Proj S01 – Alexandra Hospital: Enhanced Patient Journey at Hospitals

Problem

Imagine you are a non-English speaker and first-time patient at a hospital for an appointment at Clinic B.

9.00am: SMS Notification

You receive an SMS notification. Seeing the "2.00PM" text in the SMS, you are reminded of your 2.00PM medical appointment at the hospital today. Anxiety starts to set in as it's your first time visiting the hospital and you are unsure whether you can navigate your way around the hospital.

1.50pm: Registration

You arrive at the hospital lobby and spot the self-registration kiosk, where you register for your appointment.

1.55pm: Queue Slip

You receive an queue slip and but you are not able to read most of the text. However, you recognise that your destination is denoted by "C02-01" and you start looking for it.

1.56pm: Signage

You start looking at the overhead signage to look for Clinic B, however, most of the signage is in English and you start to panic. Unfortunately, as you start to panic, you lose your concentration, making it harder for you to comprehend the information on the board.

Seeing the big letter "B" on the signage (which denotes Zone B), you think you are near Clinic B and start to walk around in search of Clinic B. However, C02-01 Clinic B is actually located in Zone C of the hospital.

2.00pm: Wayfinding
and Time for Appointment

As you start walking back and forth around the hospital, you realise that you are unable to find C02-01. Your anxiety worsens as it's time for your appointment but you are lost. However, you are too shy to ask for help.

2.05pm: Help Arrives

Fortunately, a healthcare staff member passing by notices you walking back and forth and approaches to ask if you require help. You arrive at Clinic B late, and your patient experience is adversely affected by the wayfinding difficulties you faced.

These wayfinding challenges are prevalent among outpatients, visitors, and caregivers

As healthcare needs increase with Singapore’s ageing population, seamless navigation in the hospital is vital to reduce the frequency of late arrivals and stress amongst patients. However, gaps, such as information-heavy signage, vaguely demarcated zones, and a lack of real-time support, remain in current wayfinding methods. This can lead to work disruptions for healthcare workers and potential financial burdens on the hospital.

Just like how the North Star
serves as a guiding light for people
lost in the wilderness...

Aims to be a personalised guide for people who are lost in complex spaces like hospitals

Our Intuitive Optimised Personalised Solution: Glowing Guide

Play Video

Let's rewind the clock. Imagine you are a non-English speaker and first-time patient at a Glowing Guide-enhanced hospital for an appointment at Clinic B.

9.00am: SMS Notification

1.50pm: Registration

You arrive at the hospital lobby and spot the self-registration kiosk, where you register for your appointment and indicate your language preference. With a few simple additional steps, such as scanning your shoeprint (which will be used to identify you) on a pressure mat and going through some visual instructions on how to use the Glowing Guide system, you are good to go after collecting your queue slip!

1.55pm: Queue Slip

You receive an queue slip but you are not able to read most of the text. However, you recognise that your destination is denoted by "C02-01" and you embark on your wayfinding journey.

1.56pm: Projection
Near Registration Kiosk

Based on the instructions provided at the registration kiosk, you proceed to the nearest projection system to get your first navigational assistance. This early intervention sets you on the right path as you learned from the navigational cue that Clinic B is in Zone C (denoted by the Blueberry symbol and Blue colour). It is also translated based on the language preference that you have selected at the registration kiosk.

You start to follow the arrows featured prominently on the projection.

1.57pm: Enhanced Signage

Looking at the enhanced overhead signage, which clearly indicates that Zone C is ahead, you are assured that you are on the right path.

1.58pm: Coloured Strips
and Zoning Stickers

At Zone C, you notice vibrant blue strips along the corridor and zoning stickers that confirm that you are at the correct path to Clinic B.

1.58pm: Projection System Available Around the Hospital

You spot another projection system along the corridor. Just to be sure that you are at the correct path, you step on the pressure mat to activate the system, which gives you directions to Clinic B.

