Upgrove Aplikasyon sa Pagtimbang-timbang sa Ibabaw nga Bahin sa Bukton ni Xinke Coco Wu

Ang disenyo nga Upgrove Aplikasyon sa Pagtimbang-timbang sa Ibabaw nga Bahin sa Bukton ni Xinke Coco Wu usa ka labihan ka tinahod nga mananaog sa prestihiyosong 2026 A' Design Award nga Puthaw sa Kategoriya sa Kompetisyon sa Disenyo sa Teknolohiyang Mobile, Aplikasyon ug Software.

PuthawMobile· 2026

Upgrove Aplikasyon sa Pagtimbang-timbang sa Ibabaw nga Bahin sa Bukton

ni Xinke Coco Wu

Kliyente: The Multiple Sclerosis Center of Georgia

Mananaog sa A' Design Award nga Puthaw sa Kategoriya sa Mobile

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Mga Kolor

Ang Disenyo

Bahin sa Upgrove Aplikasyon sa Pagtimbang-timbang sa Ibabaw nga Bahin sa Bukton

Ang Upgrove usa ka mobile nga aplikasyon alang sa pagtimbang-timbang sa rehabilitasyon sa ibabaw nga bahin sa bukton diha sa balay. Ang aplikasyon naggamit sa camera-based motion capture sa ordinaryong mga telepono, tablet ug telebisyon nga adunay front-facing nga kamera, busa wala nay gikinahanglan nga mga wearable sensor. Ang mga standardized nga klinikal nga pagsulay sa lihok gihimo nga mga mini-game nga may temang umahan. Ang computer vision moanalisar sa lihok aron mabanabana ang range of motion, katukma ug kalig-on, ug adunay iskor nga mahatag human sa matag kalihokan. Ang mga taho sa pag-uswag nagtugot sa mga pasyente sa pagsubay sa ilang dugay nga pagkaayo ug nagtugot sa mga clinician sa pagsusi sa performance gikan sa layo.

Ang Pag-ila

Bahin sa A' Design Award nga Puthaw

Upgrove Aplikasyon sa Pagtimbang-timbang sa Ibabaw nga Bahin sa Bukton usa ka mananaog sa A' Design Award nga Puthaw, usa ka dungganon nga pag-ila nga gihatag sa maayong mga disenyo nga nakatagbo sa propesyonal ug industriyal nga mga gikinahanglan nga gipaabot gikan sa maayo ang pagkadisenyo nga mga paglalang. Ang mga mananaog sa Puthaw nagpakita og dakong kahanas, taas nga espesyalisasyon, eksperto nga pagsabot, ug mamugnaon nga abilidad sa ilang mga tiglalang. Gilauman nga ang Upgrove Aplikasyon sa Pagtimbang-timbang sa Ibabaw nga Bahin sa Bukton mahimong gipabilhan, gihangaan, ug gihigugma nga paglalang nga praktikal ug bag-o. Kini nga disenyo nga nakadaog og A' Design Award nga Puthaw naghiusa sa labing maayong mga praktis sa industriya ug adunay hanas nga teknikal nga mga kinaiya nga nalambigit sa kahibalo ug talento. Upgrove Aplikasyon sa Pagtimbang-timbang sa Ibabaw nga Bahin sa Bukton gitahod tungod sa pagkamaabtik niini ug gidisenyo aron maghatag og mga pagpaayo sa kalidad sa kinabuhi nga makatabang sa paghimo sa kalibutan nga mas maayong dapit.

Luyo sa Disenyo

Press Kit

Mga kredito, mga miyembro sa team ug teknikal nga mga detalye nga gihatag sa tigdisenyo.

