Monica ヘルスケアモバイルアプリケーション by Muling Huang and Xintong Li is a highly esteemed winner of the very prestigious 2021 A' Design Award 銅賞 in モバイル技術・アプリケーション・ソフトウェアデザイン Competition Category.
銅モバイル· 2021
Monica ヘルスケアモバイルアプリケーション
by Muling Huang and Xintong Li
Client: Zhejiang University
A' Design Award 銅賞 Winner in モバイル Category
Verified Award Winner
Verify Award Status for #110504The Design
About Monica ヘルスケアモバイルアプリケーション
Monicaは、多嚢胞性卵巣症候群（PCOS）を抱える女性のためのモバイルアプリケーションです。本アプリケーションは人工知能と対話型インターフェースを活用しており、シンプルな会話を通じて情報が提供されます。Monicaはこの疾患をわかりやすい言葉で説明し、ユーザーが入力した個人情報に基づいてカスタマイズされたガイダンスを提示します。ガイダンスの内容は、運動、規則的な休息、食事計画、時間どおりの服薬にわたります。コミュニティセクションでは、ユーザー同士が体験を共有し、互いに支え合うことができます。本アプリケーションはiOSおよびAndroid端末向けに開発されています。
The Recognition
About the A' Design Award 銅賞
Monica ヘルスケアモバイルアプリケーションは、創造性、独創性、鋭い洞察力で際立つ傑出したデザインに授与される、高い権威をもつ評価である A' Design Award 銅賞の受賞作品です。銅賞の受賞作品は、十分に巧みで印象的なほど創造的な工芸品であり、デザイナーの豊富な経験、想像力、機知を裏づけています。Monica ヘルスケアモバイルアプリケーションは、高く評価され、称賛され、愛される品であり、顕著にプロフェッショナルで革新的であることが期待されます。この A' Design Award 銅賞を受賞したデザインは、芸術・科学・デザイン・技術のベストプラクティスを取り入れており、細部への配慮に優れています。Monica ヘルスケアモバイルアプリケーションは、ニーズを見事に満たし、欲求に触れ、感情を魅了し、好奇心を引きつけます。
Behind the Design
Press Kit
Credits, team members and technical details provided by the designer.
- Unique Properties
- Monica is an app designed for women with PCOS (polycystic ovary syndrome). Based on artificial intelligence technology, Monica simulates the role of girlfriends, popularizes knowledge related to diseases for female patients, encourages patients with PCOS to face up to diseases, and guides patients to actively adjust themselves and pay attention to their endocrine system health. Monica calls on women to put down their psychological burden, get treatment and embrace a better life.
- Dimensions & Packaging
- The app is designed for iOS & Android platforms, fitting various screen sizes.
Referring to the submitted entry the design is made for iPhone 11 Pro. Screen Size 1242px x 2688px and Resolution 458 ppi. - Tags
- Female, health, care, mobile app, community, artificial intelligence
- Production Technology
- Conversational AI is the key realization technology of Monica, which is presented in the form of a dialog-like user interface (Conversational UI). Conversational UI (CUI) can interact with users in the most natural and friendly way of dialogue, making digital products not as cold as machines, and closer to the real needs of users. For Monica, an app that focuses on women's health, this format is perfect.
- Design Challenge
- We had to create a friendly, trustworthy and empathetic role for women, and provide humanized and customized support and guidance for patients with PCOS. We hope that Monica can help them face the disease, actively treat it, and reduce negative emotions without overly interfering in the lives of patients.
- Research
- Our research in this project is mainly about how to ensure that the design provides physical and psychological support for women with PCOS. Through literature research and interviews with doctors, patients and other women, we learned about the treatment methods of PCOS and the true psychological state and demands of target users. After that, we designed Monica version 1.0 and solicited feedback from them, through which we conducted further evaluation and optimization to form the current version.
- Inspiration
- A common hormonal disorder that affects ovaries in women during childbearing years. At least one out of every ten women in the world has a PCOS (polycystic ovary syndrome). Worryingly, due to women's neglect, nearly 70% of PCOS women worldwide are not diagnosed in time.
- Project Duration
- The project started in July 2020 and finished in September 2020 in China.
- Operation Flow
- Through the selection and recording of personal information, Monica provides customized treatment guidance for women with PCOS. Monica instructs them to adjust their endocrine system by strengthening exercise, regular work and rest, planning a diet, and taking medication on time. In addition, users can share their experiences and encourage each other in the community.
- Team Members
- Muling Huang
Xintong Li
Pitchayapat Sonchaeng
Lingyan Zhang
Yue Hao
Yingqiao Chen
Ying Zhou
Xiaoqing Wang
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