1.59pm: Arrival On Time
and With Ease

You spot a distinct banner with a familiar clinic number, "C02-01". You are relieved that you have reached Clinic B punctually on your own and with ease, as Glowing Guide guided you through every step of your wayfinding journey.

Reimagining Wayfinding Experiences in Hospitals

Overview of Glowing Guide's Subsystems

To better understand the different subsystems of Glowing Guide, let us walk you through a common patient journey and compare it with the proposed patient journey with Glowing Guide.

Current Patient Journey

Enhanced Patient Journey

Explore Glowing Guide's 5 Main Subsystems

Registration Flow

Your registration flow remains largely unchanged, with the main difference being an incorporation of the scanning of your shoeprints using the pressure mats. You are also provided with wayfinding instructions before you get your printed queue slip. Similar to the existing kiosk, you will be asked to select your preferred language, which will be used in the rest of the kiosk interface and the projections.

Website Developed

To assess the user experience of the proposed self-registration process in Study 1 (check out the User Testing & Results section below for more details), that can inform its feasibility, a website has been developed using React and Tailwind CSS. The wireframes and graphics for the website were designed using Figma.

Selection of language preference

Screen shown during shoeprint scanning

Translated graphical and text-based wayfinding instructions

Data Flow from Registration Website to Projection System

The information entered by you, namely your language preference, name, phone number, symptoms, and whether you require wayfinding assistance will be automatically uploaded to an Amazon DynamoDB database through an AWS AppSync API call on the Confirmation page. The shoeprints that were captured during the scanning process are saved to the same database, with implementation details found in the next section. Based on your information and required patient journey for the day, your start and end destination will also be obtained and saved to the database. These will be used for the location-based projections and supported by the optimised route generated through Glowing Guide’s route optimisation algorithm.

Shoeprint Acquisition

Protective Cover: To protect the sensors from damage

Sensors: To scan patients' or visitors' shoeprints and capture the unique pressure distribution exerted by the shoe and user's weight on the pressure mat

Base: To keep sensors and protective cover in place and to visually contrast with the protective cover to signpost to patients and visitors on where to stand

Comprising an array of 32 piezoresistive sensors, whose electrical properties change when compressive stress is applied, the pressure mat captures your shoeprints when you step on it, serving as your identification for the day’s visit. Custom electronics hardware has been designed to process the data and transmit it via IoT communication protocols to the cloud backend.

Data Flow from Registration Kiosk's Pressure Mat to System

Shoeprints will first be captured and stored during registration. With your shoeprint scans obtained through the pressure mat during the registration process, an algorithm allows Glowing Guide to identify you. As you navigate around the hospital and step on other pressure mats, the algorithm automatically runs on AWS Lambda upon receiving a trigger from the pressure mat through AWS IoT Core, and identifies you. Your identity is subsequently used to inform the system of your next location and the navigational cues to be projected.

Data Flow from Pressure Mat and Kiosk Registration to Projection System

Upon stepping on the pressure mat and identification of your shoeprints, information such as your next destination and preferred choice of language, obtained during the kiosk registration, will be extracted from Amazon DynamoDB and sent via an AWS Lambda function to Amazon Simple Queue Service. The microprocessor, a Raspberry Pi 4, will continuously query the queue to poll for messages until it receives your information, The message will then be unpacked and the corresponding navigation cue graphics will be extracted from the microprocessor's internal storage.

Process of Using Projection System

Your personalised navigation cues will then be displayed on the floor in front of you by the projector. You will be able to view the zone of your destination, name of your destination, code (i.e., containing the zone, level and clinic number) of your destination and direction arrows. Simply follow the directions and you will be there in no time!

Sequence of Projections

Step 1: Indication of the availability of wayfinding assistance and concise instructions on how to interact with the Light Projection System appears.

Step 2: Loading screen appears when pressure mat is stepped on (i.e., when the system is scanning your shoeprint and preparing the personalised navigation cues).

Step 3: Your personalised navigation cue appears, providing you instructions on where you should go to next.

