Aurora Ọrụ Bụ Isi: Ngwa Ekwentị by Ping Chen

Aurora Ọrụ Bụ Isi: Ngwa Ekwentị by Ping Chen is a highly esteemed winner of the very prestigious 2026 Ihe Nrite A' Design Award nke Igwe in Nhazi Teknụzụ Mkpanaka, Ngwa na Sọftụwia Competition Category.

IgweMkpanaka· 2026

Aurora Ọrụ Bụ Isi: Ngwa Ekwentị

by Ping Chen

Client: Aurora

Ihe Nrite A' Design Award nke Igwe Winner in Mkpanaka Category

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The Design

About Aurora Ọrụ Bụ Isi: Ngwa Ekwentị

Ederede Akwụkwọ: Aurora bụ ngwa ekwentị nke na-akwado nhazi mmetụta uche maka ndị nwere Adhd site na mmekọrịta dabere na egwu. Ihu ngwa ahụ na-ejikọta mmepụta ndepụta egwu dakọtara na ọnọdụ, akwụkwọ ndekọ ọnọdụ obi dị iche iche, na nchịkọta usoro kwa ụbọchị. Ndekọ ọ bụla na-ejikọta egwu a na-egwu ugbu a na slider ike ọnọdụ obi yana obere ndetu. Nlele omume na-egosipụta oge ndị dị mkpa mgbe egwu mere ka uche dokwuo anya ma ọ bụ belata nrụgide. Ụdị nhụ anya jikọtara na rhythm na-enye ntụzịaka mmegharị dị nro mgbe a na-ege ntị iji kwado guzosie ike.

The Recognition

About the Ihe Nrite A' Design Award nke Igwe

Aurora Ọrụ Bụ Isi: Ngwa Ekwentị meriri A' Design Award nke Igwe, nnabata dị ugwu e nyere design ndị dị mma nke na-emezu ihe ndị a chọrọ n'ọrụ na ụlọ ọrụ nke a na-atụ anya n'ihe e kere eke ndị e mere nke ọma. Ndị meriri na Igwe na-egosi nka buru ibu, ọkachamara dị elu, nghọta ọkachamara na ikike imepụta nke ndị kere ha. A na-atụ anya na Aurora Ọrụ Bụ Isi: Ngwa Ekwentị ga-abụ ihe e kere eke a na-asọpụrụ nke ukwuu, a na-eto na a hụrụ n'anya nke bụ ihe bara uru ma dị ọhụrụ. Design a meriri A' Design Award nke Igwe na-ejikọta ụzọ kacha mma nke ụlọ ọrụ ma nwee àgwà teknụzụ kwesịrị ekwesị jikọtara na ihe ọmụma na talent. A na-asọpụrụ Aurora Ọrụ Bụ Isi: Ngwa Ekwentị maka nlezianya ya ma e mere ya ka ọ nye mmeziwanye ndụ nke na-enyere aka ime ka ụwa bụrụ ebe ka mma.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: Aurora is a music-based emotional support app for people with ADHD. Unlike traditional music platforms that recommend by genre or history, Aurora learns from users' mood journals to generate state-matched playlists, highlight moments when music helped, and reveal daily regulation patterns. Rhythm-synced visuals add gentle grounding during listening. The result is a low-effort tool that turns everyday songs into long-term self-regulation habits for wellbeing support.
Dimensions & Packaging: Platform: Mobile app (iOS and Android concept). Core inputs: current track metadata, time stamp, multi-mood intensity sliders, and short text notes. Core outputs: state-matched playlists, daily mood pattern summaries, highlighted key moments, and rhythm-synced visual modes. Data model links each journal entry to a song and a time period to support calendar navigation and trend views. Visual modes include multiple selectable patterns designed for low stimulation.
Tags: ADHD support, emotional regulation, mood based playlists, music journaling, rhythm synced visuals, neurodiverse wellness, focus support, calm support, behavior design
Production Technology: Aurora is designed as a mobile app concept with interactive prototypes. The experience is structured around three modules: playlist generation, mood journaling, and visual listening mode. Mood inputs are captured with multi-dimensional sliders and saved as time-stamped entries linked to the current music track. The app then summarizes entries into daily patterns and generates state-matched playlists based on past mood and listening records. Rhythm-synced visuals are designed to respond to BPM and audio energy.
Design Challenge: The main challenge was designing for mixed emotional states without adding cognitive load. Many mood trackers force a single label, while detailed journaling can feel too demanding for ADHD users. This was addressed by using a small set of mood dimensions with quick sliders, blended visual cues to reflect mixed states, and an insight-first trend view that highlights only the most meaningful moments instead of showing every entry.
Research: Research Objectives: Understand how people with ADHD use music to manage focus and mood.
Methodology: Semi structured interviews and concept testing. Data Collection and Research Tools Used: Interview notes, affinity mapping, storyboard and UI prototypes.
Participants: 10 adults with ADHD. Results: Music helps regulation but playlists rarely match the moment and helpful tracks are hard to recall.
Insights and Impacts: Led to mood logging, pattern highlights, and state matched playlists. Effect of the Research in Real-Life Phenomena such as Business, Society and Design Itself: Supports neurodiverse wellbeing and reframes music as intentional support.
Inspiration: After interviewing 10 people with ADHD, I saw a repeated pattern: music helps them focus or calm down, but generic playlists rarely match the moment, and it is hard to remember what worked later. This gap inspired Aurora. I combined mood journaling, pattern insights, and rhythm-synced visuals to turn listening into a repeatable self-regulation tool.
Project Duration: Aurora was designed over approximately 8 weeks in the United States (Boston, MA). Work included user interviews, synthesis, concept development, wireframing, and high-fidelity UI prototyping.
Operation Flow: Users listen to music, then log a quick moment: what they are listening to, how they feel across a few mood sliders, and a short note. Aurora turns these moments into state matched playlists and a daily trend view that highlights when music helped stabilize focus or calm. A visual mode adds gentle rhythm synced motion during listening to support grounding and reduce overstimulation.
Patents: Copyrights belong to Ping Chen, 2025.
Team Members: Ping Chen
Haowei Zang