Aurora Función Primaria: Aplicación móbil by Ping Chen is a highly esteemed winner of the very prestigious 2026 A' Design Award de Ferro in Deseño de Tecnoloxías Móbiles, Aplicacións e Software Competition Category.
FerroMóbil· 2026
Aurora Función Primaria: Aplicación móbil
by Ping Chen
Client: Aurora
A' Design Award de Ferro Winner in Móbil Category
Verified Award Winner
Verify Award Status for #182515The Design
About Aurora Función Primaria: Aplicación móbil
Texto do Libro: Aurora é unha aplicación móbil que apoia a regulación emocional das persoas con TDAH a través da interacción baseada na música. A interface combina a xeración de listas de reprodución axustadas ao estado de ánimo, un diario multiemocional e resumos de patróns diarios. Cada entrada do diario vincula a pista actual con controis deslizantes de intensidade emocional e unha breve nota. A vista de tendencias destaca os momentos clave nos que a música mellorou a concentración ou reduciu o estrés. Un modo visual sincronizado co ritmo proporciona suaves indicacións de movemento durante a escoita para favorecer o enraizamento.
The Recognition
About the A' Design Award de Ferro
Aurora Función Primaria: Aplicación móbil gañou o A' Design Award de Ferro, un recoñecemento prestixioso outorgado a bos deseños que cumpren os requisitos profesionais e industriais esperados de creacións ben deseñadas. Os gañadores Ferro demostran a gran habilidade, a alta especialización, a comprensión experta e a capacidade creativa dos seus creadores. Espérase que Aurora Función Primaria: Aplicación móbil sexa unha creación moi apreciada, admirada e querida que é práctica e innovadora. Este deseño gañador do A' Design Award de Ferro integra as mellores prácticas do sector e ten características técnicas competentes ligadas ao saber facer e ao talento. Aurora Función Primaria: Aplicación móbil é respectado pola súa minuciosidade e está deseñado para proporcionar melloras na calidade de vida que axudan a facer do mundo un lugar mellor.
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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