Key Design Features

Feature 1

Feature 2

Feature 3

Feature 1

Feature 2

Feature 3

Feature 1

Clear Hierarchy of Navigational Cues
Allows for greater comprehension and recall (Lege, 2019), which can aid in wayfinding.

Greater Emphasis on Symbols
To ease understanding of instructions or to cater to those who are illiterate (Apelt et al., 2007).

High Contrast Colours
Conforming to Web Content Accessibility Guidelines AAA Standards to enhance visibility of instructions.

Algorithm to Optimise Route

To ensure a seamless hospital journey, the A* algorithm optimises your route through various locations based on your scheduled appointments, ensuring you take the shortest and most direct path possible. It calculates the best route by considering both the actual distance to the next location in the path, g(n), and the estimated distance remaining to your final location, h(n), guiding you efficiently from one point to another. These 2 sets of distances are calculated across various locations, using the floor plan of the hospital as shown below.

g(n) is calculated using the actual distances between adjacent locations, extracted from the blue lines in the floor plan above. h(n) is calculated using Manhattan’s distance, defined as the sum of the absolute differences of the Cartesian coordinates of two points (i.e., the green dots referring to the central coordinates of each polygon in the floor plan above).

Understanding the Algorithm through a Case Study

1. Let's say you are at the Pharmacy (Level 1) and your next medical appointment is at Ward 10 (Level 2).

2. You have 2 options to go from Level 1 to Level 2: (1) take Lift A or (2) take Lift B. The actual distance travelled by choosing Option 1 is much lower than that of Option 2. Option 1 seems to be the better option.

3. However, the heuristic of Option 1 is much higher than Option 2.

4. The savings in the actual cost to a lift for Option 1 is not enough to make up for the additional estimated distance from Lift A to Ward 10, as compared to Lift B to Ward 10. Therefore, the optimal route is Option 2.

Similar to the case study above, the A* algorithm will be used to help Glowing Guide decide the projections that you will see as you travel around the hospital to your various destinations.

If your next location changes after visiting one location (e.g., in the event that you need to visit the Clinical Measurement Centre after an appointment with a doctor), the Patient Service Associates will be able to modify your patient journey and the database will be synced with these changes. This results in a revised optimised route that takes your new destination into account, and integrates seamlessly with the Light Projection System to provide you suitable graphics as you step on pressure mats around the hospital.

In addition to receiving personalised navigational assistance from projections of optimised routes, you can receive additional wayfinding assistance from Glowing Guide's evidence-based and architecture-based strategies, including graphical redesigns of hospital zones and signage, as well as spatial redesigns of hospital zones.

Hospital Zones: Graphical Redesign

Key Design Features

Common Fruits
People are more likely to recognise them

Two Colours Per Fruits
To ensure simplicity (Naharudin, 2017)

Colours Match
Existing Zones
To prevent confusion among past visitors who are familiar with the existing zones

Text Remains
To cater to patients or visitors that are unable to differentiate colours well (Apelt et al., 2007)

Arial Typeface
Font choice ensures legibility of wayfinding instructions
(Apelt et al., 2007)

Hospital Zones: Spatial Redesign

Key Design Features

Wall and Overhead Signage
Remains in the hospital but redesigned to enhance readability and reduce cognitive load.

Coloured Strips along Corridor
Clear indication of start and end point of zones, making routes clearer and more visible (Madson & Goodwin, 2021). Placed along corridors at optimal viewing angle.

Large Fruit Stickers or Murals
Placed at strategic locations to address potential confusion caused by breaks between coloured strips (Ford et al., 2020).

Hospital Signage: Graphical Redesign

Key Design Features

Removal Of Content Redundancies Through Grouping
Site studies have revealed wayfinding difficulties stemming from information overload. Research has also shown that content redundancies have a potentially adverse effect on one’s cognitive load (Bobis et al., 1993) and learning of information (Pastore, 2012). To reduce content redundancies, zones associated with the same directional arrow (e.g., Zone D and Zone C associated with an ahead arrow) are grouped together.

