Soulnest Гар утасны аппликейшн by Yixuan Song and Jiahui Yu

Soulnest Гар утасны аппликейшн by Yixuan Song and Jiahui Yu is a highly esteemed winner of the very prestigious 2026 A' Design Award Төмөр шагнал in Мобайл технологи, аппликейшн ба программ хангамжийн дизайн Competition Category.

ТөмөрМобайл· 2026

Soulnest Гар утасны аппликейшн

by Yixuan Song and Jiahui Yu

Client: SoulNest

A' Design Award Төмөр шагнал Winner in Мобайл Category

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The Design

About Soulnest Гар утасны аппликейшн

Soulnest бол сэтгэцийн эрүүл мэндийг дэмжих зорилгоор бүтээгдсэн гар утасны аппликейшн юм. Уг аппликейшн нь хэрэглэгчдийг дөрвөн алхмаар удирдан чиглүүлдэг хиймэл оюун ухаант хамтрагчийг санал болгодог: хамтрагч сонгох, үнэлгээ хийх, эмчилгээ болон хямралын үеийн тусламж. Царайны шинжилгээ болон зүрхний цохилтыг мэдрэх технологийн тусламжтайгаар хамтрагч нь өөрийн өнгө аяс болон зөвлөгөөгөө бодит цаг хугацаанд тохируулан өөрчилдөг. Хэрэглэгчдэд сэтгэл санааны стрессээ зохицуулахад нь туслахын тулд танин мэдэхүйн зан үйлийн эмчилгээний аргуудыг ашигладаг. Бүх боловсруулалт төхөөрөмж дээр хийгддэг тул аппликейшн нь офлайн горимд ажилладаг бөгөөд хувийн мэдээллийг нууцлалтай хадгалдаг.

The Recognition

About the A' Design Award Төмөр шагнал

Soulnest Гар утасны аппликейшн нь A' Design Award Төмөр шагналын ялагч бөгөөд сайн зохиогдсон бүтээлээс хүлээгддэг мэргэжлийн болон үйлдвэрлэлийн шаардлагыг хангасан сайн загварт олгодог нэр хүндтэй хүлээн зөвшөөрөлт юм. Төмөр ялагчид бүтээгчдийнхээ агуу ур чадвар, өндөр мэргэшил, мэргэжилтний ойлголт, бүтээлч чадавхийг харуулдаг. Soulnest Гар утасны аппликейшн нь өндөр үнэлэгдсэн, биширсэн, хайрласан, практик, шинэлэг бүтээл байх болно гэж хүлээгддэг. Төмөр шагнал хүртсэн энэ загвар нь салбарын шилдэг туршлагыг нэгтгэж, мэдлэг, авьяастай холбогдсон чадварлаг техникийн шинж чанартай. Soulnest Гар утасны аппликейшн нь нухацтай байдлаараа хүндлэгддэг бөгөөд амьдралын чанарыг сайжруулж, дэлхийг илүү сайхан газар болгоход туслахаар зохиогдсон.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: 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.
Dimensions & Packaging: 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.
Tags: Mental Wellness, Ai Companion, Social Impact, Emotional Intelligence, Inclusive Design, Biofeedback, Digital Health, Wearable Interaction, Cbt Therapy, Accessibility
Production Technology: 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.
Design Challenge: 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.
Research: 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.
Inspiration: 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.
Project Duration: The project started in Nov 2024 in San Jose and launched the beta version in Aug 2025.
Operation Flow: 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.
Team Members: Yixuan Song
Jiahui Yu
Xianxi Liao