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Aurora اپلیکیشن موبایل by Ping Chen

Aurora اپلیکیشن موبایل by Ping Chen is a highly esteemed winner of the very prestigious 2026 جایزه آهنی A' Design Award in طراحی فناوری‌های موبایل، اپلیکیشن‌ها و نرم‌افزار Competition Category.


آهنموبایل· 2026

Aurora اپلیکیشن موبایل

by Ping Chen

Client: Aurora

جایزه آهنی A' Design Award Winner in موبایل Category

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Verified Award Winner

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The Design

About Aurora اپلیکیشن موبایل

آرورا یک اپلیکیشن موبایل است که از تنظیم هیجانی برای افراد مبتلا به ADHD از طریق تعامل مبتنی بر موسیقی پشتیبانی می‌کند. این رابط کاربری، تولید فهرست پخش متناسب با حالت، یک دفترچه چندحالته خلق‌وخو، و خلاصه‌های الگوی روزانه را با هم ترکیب می‌کند. هر ورودی دفترچه، آهنگ فعلی را با نوارهای لغزنده شدت خلق‌وخو و یک یادداشت کوتاه پیوند می‌دهد. نمای روند، لحظات کلیدی را که در آن‌ها موسیقی تمرکز را بهبود بخشیده یا استرس را کاهش داده است، برجسته می‌کند. یک حالت بصری همگام‌شده با ریتم، نشانه‌های حرکتی ملایمی را در حین گوش دادن ارائه می‌دهد تا از زمین‌گیری ذهنی پشتیبانی کند.

The Recognition

About the جایزه آهنی A' Design Award

Aurora اپلیکیشن موبایل برنده جایزه آهنی A' Design Award است، شناختی معتبر که به طراحی‌های خوبی اعطا می‌شود که الزامات حرفه‌ای و صنعتی مورد انتظار از آفرینش‌های خوب طراحی‌شده را برآورده می‌کنند. برندگان آهن مهارت بزرگ، تخصص بالا، درک کارشناسانه و ظرفیت خلاقانه سازندگان خود را نشان می‌دهند. از Aurora اپلیکیشن موبایل انتظار می‌رود آفرینشی بسیار ارجمند، ستوده و دوست‌داشتنی باشد که کاربردی و نوآورانه است. این طراحی برنده جایزه آهنی A' Design Award بهترین رویه‌های صنعت را یکپارچه می‌کند و ویژگی‌های فنی شایسته‌ای دارد که با دانش عملی و استعداد پیوند خورده است. Aurora اپلیکیشن موبایل به سبب دقتش محترم است و برای عرضه بهبودهای کیفیت زندگی که به بهتر شدن جهان کمک می‌کنند طراحی شده است.

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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