Aurora لومړنۍ دنده: ګرځنده اپلیکیشن by Ping Chen

Aurora لومړنۍ دنده: ګرځنده اپلیکیشن by Ping Chen is a highly esteemed winner of the very prestigious 2026 د اوسپنې A' Design Award جایزه in د ګرځنده ټکنالوژۍ، اپلیکیشنونو او سافټویر ډیزاین Competition Category.

اوسپنهګرځنده· 2026

Aurora لومړنۍ دنده: ګرځنده اپلیکیشن

by Ping Chen

Client: Aurora

د اوسپنې A' Design Award جایزه Winner in ګرځنده Category

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The Design

About Aurora لومړنۍ دنده: ګرځنده اپلیکیشن

اورورا یو ګرځنده اپلیکیشن دی چې د موسیقۍ پر بنسټ تعامل له لارې د ADHD لرونکو خلکو لپاره د احساساتو تنظیم ملاتړ کوي. انټرفیس د حالت سره سمون لرونکی پلے لیسټ جوړونه، د څو خویونو ژورنال، او د ورځني نمونو لنډیزونه سره یوځای کوي. د ژورنال هره ننوتنه اوسنۍ سندره د خوی د شدت سلایډرونو او یوې لنډې یادداشت سره نښلوي. د رجحان لید هغه کلیدي شیبې روښانه کوي کله چې موسیقۍ تمرکز ښه کړی یا فشار یې کم کړی وي. د ریتم سره همغږی شوی بصري حالت د اوریدلو پر مهال نرم حرکتي اشارې وړاندې کوي ترڅو د ثبات ملاتړ وکړي.

The Recognition

About the د اوسپنې A' Design Award جایزه

Aurora لومړنۍ دنده: ګرځنده اپلیکیشن د اوسپنې A' Design Award جایزې ګټونکی دی، یوه ویاړلې پېژندنه چې ښو ډیزاینونو ته ورکول کېږي چې هغه مسلکي او صنعتي اړتیاوې پوره کوي چې له ښه ډیزاین شویو جوړښتونو څخه تمه کېږي. د اوسپنې ګټونکي د خپلو جوړوونکو لویه مهارت، لوړه تخصص، کارپوهانه پوهه او خلاقي وړتیا ښيي. له Aurora لومړنۍ دنده: ګرځنده اپلیکیشن څخه تمه کېږي چې یو ډېر ارزښتناک، ستایل شوی او ګران جوړښت وي چې عملي او نوښتګر دی. دا د اوسپنې A' Design Award جایزې ګټونکی ډیزاین د صنعت غوره کړنلارې یو ځای کوي او وړ تخنیکي ځانګړتیاوې لري چې له پوهې او استعداد سره تړلي دي. Aurora لومړنۍ دنده: ګرځنده اپلیکیشن د خپل دقت له امله درناوی کېږي او د ژوند د کیفیت داسې ښه والی وړاندې کولو لپاره ډیزاین شوی چې نړۍ یو ښه ځای ګرځولو کې مرسته کوي.

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