be considered at each point along the journey, and a variety of templates to aid in the completion of the review.

The Review Nanny program is a practical means to provide guidance and structure at each stage along the review process. At a program level, it serves as both a monitoring and quality-check. In addition, because the program portrays the review process at a granular level it is useful for externally driven and funded review projects to explain the complexities of reviewing and to justify resources needed to conduct the review.

23. App to optimize postoperative patient recovery

Customer: Michael McMullen, Department of Anesthesiology and Preoperative Medicine, Queen's University

Postoperatively, one of the primary determinants for readiness to discharge is the patients’ functional status and it is often central to patient recovery depending upon the surgical procedure.  Despite its importance, there are multiple barriers to collecting information regarding patients’ postoperative activities and collecting such information is generally outside the realm of the routine surgical workflow.

The ubiquity of mobile devices (mdevices) and advances in computing technology has provided an avenue to fill this gap and electronic health (ehealth) apps are becoming increasingly popular in perioperative patient management. They can support standardized care delivery plans, deliver patient assessments and aid in the identification of patients that would benefit from additional care. However, to date, the majority of ehealth apps reported in the literature are observational in nature and aimed at providing feedback to clinicians to guide care or deliver the postoperative care protocol to the patient. These apps may or may not make an actual difference in terms of care delivery and patient outcomes.

The primary aim of our currently proposed application is to provide feedback to the patient regarding their own functional status in relation to what is “optimal” or “recommended” (i.e, percent achieved of target).There is some evidence with healthy non-clinical participants that activity levels can be manipulated depending upon the feedback provided. We are currently running a pilot study in abdominal surgical patients with a fitbit to assess feasibility and demonstrate that we can significantly modify the patients’ postoperative activity levels.

Once demonstrated, the next phase is to develop a more sophisticated ehealth app which first monitors activity levels of individuals and then recommends activity levels based upon a gradual ascending algorithm (e.g., to recommend a 10% increase over baseline on postoperative day 2, and then again on day 4?) so that the performance level of each algorithm is customized for that particular patient. When the patient either performs at maximal performance or way below maximal, the algorithm auto-adjusts appropriately to maintain patient engagement.

Once this second phase is completed, we will perform a randomized controlled trial in which patients are randomized to receive no feedback or 1 of several different feedback algorithms (algorithms and platform TBD during development using patient information from the pilot study), and activity levels as well as clinically relevant patient outcomes will be examined.

If we successfully develop an app which can non-invasively and ethically manipulate patients’ post-operative activity levels AND we can demonstrate improved clinically relevant patient outcomes, this app will be highly marketable. Given the impact of such a postoperative app, it is likely that it would be marketable even in the absence of demonstrating hard patient outcomes. It could still be highly relevant and cost-effective for getting patients mobilized and discharged from hospital earlier which is another potential avenue for investigation. In fact, development of such an app would have many possibilities and potentially have a very significant impact in patient care.

24. Standardized Patient Program - Demographic, Session and Financial Database Development

Customer: Katherine Slagle, School of Medcine, Queen's University

A standardized patient is an actor who is trained to interact with future healthcare professionals giving them the opportunity to practice their communication and physical examination skills before interacting with real patients.  On a daily basis we facilitate standardized patient (SP) sessions for medical, nursing, rehabilitation therapy students, etc.

We currently have a pool of over 100 SPs and are looking to develop a database to log:

- Demographic data

- Personal contact information

- Session frequency (Faculty of Health Sciences and invoiced)

- SP session preference

- Completed training (Faculty of Health Sciences and invoiced)

- Training videos

- University requirements i.e. AODA, Health and Safety Tx, CPICs, etc.

- Payroll data

- Scenarios/roles used

- Personal SP develop notes

Ideally, from the database we would be able to generate reports and invoices:

- Costs associated with each session

- Scenario/role frequency

- University requirement adherence

- External invoices

25. Electronic Clinical Aids

Customer: Gregory Klar, Queen's Anesthesiology and Perioperative Medicine 

In the interest of patient safety, anesthesia continues to protocolize patient care and finds innovative ways to reduce errors. Nonetheless, medication errors remain common and cause a significant cause of morbidity and mortality in North America and around the world. Medication errors can be either prescribing errors, giving the wrong medication, or omission errors forgetting to give a drug at the correct time or entirely. Despite being protocol driven, medication errors continue to be a common problem. Furthermore, good recent data has shown that electronic aids can be vey helpful in reducing errors both prescribing and omission errors. Lastly, medicine is very slow to adopt the use of electronic support systems to help manage patient care and avoid errors. The goal for this electronic support system, to intergrade common anesthesia protocols into a responsive electronics aid that will help to steer clinicians to make timely decisions with regards to drug administration and adherence to protocols. The goals is to mitigate human error and improve patient care. 

