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Try-it-yourself table Peacock Lantern Shadow Movement Dance

Ann K. Chou

Multi-sensory artist, lantern-maker, access designer, artist-scientist

I create inclusive, sensory-based environments that spark improvised reflection and community connection.

Practice Overview

Lanterns that move. Shadows that tell. Sounds that guide.
Inclusive, eco-conscious spaces for play, improvisation, and reflection.

Ann K. Chou is an artist-scientist and researcher working with lanterns, shadow animation, improvised sound, and access-led performance. Her practice explores how meaning shifts across light, movement, language, and sensory difference.

Grounded in lived experience as a hard-of-hearing Cantonese speaker, Chou develops adaptive methods rather than fixed representations. Lantern figures remain physically still while light moves, producing animated shadows that respond to proximity, pacing, and audience attention. Materials are chosen with care, often incorporating recycled or low-impact elements, supporting both accessibility and environmental awareness. Speech, captions, and bilingual wordplay are treated as evolving tools rather than complete systems.

Her work spans performance, installation, workshops, and research-creation, often unfolding through iterative public tests rather than finished objects. Across contexts, she is interested in how access can function as a creative method—shaping form, rhythm, and shared spaces for intergenerational encounter and creative care.

About Ann

Ann K. Chou (she/her) is a hard-of-hearing, neurodivergent multi-sensory artist, access designer, artist-scientist, born in Hong Kong and currently active on the unceded lands of the xʷməθkʷəy̓əm and lək̓ʷəŋən peoplw —also known as Vancouver and Victoria, BC.

Her practice bridges science and art—from microscope imaging to lantern-building—working with light, shadow, recycled materials, and movement to explore access, ecology, and collective care. Ann celebrates broken objects, spontaneous collaboration, and joyful inclusion through tactile installations, sumi-e brushwork, and mobile lantern sculptures.

She believes things are meant to break—and be beautifully rebuilt.

Her materials often include translucent fabrics, bamboo, garden clippings, mesh, and upcycled plastics, designed for multisensory engagement and adaptability across diverse environments.

Learn Ann's Journey →

🖍️ Art Meets Health Data -- "Draw-Aloud Symptom/s:

Critical Ethnographic Design of Participant Personal Health Records for Patient Agency"

🎯 Method & Intent

This Master's Thesis project (2020-2023) reimagines electronic health records (EHRs) as shared spaces—not just clinical data, but co-authored stories. It centers patient agency and embodied knowledge beyond lab results.

  • Method: Critical ethnography + illustrated dialogue + community engaged research
  • Tools: Drawing kits, Draw-Aloud Protocol, ELITO sticky-note mapping
  • Focus: Patient-centred Data Story, agency, design justice, inclusive infrastructure

This work is part of my Master’s thesis in EHR Design Research within the School of Interactive Arts and Technology at Simon Fraser University (SFU). Read Ann's MSc Thesis on SFU Summit→

🖌️ Draw-Aloud Protocol in Action

In familiar, community-based settings, participants mapped their health journeys across three time landmarks—past, present, and future—through live sketching and spoken reflection. These visual timelines became expressive, multimodal health records.

The Draw-Aloud protocol is a guided procedure designed to support emotional safety and narrative expression. It was facilitated either live in person or via virtual platforms. A self-directed version was also developed as a photo-mailback kit, enabling participants to engage independently while following a structured, reflective flow.

Each session or kit began with a grounding exercise to honor the emotional vulnerability of illness storytelling. To support interpretability by future healthcare providers, we adopted a “Patient Explanation Model”, allowing participants to annotate their drawings with short descriptions or keywords in their own words.

🔎 Agentic Technology Personas & Design Impact

Technology is often framed as a neutral tool—but this project challenges that notion. Through iterative analysis-to-design loops using the ELITO method, we surfaced four agentic technology personas that reflect how people relate to health data not just functionally, but emotionally, symbolically, and ritually.

  • 🦇 Bat – Sonification, distance from metrics
  • 🐕 Dog – Ownership, portability
  • 🛕 Health Altar – Ritual, self-body scale
  • 🦋 Butterfly – Hope, visualization

These metaphors move beyond the idea of technology as a passive or purely clinical interface. They now guide inclusive service design and Draw-Aloud–based workshops, helping teams imagine future systems that are relational, multimodal, and grounded in lived experience.

