Aurora 手機應用程式

由 Ping Chen

客戶: Aurora

流動類別嘅 A' Design Award 鐵獎得獎者

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驗證設計 #182515 嘅獲獎狀態

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設計

關於 Aurora 手機應用程式

Aurora係一款手機應用程式，透過以音樂為基礎嘅互動，幫助有專注力不足／過度活躍症（ADHD）嘅人士調節情緒。介面結合咗按狀態配對嘅播放清單生成功能、多重情緒日誌，以及每日模式總結。每篇日誌都會將當下播放嘅樂曲、情緒強度滑桿同埋一段簡短筆記連繫起嚟。趨勢檢視會突顯音樂幫助提升專注力或紓緩壓力嘅關鍵時刻。節奏同步嘅視覺模式，會喺聆聽期間提供柔和嘅動態提示，協助使用者穩定情緒、保持安定。

榮譽認可

關於A' Design Award 鐵獎

Aurora 手機應用程式是 A' Design Award 鐵獎得主，這是授予滿足人們對設計精良的創作所期待的專業與工業要求的優良設計的聲望認可。鐵獎得主展現出其創作者的高超技藝、高度專業化、專家級的理解力和創造能力。預計Aurora 手機應用程式將成為一件備受推崇、令人欽佩且被珍愛的創作，既實用又創新。這件贏得 A' Design Award 鐵獎的設計整合了行業最佳實踐，並擁有與專業知識和才華相結合的稱職技術特性。Aurora 手機應用程式因其嚴謹而受到尊重，旨在提供有助於讓世界變得更美好的生活品質改善。

設計背後

新聞資料包

由設計師提供嘅製作人員名單、團隊成員同技術詳情。

獨特屬性: 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.
尺寸同包裝: 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.
標籤: ADHD support, emotional regulation, mood based playlists, music journaling, rhythm synced visuals, neurodiverse wellness, focus support, calm support, behavior design
生產技術: 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.
設計挑戰: 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.
研究: 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.
靈感: 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.
項目時長: 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.
操作流程: 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.
專利: Copyrights belong to Ping Chen, 2025.
團隊成員: Ping Chen
Haowei Zang