The majority of this protocol could be put into an electronic flow chart with “notifications” to help clinician adherence to this protocol. Although these protocols do exist in PDF formats in a busy operating room setting daily mistakes are made. I also encourage you to read the attached recent article from the Canadian Journal of Anesthesia that highlights many of these points.

The goal of the electronic aid is simple. When for example an anesthesiologist will be doing a “ERAS” case, he will enter a start time in his phone or computer program. This will trigger notifications such as preadmission and surgical daycare goals to ensure nothing is forgotten. Then in the operating room the anesthesiologist would press “start” and form then all medications within the protocol would come up as notifications. The program will also start a count down that will enable appropriate and timely re-dosing of antibiotics (please see attached CJA paper). Once the operation is finishing the program would have a “finishing” button that would allow for reminders for the “end of the operation” and “recovery room”. Clinicians are very dedicated to provide optimal care, yet medication and protocol errors remain a common cause of in hospital morbidity and mortality. The goal of this program is to reduce this burden.

26. Augmented Reality Health Care Museum Exhibit

Customer: Jenny Brown and Maxime Chouinard, Museum of Health Care. Rob Harrap, Department of Geological Sciences and Geological Engineering

Supervisor: Nick Graham, School of Computing

The Museum of Health Care at Kingston, located on the Queen’s Campus, preserves and promotes the rich material legacy of our medical and health care past. The museum wishes to augment the experience of visitors to the Museum of Health Care using augmented reality techniques. In particular, we hope to highlight objects and devices in the Electricity and Invisible Ray gallery so that visitors gain insight both into what the objects are and into what role they play in historical medicine. This project would also add some engaging interactive component to the display.

Specifically, augmented reality would be used in a recreation of a 1930’s general practitioner’s treatment room. The AR system would allow visitors to highlight objects, and bring up additional text, audio, photos and animation about the object. This project would develop a first prototype of the system, helping to understand the technical issues of designing such AR exhibits, and providing an initial AR experience.

27. Virtual Reality for Scientific Visualization

Customer: Melissa Green, Department of Mechanical and Aerospace Engineering, Syracuse University. Michael Rainbow, Department of Mechanical and Materials Engineering, Queen's Univeristy.

Supervisor: Dorothea Blostein, School of Computing

The purpose of this project is to develop a suite of scientific visualization tools for use in a virtual reality environment (HTC VIVE). The Biopropulsion of Adaptive Systems Group is interested in learning about the interface between the environment and the organism (e.g. fluid-structure interactions) and how the dynamics at the interface are related to the organism’s biomechanics. To that end, we would like to develop tools that allow us to visualize these complex system interactions. Current VR tools allow us to load in precomputed surfaces and rigid body transforms, but we are unable to manipulate these surfaces to generate derivative visualizations (for example, real-time modeling of muscle tendon lengthening or visualization of a vector field that is changing in time). Examples of the current development, as well as the types of data we would like to visualize can be found at the following links. ,

This suite of tools has the potential to provide insights into the relationship between an organism’s biomechanics and its interactions with the world that were previously impossible to see using traditional tools.   

28. Gamified Financial Literacy Training for Medical Students

Customer: Greg Davies, Maternal-Fetal Medicine, Queen's

MEDucate is an EdTech startup that has partnered with the Queen’s School of Medicine to teach medical students how to run their own medical practices and help them become financially literate. This will be done using a two-pronged approach: a web or mobile-based medical practice simulator to keep students engaged, as well as give them an avenue to experiment with business concepts, and a series of online video tutorials to teach them the academic side of running a small business. Student and medical school interest has been qualified through the MEDucate team’s primary research. At this stage, a minimum viable product needs to be built which can be used for beta testing

Extensive work has already been completed to identify need, build a go-to-market strategy, and create a conceptual design (including professionally-produced UI mockups). Interested teams should have strong interest or experience with UI creation and/or web/mobile game design.

29. After Visit Summary" For Patient

Customer: Kristen MacKinnon, Queen's Family Health Team, Department of Family Medicine, Queen's University

The Queen's Family Health Team (QFHT) is looking to create an "After Visit Summary" that we can give to our patients after their appointment. Since we are a teaching facility, our patients mainly see residents and there can sometimes be some miscommunication about what was discussed and the next steps required for the patient, especially if the patient has multiple chronic conditions or is managing many different medications. This "After Visit Summary" would provide the date, reason for appointment, patient's name, date of birth, staff physician (MRP), doctor that conducted the appointment, vitals, allergies, list of current medications, a summary from the SOAP note about what was discussed, and patient instructions. QFHT uses an electronic medical record (EMR) called OSCAR where all of this information is entered. The task would be to pull this information together from the different modules in OSCAR to create the "After Visit Summary".