Aurora Função Principal: Aplicativo Móvel por Ping Chen

O design Aurora Função Principal: Aplicativo Móvel por Ping Chen é um vencedor altamente estimado do prestigioso 2026 A' Design Award de Ferro na Categoria de Competição Design de Tecnologias Móveis, Aplicações e Software.

FerroDispositivo Móvel· 2026

Aurora Função Principal: Aplicativo Móvel

por Ping Chen

Cliente: Aurora

Vencedor do A' Design Award de Ferro na Categoria Dispositivo Móvel

7,288

Vencedor de Prémio Verificado

Verificar Estado do Prémio para #182515

Ver no A' Design Award Comunicado de Imprensa Selo do Prémio

Cores

O Design

Sobre Aurora Função Principal: Aplicativo Móvel

Texto do Livro: Aurora é um aplicativo móvel que apoia a regulação emocional de pessoas com TDAH por meio da interação baseada em música. A interface combina a geração de playlists correspondentes ao estado, um diário de múltiplos humores e resumos de padrões diários. Cada entrada do diário vincula a faixa atual a controles deslizantes de intensidade de humor e uma breve anotação. A visualização de tendências destaca momentos-chave em que a música melhorou o foco ou reduziu o estresse. Um modo visual sincronizado com o ritmo oferece suaves indicações de movimento durante a audição para apoiar o ancoramento.

O Reconhecimento

Sobre o A' Design Award de Ferro

Aurora Função Principal: Aplicativo Móvel conquistou o A' Design Award de Ferro, um reconhecimento prestigiado atribuído a bons designs que cumprem os requisitos profissionais e industriais esperados de criações bem concebidas. Os vencedores do Ferro demonstram grande habilidade, elevada especialização, compreensão especializada e capacidade criativa dos seus criadores. Espera-se que Aurora Função Principal: Aplicativo Móvel seja uma criação muito considerada, admirada e estimada, prática e inovadora. Este design vencedor do A' Design Award de Ferro integra as melhores práticas do setor e tem características técnicas competentes associadas a conhecimento especializado e talento. Pela sua minúcia, Aurora Função Principal: Aplicativo Móvel merece respeito e destina-se a proporcionar melhorias na qualidade de vida que ajudam a tornar o mundo num lugar melhor.

Por Trás do Design

Kit de Imprensa

Créditos, membros da equipa e detalhes técnicos fornecidos pelo designer.

Propriedades Únicas: 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.
Dimensões e Embalagem: 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.
Etiquetas: ADHD support, emotional regulation, mood based playlists, music journaling, rhythm synced visuals, neurodiverse wellness, focus support, calm support, behavior design
Tecnologia de Produção: 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.
Desafio de Design: 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.
Pesquisa: 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.
Inspiração: 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.
Duração do Projeto: 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.
Fluxo de Operação: 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.
Patentes: Copyrights belong to Ping Chen, 2025.
Membros da Equipa: Ping Chen
Haowei Zang