Aurora Elsődleges funkció: Mobilalkalmazás by Ping Chen is a highly esteemed winner of the very prestigious 2026 Vasdíj A' Design Award in Mobiltechnológia, alkalmazás és szoftver tervezése Competition Category.
VasMobil· 2026
Aurora Elsődleges funkció: Mobilalkalmazás
by Ping Chen
Client: Aurora
Vasdíj A' Design Award Winner in Mobil Category
Verified Award Winner
Verify Award Status for #182515The Design
About Aurora Elsődleges funkció: Mobilalkalmazás
Az Aurora egy mobilalkalmazás, amely zenei alapú interakción keresztül támogatja az ADHD-val élők érzelmi szabályozását. A felület ötvözi az állapothoz illeszkedő lejátszási listák generálását, egy többféle hangulatot rögzítő naplót és a napi minták összefoglalóit. Minden naplóbejegyzés összekapcsolja az aktuális számot a hangulati intenzitás csúszkáival és egy rövid megjegyzéssel. A trendnézet kiemeli azokat a kulcsfontosságú pillanatokat, amikor a zene javította a koncentrációt vagy csökkentette a stresszt. Egy ritmushoz szinkronizált vizuális mód finom mozgási jelzéseket nyújt a hallgatás közben a megalapozottság elősegítésére.
The Recognition
About the Vasdíj A' Design Award
Aurora Elsődleges funkció: Mobilalkalmazás a Vasdíj A' Design Award győztese, rangos elismerés a jó dizájnoknak, amelyek megfelelnek a jól megtervezett alkotásoktól elvárt szakmai és ipari követelményeknek. A vasgyőztesek alkotóik nagy tudását, magas fokú szakosodását, szakértői megértését és kreatív képességét mutatják. Aurora Elsődleges funkció: Mobilalkalmazás-tól azt várják, hogy nagyra becsült, csodált és kedvelt, gyakorlatias és innovatív alkotás legyen. Ez a Vasdíj A' Design Award kitüntetést elnyert dizájn integrálja az iparág legjobb gyakorlatait, és hozzáértő műszaki jellemzőkkel rendelkezik, amelyek szakértelemmel és tehetséggel párosulnak. Aurora Elsődleges funkció: Mobilalkalmazás-t alaposságáért tisztelik, és úgy tervezték, hogy az életminőséget javító fejlesztéseket nyújtson, amelyek segítenek a világot jobb hellyé tenni.
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
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