Application of Gestalt Theory
Information organised in a straight line and grouped by colour to enhance comprehension and to decrease cognitive load (Majooni et al., 2016), tackling the issue of getting lost due to information overload.

Greater Prominence Of Clinic Number
As illustrated by the team's user studies, non-English speakers displayed greater reliance on clinic numbers (e.g., C01-01) instead of the clinic names. To increase the prominence of the clinic number, the clinic numbers are made larger and left-aligned, matching left-to-right reading patterns (Bergen & Chan, 2005). This adjustment is supported by arranging clinics by their numbers to further aid navigation.

Integration With Zoning Redesign
Integrates closely with redesigned zoning system, utilising fruit symbols to represent the different zones. Uniformity present in redesign can enhance the effectiveness of the proposed wayfinding system (Apelt et al., 2007).

Overall System Architecture Diagram

The various subsystems are integrated into an end-to-end system using Amazon Web Services (AWS) cloud microservices as the back-end for data storage, app hosting, cloud computation and IoT communication. Performing and hosting almost all computations on the cloud allows the Glowing Guide system to remain lightweight and easily deployable. The architecture diagram below shows the back-end sequences for both patient initialisation and wayfinding query sequences.

Study 1: Registration Kiosk Simulation Study

This study involved a in-person user study that aimed to assess Glowing Guide’s proposed kiosk registration process. This was done through an evaluation of participants’ understanding of the different screens in the proposed registration and their feedback on the overall user experience when using the simulated registration kiosk.

15 participants (aged 18 and above), a majority of whom use English as a preferred language when reading texts in their day-to-day life (N = 14) took part in the study. Overall, participants felt that the content and instructions on most screens were clear, the instructions on most screens were easy to understand, and they understood how to interact with most screens. Participants also suggested areas for improvement, with notable feedback involving creating a more intuitive, accessible, and efficient user interface and experience design through visuals, animations, and clearer or more concise language. Participants also noted considerations for diverse user needs.

In addition to pinpointing potential areas for enhancement, the findings from the study also served to validate the design decisions incorporated into the proposed registration kiosk.

Examples of Changes Made

Participants noted that the multi-step process in the original design was confusing as they were not sure when to remove their feet from the outlines.

In the revised design, the multi-step process of standing still followed by removing one’s feet was removed, and an animation to indicate that the scanning process was in progress for the user.

Participants noted that some of the terminology used in the original design (e.g., “wayfinding checkpoint”, “footprint”) were not clear. During the study, participants also expressed confusion regarding whether they were supposed to look out for a footprint on the floor while on this screen (shown above under the "Before" section).

The revised design’s text was updated to better reflect the exact use case of this screen, advising users to only follow the shoeprint on the floor near a certain lift after collecting their queue slip.

Study 2: Wayfinding Projection and Signage & Zoning Redesign Study

Try interpreting the team's first version of projection graphics and hover over them after you are done to see if you got it right!

Which design do you prefer? Hover over the images to see what others prefer.

This study involved an online survey that aimed to assess Glowing Guide’s proposed enhancements to the signage and navigational cues projected on the floor. Participants were asked to interpret the personalised navigational cues (i.e., projection designs) and choose between the redesigned or existing signage.

The survey received a total of 76 respondents aged 18 and above, all of whom mostly used English as a preferred language when reading texts in their day-to-day life (N = 75). Participants were mostly able to interpret the proposed navigational cues and mostly favoured the team’s proposed signage designs. They highlighted improvements to enhance the designs of the navigational cues and provided feedback in terms of colour, font or proportion, with some notable feedback relating to the clarity of the arrows in the navigational cues and adding colours to the navigational cues. For participants who favoured the team’s proposed signage designs, they acknowledged possible enhancements, some of which involved a combination of both the redesigned and original signage.