  • Multimodal reflection
  • Inclusive infrastructure
  • Patient-centered data practices
Composite image showing participant drawings, sticky notes, and visual coding from the Draw-Aloud Symptom/s project.
A glimpse into “Draw-Aloud Symptom/s”—an art × service design thesis grounded in critical ethnography. The project engaged diverse participants in community settings using the Draw-Aloud protocol to map past, present, and future health experiences through drawing and reflection. Using the ELITO method, participant insights were translated into four technology personas—Bat, Dog, Health Altar, and Butterfly—each representing a unique relationship to health data and care. These personas now inform future blueprints and inclusive service design workshops.

🧱 Digital Foundations of Care Interfaces

🧩 These foundational experiments in data visualization and playful design set the stage for my Draw-Aloud protocol—where health stories became visual, relational, and co-authored. From dispatch maps to sumi-e gestures, each project explores how people interact with care through code, form, and feeling.

📊 HT (Heltcopter): Interactive Health Data Prototype

HT interface thumbnail: chart showing dispatch distance vs health outcomes.
Data visualization exploring emergency dispatch metrics and diagnosis-outcome relationships.

A pre-thesis visual reasoning tool testing intuitive exploration of dispatch distance, diagnosis, and outcomes. Initially built with Plotly.py and revised for D3.js, this live demo lets users place average lines and sense relationships dynamically.

Why it matters: Made data relational, spatial, and user-centered—laying the conceptual groundwork for Draw-Aloud protocols.

Tools: Plotly.py, D3.js

Explore Prototype →

🎮 Vincent Bird: Sumi-e Game Interface

Vincent Bird thumbnail: game scene with sumi-e brushwork on walls and terrain.
Unity 3D scene featuring hand-painted brush textures on mountains and level map.

A Unity-based student experiment by Ann merging Japanese brushwork with game design. Vincent Bird explores spatial interface and material presence through subtle gesture—bridging physical painting and virtual storytelling.

Why it matters: Demonstrated how even partial aesthetic intervention—like textured walls and mapped mountains—can reshape digital space toward multisensory access and embodied emotion.

Tools: Unity 3D, Sumi-e Texture Mapping

See My Code on GitHub →

🩺 ePROMS Portal: Patient-Reported Symptom Interface

ePROMS Portal thumbnail showing patient symptom entry interface.
Standards-based prototype for capturing PROMs using HL7 FHIR and LHC-Forms.

This interface explores how patients can report symptoms using clinically validated questionnaires. Implemented partially via LHC-Forms and custom FHIR JSON, it demonstrates how PROMs like PHQ-9 can be modeled and mapped to SNOMED CT and LOINC standards.

Status: Prototype — not a functional portal, but ready for integration into Patient Health Record (PHR) systems that support JSON-formatted, standards-compliant PROMs.

Why it matters: Bridges patient voice and clinical structure, offering a design-led lens into participatory care tools and semantic interoperability.

Tools & Standards: HL7 FHIR, LHC-Forms, JSON, LOINC, SNOMED CT

Explore Simplified Report → View Technical Repository →

AI & Service Design Portfolio

AF Discovery (AI4Good Internship Project – 2023)

An AI-assisted ultrasound analysis system co-developed to estimate fetal head circumference. Combines UNET segmentation with Random Forest regression to support low-resource maternal care.

🧬 View Project on GitHub
Diagram of the AF Discovery model showing fetal head segmentation and circumference estimation via ultrasound.
Segmentation and regression pipeline for fetal biometrics in maternal care.

Guide & Service Dog Accessibility Poster (2025)

Behavioral-insight–informed poster design to welcome neurodivergent individuals with service animals. Started from a CoPilot AI prompt and refined through visual/textual research on signage and stigma.

Illustrated poster showing a person with a guide dog entering a building, dog alert and focused.
Accessibility poster developed to support awareness of the Guide and Service Dog Act. Uses behavioral insight and inclusive visuals to affirm entry rights and reduce social friction for neurodivergent individuals accompanied by working animals.
🦮 View the Service & Guide Dog Poster

Access-Centered UX Scorecard (2025)

Designed for public sector teams without direct user testing capacity, this lightweight scorecard enables more inclusive UX evaluations. Developed independently, it combines behavioral frameworks with inclusive design literature to guide equitable assessments.

🧮 View UX Scorecard Overview
UX scorecard interface with dimensions, grading scale, and persona prompts shown on-screen.
UX evaluation tool built to help public service teams internalize access as a quality, not a checkbox. Features an interpretive grading scale, persona-grounded prompts, and metrics focused on comprehension, task success, and emotional burden.

Let’s Collaborate

Interested in a storefront activation, co-created workshop, or arts residency? Let’s build it together.

You're welcome to contact me via email: annreflection at gmail dot com

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