Upgrove د پورتنیو غړو د ارزونې اپلیکیشن د Xinke Coco Wu لخوا

Upgrove د پورتنیو غړو د ارزونې اپلیکیشن د Xinke Coco Wu لخوا د خورا باوقاره 2026 د اوسپنې A' Design Award جایزه په د ګرځنده ټکنالوژۍ، اپلیکیشنونو او سافټویر ډیزاین سیالۍ کټګوري کې یو ډیر ارزښتمن ګټونکی دی.

اوسپنهګرځنده· 2026

Upgrove د پورتنیو غړو د ارزونې اپلیکیشن

د Xinke Coco Wu لخوا

پیرودونکی: The Multiple Sclerosis Center of Georgia

په ګرځنده کټګوري کې د د اوسپنې A' Design Award جایزه ګټونکی

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سایټ وګورئ په A' Design Award کې وګورئ خبري خپرونه د جایزې بېج

رنګونه

ډیزاین

د Upgrove د پورتنیو غړو د ارزونې اپلیکیشن په اړه

اپګروو (Upgrove) یو ګرځنده اپلیکیشن دی چې په کور کې د پورتنیو غړو د بیارغونې ارزونې لپاره کارول کیږي. دا اپلیکیشن په معیاري ټیلیفونونو، ټابلیټونو او هغو تلویزیونونو کې چې مخکینۍ کامرې لري، د کامرې پر بنسټ د حرکت نیول (motion capture) کاروي، نو د اغوستلو وړ سنسرونو ته اړتیا نشته. معیاري کلینیکي حرکتي ازموینې د کرنې پر موضوع ولاړو کوچنیو لوبو ته اړول شوي دي. کمپیوټري لید (computer vision) حرکت تحلیلوي ترڅو د حرکت کچه، دقت او ثبات وارزوي، او د هر فعالیت وروسته یو نمرې ورکول کیږي. د پرمختګ راپورونه ناروغانو ته اجازه ورکوي چې اوږدمهاله رغیدنه تعقیب کړي او کلینیکي کارپوهانو ته اجازه ورکوي چې له لرې د فعالیت کتنه وکړي.

پیژندنه

د د اوسپنې A' Design Award جایزه په اړه

Upgrove د پورتنیو غړو د ارزونې اپلیکیشن د اوسپنې A' Design Award جایزې ګټونکی دی، یوه ویاړلې پېژندنه چې ښو ډیزاینونو ته ورکول کېږي چې هغه مسلکي او صنعتي اړتیاوې پوره کوي چې له ښه ډیزاین شویو جوړښتونو څخه تمه کېږي. د اوسپنې ګټونکي د خپلو جوړوونکو لویه مهارت، لوړه تخصص، کارپوهانه پوهه او خلاقي وړتیا ښيي. له Upgrove د پورتنیو غړو د ارزونې اپلیکیشن څخه تمه کېږي چې یو ډېر ارزښتناک، ستایل شوی او ګران جوړښت وي چې عملي او نوښتګر دی. دا د اوسپنې A' Design Award جایزې ګټونکی ډیزاین د صنعت غوره کړنلارې یو ځای کوي او وړ تخنیکي ځانګړتیاوې لري چې له پوهې او استعداد سره تړلي دي. Upgrove د پورتنیو غړو د ارزونې اپلیکیشن د خپل دقت له امله درناوی کېږي او د ژوند د کیفیت داسې ښه والی وړاندې کولو لپاره ډیزاین شوی چې نړۍ یو ښه ځای ګرځولو کې مرسته کوي.

د ډیزاین تر شا

خبري کټ

اعتبارونه، د ټیم غړي او تخنیکي توضیحات چې د ډیزاینر لخوا وړاندې شوي.

ځانګړي ځانګړتیاوې: 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.
ابعاد او بسته بندي: 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.
ټاګونه: Digital Health, Upper-Limb Recovery, Sensor-Free Motion Capture, Computer Vision, Gamified Therapy, Gamified Assessment, Gesture Interaction, Motion Games
د تولید ټیکنالوژي: 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.
د ډیزاین ننګونه: 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.
څیړنه: 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.
الهام: 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.
د پروژې موده: 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.
د عملیاتو بهیر: 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.
د ټیم غړي: Design Lead: Xinke (Coco) Wu
Visual Designer: Jhih Rou (Iris) Sun
Motion Designer: Yameng Li
د عکس اعتبار: 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.