Apart from highlighting potential areas of improvement, the findings from the study helped to validate Glowing Guide’s design choices in the Enhanced Zones and Signage subsystem.

Examples of Changes Made

As participants were confused about the direction to interpret in the original design, the enhanced design included textual instructions to inform participants about the direction to head towards.

Participants suggested changes such as adding colour to the graphic, as well as increasing the size and proportion of most things on the graphic. This was reflected in the enhanced design.

Some participants appreciated the visual segmentation and grouping of similar zones into one column as seen in the team’s proposed design (shown in the screen above under the "Before" section). The toilet symbol was also made slightly larger as requested by participants. Additionally, to allow users to better orient themselves when reading this sign, a detail was added in the left hand side of the graphic to inform users of the current zone that they were in. This combined feedback gave rise to the enhanced design (shown in the screen above under the "After" section).

Participants preferred circled clinic letters and the clinic numbers being highlighted with a background behind it. However, participants found the text arrangement in the team’s proposed design (shown in the screen above under the "Before" section) to be clearer and more organised compared to the existing design (in the hospital), and highlighted that the placement of clinic numbers and abbreviations was more uniform in the team’s proposed design, making it easier to navigate and locate relevant information. This combined feedback gave rise to the enhanced design (shown in the screen above under the "After" section).

Study 3: Integrated Testing of Pressure Mat and Light Projection System

Informed by the team’s user studies that involved various subsystems of Glowing Guide (refer to Study 1 and Study 2 above), the team embarked on a in-person user study that aimed to observe how users interact with the prototype in terms of how comfortable their experience is using it and how intuitively they follow the navigational directions given to them; and to seek suggestions to improve the proposed projection designs.

22 participants, all of whom use English as a preferred language when reading texts in their day-to-day life, took part in this study. Participants were mostly able to interpret the proposed navigational cues, and mentioned a positive user experience interacting with the prototype. Participants also noted possible improvements to the design of the projection graphics, such as increasing the saturation of colours used in the graphics and the need for clearer content placement and representation to avoid potential confusion.

Examples of Changes Made

Participants recommended making the zone information more prominent and preferred adding more colours to the graphics. In the amended graphics, the saturation of the background colour behind the zone information was increased and the zone symbol and text were made larger.

Most participants were able to interpret this graphic, but mentioned that there could be potential confusion when interpreting the distances. The placement of the arrow symbol in the graphic was moved closer to the next location that the arrow is directing the user to (e.g. Stairs, Lift 3 or Lift 4), rather than the final destination (Ward 7).

Apart from highlighting potential areas of improvement and determining the effectiveness of the prototype, the findings from the study helped to validate design choices incorporated into the system.

Now that you have learned more about the 5 main integrated subsystems of Glowing Guide, join us on a trip down memory lane to learn how the team developed Glowing Guide using the Double Diamond Framework!

Literature Review

In Glowing Guide’s earlier days, the team embarked on a comprehensive literature review to better understand the problem space, especially in the context of elderly patients.

Elderly face a combination of challenges, such as cross-cultural understanding, vision deterioration, and cognitive decline, that increase their likelihood of facing wayfinding difficulties. Age-related vision deterioration (Salvi et al., 2006) and an increased risk of developing age-related eye diseases such as cataract and glaucoma (Loh & Ogle, 2004) can hinder their wayfinding. Elderly may also experience cognitive decline, with the ageing of brain regions that affect spatial cognition (Klencklen et al., 2012). Mänty et al. (2007) also identified a potential age-related decline in mobility. Huelat (2007) and Golledge (1992) related wayfinding difficulties to anxiety-related conditions due to their correlation to decreased concentration and misinterpretation of navigation cues.

Apart from these physical challenges, elderly may also face other challenges. Ming (2017) posited that elderly may also possess a fear of a steep learning curve and making mistakes compared to younger counterparts, leading to them having to rely on others to navigate the increasingly digitised environment.

Drawing upon these insights, the team conducted various user studies at Alexandra Hospital (AH) to understand its current wayfinding system and identify gaps.

