Yixuan Song and Jiahui Yu 嘅作品 Soulnest 流動應用程式

由設計師 Yixuan Song and Jiahui Yu 創作嘅 Soulnest 流動應用程式係備受推崇嘅 2026 A' Design Award 鐵獎得獎作品，獲獎類別為流動設計。

鐵流動· 2026

Soulnest 流動應用程式

由 Yixuan Song and Jiahui Yu

客戶: SoulNest

流動類別嘅 A' Design Award 鐵獎得獎者

6,064

經驗證嘅獲獎者

驗證設計 #182422 嘅獲獎狀態

訪問網站喺 A' Design Award 查看新聞稿獎項徽章

色彩

設計

關於 Soulnest 流動應用程式

Soulnest係一個為支援心理健康而創作嘅流動應用程式。呢個應用程式提供一個人工智能夥伴，引導用戶完成四個步驟：夥伴選擇、評估、治療同危機紓緩。透過面部分析同心率感測，個夥伴可以實時調整佢嘅語氣同引導方式。應用程式運用認知行為治療方法，幫助用戶管理情緒壓力。所有處理都喺裝置上進行，所以應用程式可以離線運作，同時保障個人資料私隱。

榮譽認可

關於A' Design Award 鐵獎

Soulnest 流動應用程式是 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Soulnest 流動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。Soulnest 流動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: Soulnest pioneers a paradigm shift in mental health by replacing traditional high-barrier appointments with an immediate, 4-step stabilization loop. It democratizes emotional care through de-stigmatized Ai avatars, delivering personalized support in under 10 seconds. Engineered for digital equity, it features on-device Ai inference for full offline functionality on low-end devices. Adhering to Wcag standards and low-arousal aesthetics, Soulnest fosters global resilience with proven 72% efficacy.
尺寸同包裝: Ai architecture: Green Llm framework optimized via Tensorflow lite for local edge-computing. Performance: On-device inference latency less than 120ms; 40% reduction in peak Cpu load via adaptive computation dimming. Bio-data: Heart rate sampling at 30fps; 100% on-device physiological processing (zero-cloud privacy). Universal equity: Lightweight build less than 150mb for low-end device compatibility. Compliance: Full Wcag 2.1 level Aa and Iso-standard data encryption for global digital wellness.
標籤: Mental Wellness, Ai Companion, Social Impact, Emotional Intelligence, Inclusive Design, Biofeedback, Digital Health, Wearable Interaction, Cbt Therapy, Accessibility
生產技術: Soulnest implements an empathic interaction system by merging Rppg bio-sensing with Facs-based facial tracking. This transforms passive interfaces into a responsive biofeedback loop, where Ai avatars dynamically adapt their tone and guidance based on real-time physiological stress markers. The design utilizes atomic design systems and flutter for cross-platform fluidity, ensuring a seamless experience that balances clinical rigor with a low-arousal visual language.
設計挑戰: The hardest part was achieving emotional authenticity while ensuring absolute privacy. Internal factors: We had to balance clinical rigor with a low-arousal Ux to prevent digital fatigue. External factors: Overcoming the limitations of on-device Ai inference was crucial to allow full functionality on low-end hardware without cloud dependency. Result: We successfully engineered a responsive bio-feedback loop that senses crisis through subtle physiological cues, navigating complex data-protection laws while delivering life-saving immediacy.
研究: We conducted a multi-modal mixed-methods study to bridge the 75% gap in immediate mental support. Methodology: Using evidence-based design and longitudinal tracking, we integrated Cbt frameworks with Ai interaction. Tools and participants: 1,200 diverse users were monitored via Rppg sensors and biometric wearables over 6 months. Results: Data showed a 72% increase in emotional regulation and a 58% reduction in crisis duration. Impact: The research proves that Ai-driven, bio-responsive tools can democratize mental healthcare, transforming high-barrier therapy into a scalable, stigma-free social infrastructure.
靈感: Inspired by the "silent crisis" where 75% of those in need lack mental support due to stigma and cost, Soulnest was born to bridge this gap. We observed that the "waiting period" is the deadliest barrier. Our goal was to create a "seamless emotional infrastructure" that is as natural as breathing. By integrating evidence-based therapy with Ai-driven empathy, Soulnest replaces medical coldness with human-centric warmth, ensuring support is a right, not a luxury, at the very moment of crisis.
項目時長: The project started in Nov 2024 in San Jose and launched the beta version in Aug 2025.
操作流程: 1. Selection: Users choose a personalized Ai companion based on visual aesthetics and emotional affinity. 2. Diagnosis: The Ai assesses mental states by analyzing facial micro-expressions and conversational patterns. 3. Therapy: Users access anytime Ai consultations with avatar using Cbt techniques for immediate emotional support. 4. Crisis relief: Interactive scenarios and sensory healing are triggered to de-escalate emotional spikes. 5. Biometric tracking: Wearable sensors monitor physiological indicators, allowing the Ai to proactively intervene and track long-term wellness trends.
團隊成員: Yixuan Song
Jiahui Yu
Xianxi Liao