Umushinga Aurora Primary Function: Porogaramu ya Telefoni wa Ping Chen ni uwatsinze igihembo cyubahwa cyane 2026 Igihembo cya A' Design Award cy'icyuma mu Cyiciro cy'Ihiganwa cya Telefoni Igendanwa.
IcyumaTelefoni Igendanwa· 2026
Aurora Primary Function: Porogaramu ya Telefoni
na Ping Chen
Umukiriya: Aurora
Uwatsinze Igihembo cya A' Design Award cy'icyuma mu Cyiciro cya Telefoni Igendanwa
Uwatsinze Igihembo Yemejwe
Emeza Uko Igihembo Gihagaze ku #182515Imigereranyo
Ibyerekeye Aurora Primary Function: Porogaramu ya Telefoni
Book Text: Aurora ni porogaramu ya telefoni ifasha abantu bafite Adhd kugenzura amarangamutima yabo binyuze mu mikoranire ishingiye ku muziki. Imbonerahamwe ihuza ikorwa ry'urutonde rw'indirimbo ruhuye n'imimerere, ikinyamakuru cy'imihindagurikire y'amarangamutima, n'incamake z'imikorere ya buri munsi. Buri nyandiko mu kinyamakuru ihuza indirimbo iriho n'imyitozo ya cursor igaragaza ubukana bw'amarangamutima hamwe n'inyandiko ngufi. Igaragaza ry'imigendekere ryerekana ibihe by'ingenzi aho umuziki wateje imbere ukwitondera cyangwa ugabanya umuhangayiko. Uburyo bw'amashusho buhuza n'injyana butanga inyandiko zoroheje z'urugendo mu gihe cyo kumva kugira ngo bushyigikire ubunyangamugayo.
Ishimwe
Ibyerekeye Igihembo cya A' Design Award cy'icyuma
Aurora Primary Function: Porogaramu ya Telefoni ni uwegukanye Igihembo cya A' Design Award cy'icyuma, ishimwe ry'agaciro ritangwa ku bishushanyo byiza bihuza ibyo umwuga n'inganda bikeneye ku bihangano byashushanyijwe neza. Abegukanye icyuma bagaragaza ubuhanga bukomeye, ubumenyi bwihariye, imyumvire y'inzobere n'ubushobozi bwo guhanga bw'ababikoze. Aurora Primary Function: Porogaramu ya Telefoni biteganyijwe ko izaba igihangano cyubahwa, gishimwa kandi gikundwa, gifatika kandi gifite udushya. Iki gishushanyo cyegukanye icyuma gihuza uburyo bwiza bukoreshwa mu nganda kandi gifite ibiranga bya tekiniki bifite ubushobozi, bifatanye n'ubumenyi n'impano. Aurora Primary Function: Porogaramu ya Telefoni yubahwa kubera gukora neza, kandi yashushanyijwe kugira ngo inoze ubuzima, ifashe gutuma isi iba nziza.
Inyuma y'Imigereranyo
Dosiye y'Itangazamakuru
Amazina y'abagize uruhare, abagize itsinda n'amakuru y'ubuhanga byatanzwe n'umuhanzi.
- Ibintu Bidasanzwe
- 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.
- Ibipimo n'Ipaki
- 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.
- Ibibazo Fatizo
- ADHD support, emotional regulation, mood based playlists, music journaling, rhythm synced visuals, neurodiverse wellness, focus support, calm support, behavior design
- Ikoranabuhanga ryo Guteza Imbere
- 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.
- Ikibazo cy'Ishusho
- 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.
- Ubushakashatsi
- 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. - Ibyatumye Habaho
- 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.
- Igihe cy'Umushinga
- 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.
- Uburyo bw'Imikorere
- 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.
- Patente
- Copyrights belong to Ping Chen, 2025.
- Abagize Itsinda
- Ping Chen
Haowei Zang
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