User Studies

The analysis of ePES surveys, which collect patient feedback regularly, revealed initial issues with wayfinding at AH. Keywords such as 'clinic,' 'signage,' and 'direction' frequently appeared, suggesting challenges in navigating to clinics, understanding the signage system, and finding directions.

Further examination using OpenAI's GPT-3.5 and GPT-4 APIs indicated dissatisfaction with wayfinding and highlighted opportunities for improvements.

Over four days, the team interviewed 21 patients and 19 caregivers or family members at AH to understand wayfinding experiences. The team learnt that most interviewees used the signage system or asked hospital staff for directions.

Although not all had trouble navigating, some did get lost. The team observed that most interviewees were repeat visitors, which might have made them more familiar with the hospital's layout. To better understand the experiences of first-time visitors, the team also spoke with hospital staff likely to have assisted such newcomers.

The team interviewed 21 hospital staff, including various roles such as Patient Service Associates and Service Transformation Ambassadors (STAs), discovering that direction inquiries were their most frequent question, especially for STAs in the lobby who received about 10 such questions hourly. This underscores a potentially significant reliance on staff for navigation cues.

The interview also identified notable wayfinding-related gaps: the signage having too many colours and being only in English, which may cause confusion, especially for non-English-speaking elderly. Additionally, the use of letters for zones and clinics was identified as a point of confusion.

A study aimed at pinpointing pain points in wayfinding for first-time hospital visitors and identifying specific locations in the hospital where visitors were more likely to get lost revealed that although all participants reached their destinations, and most didn't express strong negative feelings, the findings confirmed issues with the current wayfinding system.

These issues lead to inefficiencies for both patients and staff, that it makes the patient journey more negative, and that the elderly and people with visual impairments struggle more with navigation.

Summary of Pain Points, Needs, Functional Requirements and Key Features

These 4 user studies above highlighted several pain points, from which needs, functional requirements and key features that the team hoped to achieve were derived.

Visual impairment
Cognitive decline
Mobility issues
Limited technological experience
Anxiety, fear, frustration or stress
Limited language literacy
Confusion over terminology
Overload of information

Explicit Needs

Easy to understand navigation cues
Identifiable navigation cues
Independence

Latent Needs

Feel well-oriented
Feel safe
Accessible & efficient routes

Guided user journey
No external help required
Inclusive
Learnable
Obvious to users
Independent navigation
Personalised assistance
Route optimisation
No training required
Safe

Simple wayfinding instructions
Visual wayfinding instructions
Minimal modifications to current processes
Clear navigational cues at every point
Instructions specific to needs of patient
Optimised and personalised route

Concept Generation through Brainstorming

Based on the pain points, needs, functional requirements and key features identified through the studies above, the team used affinity clustering to produce the 6 key features highlighted above.

Based on these key features, the team then utilised the morphological matrix method to generate concepts that would suit the problem statement.

Approaches with the most applicability and potential were grouped into two categories, namely modalities, meaning the tangible outcomes that a user could expect to hold, and tools, the navigational aids that could be combined with the modalities in order to achieve the team’s desired functions.

The team then used classical brainstorming and blended these modalities and tools to formulate more developed ideas.

13 distinct concepts were generated and grouped into 5 categories: Immersive Visual Aids, Devices with Simple Arrow Interface, Integration into Built Environment, Interactive and Gamified Tools and Others.

Concept Selection through Pugh Chart

Concept selection was done through a Pugh Chart, with criteria developed from the needs of both the users and the hospital. For the users’ needs, the team included 6 criteria, namely intuitiveness, user independence, inclusivity, comfort, personalisation and safety. The hospital’s needs included the solution's affordability, as well as scalability.

