Upgrove ແອັບພລິເຄຊັນປະເມີນແຂນສ່ວນເທິງ ໂດຍ Xinke Coco Wu

ຜົນງານ Upgrove ແອັບພລິເຄຊັນປະເມີນແຂນສ່ວນເທິງ ໂດຍ Xinke Coco Wu ເປັນຜູ້ຊະນະທີ່ໄດ້ຮັບຄວາມນັບຖືສູງຂອງລາງວັນ 2026 A' Design Award ລະດັບເຫຼັກ ອັນຊົງກຽດໃນໝວດການແຂ່ງຂັນ ການອອກແບບເທັກໂນໂລຊີມືຖື, ແອັບພລິເຄຊັ່ນ ແລະ ຊອບແວ.

ເຫຼັກມືຖື· 2026

Upgrove ແອັບພລິເຄຊັນປະເມີນແຂນສ່ວນເທິງ

ໂດຍ Xinke Coco Wu

ລູກຄ້າ: The Multiple Sclerosis Center of Georgia

ຜູ້ຊະນະ A' Design Award ລະດັບເຫຼັກ ໃນໝວດ ມືຖື

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ເຂົ້າເບິ່ງເວັບໄຊ ເບິ່ງທີ່ A' Design Award ຂ່າວເຜີຍແຜ່ ເຄື່ອງໝາຍລາງວັນ

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ການອອກແບບ

ກ່ຽວກັບ Upgrove ແອັບພລິເຄຊັນປະເມີນແຂນສ່ວນເທິງ

Upgrove ແມ່ນແອັບພລິເຄຊັນມືຖືສຳລັບການປະເມີນການຟື້ນຟູສະມັດຕະພາບແຂນສ່ວນເທິງຢູ່ເຮືອນ. ແອັບພລິເຄຊັນນີ້ໃຊ້ການຈັບການເຄື່ອນໄຫວຜ່ານກ້ອງຖ່າຍຮູບໃນໂທລະສັບ, ແທັບເລັດ ແລະ ໂທລະທັດທົ່ວໄປທີ່ມີກ້ອງດ້ານໜ້າ, ດັ່ງນັ້ນຈຶ່ງບໍ່ຈຳເປັນຕ້ອງໃຊ້ເຊັນເຊີແບບສວມໃສ່. ການທົດສອບການເຄື່ອນໄຫວທາງຄລີນິກຕາມມາດຕະຖານຖືກປ່ຽນເປັນມິນິເກມທີ່ມີທີມກ່ຽວກັບຟາມ. ເທັກໂນໂລຊີວິໄສທັດຄອມພິວເຕີວິເຄາະການເຄື່ອນໄຫວເພື່ອປະເມີນຂອບເຂດການເຄື່ອນໄຫວ, ຄວາມແມ່ນຍຳ ແລະ ຄວາມໝັ້ນຄົງ, ແລະ ຄະແນນຈະຖືກສ້າງຂຶ້ນຫຼັງຈາກແຕ່ລະກິດຈະກຳ. ບົດລາຍງານຄວາມຄືບໜ້າຊ່ວຍໃຫ້ຄົນເຈັບສາມາດຕິດຕາມການຟື້ນຕົວໃນໄລຍະຍາວ ແລະ ຊ່ວຍໃຫ້ແພດສາມາດກວດເບິ່ງຜົນການປະຕິບັດຈາກທາງໄກໄດ້.

ການຮັບຮູ້

ກ່ຽວກັບ A' Design Award ລະດັບເຫຼັກ

Upgrove ແອັບພລິເຄຊັນປະເມີນແຂນສ່ວນເທິງ ແມ່ນຜູ້ຊະນະ A' Design Award ລະດັບເຫຼັກ ເຊິ່ງເປັນການຍອມຮັບທີ່ມີກຽດສຳລັບການອອກແບບທີ່ດີ ທີ່ຕອບສະໜອງຄວາມຕ້ອງການທາງວິຊາຊີບ ແລະ ອຸດສາຫະກຳທີ່ຄາດຫວັງຈາກຜົນງານທີ່ອອກແບບມາຢ່າງດີ. ຜູ້ຊະນະລະດັບເຫຼັກສະແດງເຖິງທັກສະອັນຍິ່ງໃຫຍ່ ຄວາມຊຳນານສະເພາະສູງ ຄວາມເຂົ້າໃຈຂອງຜູ້ຊ່ຽວຊານ ແລະ ຄວາມສາມາດໃນການສ້າງສັນຂອງຜູ້ສ້າງ. Upgrove ແອັບພລິເຄຊັນປະເມີນແຂນສ່ວນເທິງ ຖືກຄາດວ່າຈະເປັນຜົນງານທີ່ໄດ້ຮັບການຍົກຍ້ອງສູງ ໜ້າຊົມເຊີຍ ແລະ ເປັນທີ່ຮັກແພງ ທີ່ໃຊ້ງານໄດ້ຈິງ ແລະ ມີນະວັດຕະກຳ. ການອອກແບບທີ່ຊະນະລະດັບເຫຼັກນີ້ລວມວິທີປະຕິບັດທີ່ດີທີ່ສຸດຂອງອຸດສາຫະກຳ ແລະ ມີຄຸນລັກສະນະທາງເຕັກນິກທີ່ມີຄວາມສາມາດ ເຊື່ອມໂຍງກັບຄວາມຮູ້ ແລະ ພອນສະຫວັນ. Upgrove ແອັບພລິເຄຊັນປະເມີນແຂນສ່ວນເທິງ ໄດ້ຮັບການເຄົາລົບສຳລັບຄວາມລະອຽດຮອບຄອບ ແລະ ຖືກອອກແບບເພື່ອປັບປຸງຄຸນນະພາບຊີວິດ ຊ່ວຍເຮັດໃຫ້ໂລກເປັນບ່ອນທີ່ດີຂຶ້ນ.

ເບື້ອງຫຼັງການອອກແບບ

ຊຸດຂ່າວ

ຂໍ້ມູນ, ສະມາຊິກທີມ ແລະ ລາຍລະອຽດທາງເຕັກນິກທີ່ສະໜອງໂດຍນັກອອກແບບ.

ຄຸນສົມບັດພິເສດ: 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.
ຂະໜາດ ແລະ ບັນຈຸພັນ: 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.
ແທັກ: Digital Health, Upper-Limb Recovery, Sensor-Free Motion Capture, Computer Vision, Gamified Therapy, Gamified Assessment, Gesture Interaction, Motion Games
ເຕັກໂນໂລຊີການຜະລິດ: 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.
ສິ່ງທ້າທາຍດ້ານການອອກແບບ: 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.
ການຄົ້ນຄວ້າ: 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.
ແຮງບັນດານໃຈ: 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.
ໄລຍະເວລາໂຄງການ: 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.
ຂັ້ນຕອນການດຳເນີນງານ: 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.
ສະມາຊິກທີມ: Design Lead: Xinke (Coco) Wu
Visual Designer: Jhih Rou (Iris) Sun
Motion Designer: Yameng Li
ເຄຣດິດຮູບພາບ: 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.