Aurora Programu ya Simu by Ping Chen is a highly esteemed winner of the very prestigious 2026 Tuzo ya Chuma ya A' Design Award in Usanifu wa Teknolojia ya Simu, Programu na Programu Competition Category.

ChumaSimu· 2026

Aurora Programu ya Simu

by Ping Chen

Client: Aurora

Tuzo ya Chuma ya A' Design Award Winner in Simu Category

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The Design

About Aurora Programu ya Simu

Aurora ni programu ya simu inayosaidia udhibiti wa hisia kwa watu wenye Adhd kupitia mwingiliano unaotegemea muziki. Kiolesura kinachanganya uundaji wa orodha za nyimbo zinazoendana na hali, shajara ya hisia mbalimbali, na muhtasari wa mifumo ya kila siku. Kila kiingilio cha shajara kinaunganisha wimbo wa sasa na vitelezi vya kiwango cha hisia pamoja na ujumbe mfupi. Mwonekano wa mwenendo unaangazia matukio muhimu wakati muziki uliboresha umakini au kupunguza msongo wa mawazo. Hali ya kuona iliyolandanishwa na mdundo hutoa viashiria laini vya mwendo wakati wa kusikiliza ili kusaidia utulivu.

The Recognition

About the Tuzo ya Chuma ya A' Design Award

Aurora Programu ya Simu ni mshindi wa Tuzo ya Chuma ya A' Design Award, utambuzi wenye heshima unaotolewa kwa miundo mizuri inayokidhi mahitaji ya kitaalamu na ya kiviwanda yanayotarajiwa kutoka kwa kazi zilizobuniwa vizuri. Washindi wa Chuma huonyesha ustadi mkubwa, utaalamu wa hali ya juu, uelewa wa kitaalamu na uwezo wa kibunifu wa waumbaji wao. Aurora Programu ya Simu inatarajiwa kuwa kazi inayothaminiwa sana, kupendwa na kuenziwa, ambayo ni ya vitendo na bunifu. Muundo huu ulioshinda Tuzo ya Chuma ya A' Design Award unajumuisha mbinu bora za tasnia na una sifa za kiufundi zenye uwezo zilizounganishwa na ujuzi na kipaji. Aurora Programu ya Simu inaheshimiwa kwa uangalifu wake na imebuniwa kutoa maboresho ya ubora wa maisha yanayosaidia kuufanya ulimwengu kuwa mahali bora zaidi.

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