Evolutionary Prototyping and Unit Testing

With a better understanding of the problem and some possible ideas, the team identified 5 key subsystems for Glowing Guide, namely Kiosk Registration, Pressure Mat, Light Projection System, Route Optimisation, and Enhanced Zones and Signage. Based on these 5 subsystems and with the key features that the team hopes to achieve to address the pain points in mind, the team embarked on an isolated subsystem prototyping approach for the development of early prototypes. A continuous and iterative cycle of evolutionary prototyping and unit testing was done for every subsystem, before being pushed for the various user studies. The prototypes were then further refined after the user studies.

Kiosk Registration Wireframes

To prototype the kiosk registration process, the team began by creating simple flowcharts to understand the current registration process, including the data collected and required steps. This helped the team design a new registration process that seamlessly integrates with the existing one.

After visualising the new flow, the team created a low-fidelity wireframe in Figma, which was extensively discussed to identify any gaps. Following these discussions, a high-fidelity wireframe was developed, incorporating graphics and animations. These wireframes served as a reference for designing the website. Prior to the user study, the team also conducted informal testing with friends and family to identify potential areas of confusion.

Pressure Mat Printed Circuit Boards (PCBs)

Single piezoresistive sensor fabricated to validate the working principle of pressure sensing

A continuous array of sensors based on the validated single sensor.

Different materials and electronics designs were experimented with to improve sensitivity and signal-to-noise characteristics

The final prototype comprises a flexible array of discrete sensors for noise reduction, and refined custom electronics for data processing and transmission.

Evolutionary prototyping with unit testing was used in the development process of the pressure mat system. To validate the working principle of piezoresistive pressure sensing, a single sensor prototype was designed. Varying amounts of pressure was applied to the sensor, and the voltage response was measured. Based on the results of the single sensor characterisation, the team proceeded to fabricate an array of sensors. Custom embedded electronics was developed for signal processing, control and transmission of data acquired by the sensor array to the cloud. Embedded software (C/C++) was developed in conjunction with the electronics, and tested both in isolation, and in conjunction with the pressure sensor array.

Through a rigorous process of prototype iterations, testing and optimisation of materials, sensor configuration, electronics and firmware, the team developed a functional prototype of the pressure mat sensor system.

Projection Graphics

To develop the projection graphics, the team conducted an extensive literature review to understand design principles, including any specific guidelines for navigational cues in complex spaces like hospitals. Using this knowledge, the team brainstormed several designs on Figma, incorporating principles such as Gestalt Theory and key features that the team aimed to achieve. A discussion among the team members yielded a set of designs selected for user testing.

Enhanced Zones and Signage

Before designing the graphics for the enhanced signage, the team visited Alexandra Hospital to study their current signage system and conducted a thorough literature review on design principles. After completing the designs in Figma, the team selected a set for user testing.

The graphics for the enhanced zones drew inspiration from existing implementations that aid wayfinding, such as the use of nostalgic items and fruits in places like train stations and residential areas. The team then iterated on the designs based on feedback from various mentors to simplify and refine them.

After rigorously prototyping and testing each of the 5 subsystems, the team proudly presents the fully integrated and tested Glowing Guide—a system that is intuitive, optimised, and personalised.

The team eagerly anticipates the endless possibilities for Glowing Guide, envisioning its application in other complex spaces such as bus interchanges, airports, and museums.

Acknowledgements

The team would like to extend their sincere appreciation to:

Prof. Ngai-Man (Man) Cheung and Prof. Cyrille Jegourel, for their insights and patient guidance that have facilitated the successful navigation of this project.

Dr. Susan Wong for generously dedicating her time to mentor and provide invaluable advice, which helped to enhance the team's communication skills, presentation, poster, video and report.

Dr. Alexander Yip, Ms. Emily Chew Hwee Hoon, and Ms. Carol Yap for their unwavering support, encompassing logistical assistance and valuable suggestions, which have been instrumental in the project’s progress and achievements.

Ms. Jasmine Tan for her continued support during the Institutional Review Board application process.

Family members, friends and the SUTD community for their participation in the user studies which have played a critical role in shaping the project’s outcome.

We would not have been able to develop Glowing Guide without all of your generous support!