Talagsaong mga Kinaiya: UpGrove addresses a key gap in upper-limb rehabilitation, where accurate assessments are typically limited to clinical settings and recovery progress remains largely invisible between visits. The system translates standardized clinical motion tests into intuitive farm-themed activities that patients can perform at home. Camera-based motion capture analyzes mobility and coordination while gameplay scores objectively quantify performance. Continuous self-tracking, progress visualization, and rewarding feedback help patients stay motivated while enabling clinicians to monitor long-term recovery beyond the clinic.
Gidak-on ug Pakete: The system operates on standard cross-platform devices such as mobile phones, tablets, and TVs equipped with front-facing cameras. Computer vision models analyze skeletal movement patterns to estimate joint mobility and motion trajectories without requiring wearable sensors. The application provides real-time visual guidance, scoring mechanisms, and progress-tracking dashboards. Motion data are translated into measurable indicators such as range of motion, accuracy, and movement stability, enabling scalable and sensor-free rehabilitation assessment.
Mga Tag: Digital Health, Upper-Limb Recovery, Sensor-Free Motion Capture, Computer Vision, Gamified Therapy, Gamified Assessment, Gesture Interaction, Motion Games
Teknolohiya sa Produksyon: UpGrove is implemented as a mobile application using camera-based motion capture powered by computer vision algorithms. The system analyzes upper-limb movements in real time to estimate range of motion, stability, and control. Gesture recognition maps clinical motion patterns to interactive game mechanics, while data processing generates performance scores and actionable feedback. The design integrates motion tracking, gamification, and data visualization to support continuous rehabilitation assessment.
Hagit sa Disenyo: The main challenge was translating clinically standardized upper-limb assessments into engaging digital interactions without compromising medical validity. Clinical tests are designed for accuracy rather than motivation, while game experiences prioritize engagement. The project required balancing these two perspectives by mapping therapeutic motions to intuitive gameplay mechanics. Another challenge was enabling reliable motion evaluation using device cameras without wearable sensors. Through close collaboration with clinicians and iterative prototyping, the design aligned clinical requirements with accessible interaction design.
Panukiduki: Mixed-methods design research was conducted to explore how clinical upper-limb assessments could become engaging gamified experiences. The study combined literature review, interviews with clinicians, domain experts, and patients, concept testing, usability testing, and technical validation. Data were gathered through clinical protocol analysis and motion interaction experiments using mobile cameras. Participants included 10+ clinicians and physical therapists and 3 patients. User testing results indicated that UpGrove significantly improved patients’ visibility of recovery progress, motivation to perform self-assessments, and accessibility of upper-limb rehabilitation beyond clinical environments.
Inspirasyon: UpGrove was inspired by the gap between clinic-based upper-limb assessments and patients’ everyday rehabilitation experiences at home. Many patients lack visibility into their long-term recovery progress and often feel discouraged during extended rehabilitation periods. In addition, traditional assessments typically require clinical visits, making frequent monitoring inconvenient for patients and clinicians alike. Research with clinicians, patients, and engineers inspired us to explore how clinical assessments could be translated into intuitive motion games and objective performance scores using device cameras. By transforming an often invisible and clinic-isolated recovery process into a visible and accessible experience, UpGrove aims to improve engagement, accessibility, and continuity in long-term rehabilitation.
Gidugayon sa Proyekto: The project was initiated in 2023 as part of human-computer interaction research on digital rehabilitation. Concept development, interaction design, and prototype implementation were completed between 2024 and 2025. The project was developed through interdisciplinary collaboration among designers, engineers, clinicians, and patients to explore accessible at-home rehabilitation assessment. The design is currently being implemented by the Georgia Tech Contextual Computing Lab in collaboration with the Georgia Multiple Sclerosis Center.
Daloy sa Operasyon: Users launch UpGrove on a personal mobile device and create a personalized profile to receive tailored self-assessment tasks. On a regular schedule, patients perform guided upper-limb motion tests designed as farm-themed mini-games in their home environment. The front-facing camera captures body movements while the system analyzes gestures in real time. Visual cues guide users through therapeutic motions, and after each activity the system generates scores and progress feedback. Over time, the application builds longitudinal recovery reports that allow patients to understand their rehabilitation progress while also enabling clinicians to remotely review performance data and monitor patient recovery outside clinical visits.
Mga Miyembro sa Team: Design Lead: Xinke (Coco) Wu
Visual Designer: Jhih Rou (Iris) Sun
Motion Designer: Yameng Li
Mga Credit sa Imahen: Images and visual materials were created by Xinke Wu (Designer), Jhih Rou (Iris) Sun (Designer) with AI-assisted generation tools like ChatGPT and Gemini, UpGrove Project, 2025.