Alz Well 認知症ケアシステム by Akhil Patel is a highly esteemed winner of the very prestigious 2025 A' Design Award 銅賞 in デジタルプロダクトデザイン Competition Category.
銅デジタルプロダクト· 2025
Alz Well 認知症ケアシステム
by Akhil Patel
Client: Akhil Patel Designs
A' Design Award 銅賞 Winner in デジタルプロダクト Category
Verified Award Winner
Verify Award Status for #163729The Design
About Alz Well 認知症ケアシステム
Alz Wellは、認知症の介護者と患者のためのデジタルケアシステムです。本システムは、夜間利用に配慮したダークモードを備えた介護者向けアプリケーション、シンプルな音声操作とワンタップ操作が可能なスマートバンド、大画面を搭載したスマートスピーカーで構成されています。位置追跡機能により、徘徊した患者を介護者が見つけやすくなります。自動提案機能を備えた一元管理型のスケジュール機能が日々の生活習慣を支え、ウェルネスダッシュボードが患者と介護者双方の状態を可視化します。聞き慣れた声を選べる機能や状況に応じた画像は、患者の記憶の想起を助けます。認知症ケアにおける複数のニーズを、ひとつのシステムで解決します。
The Recognition
About the A' Design Award 銅賞
Alz Well 認知症ケアシステムは、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。Alz Well 認知症ケアシステムは、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。Alz Well 認知症ケアシステムは、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
- AlzWell includes a caregiver app with dark mode for night use, a smart band for patients with simple voice and one-tap interactions, and a smart speaker with a large screen for voice commands and viewing memories. Key features: AI location tracking for wandering patients, central scheduling with AI suggestions, custom voice options for familiarity, and a wellness dashboard for caregivers. Patients gain confidence with contextual visuals, and the system simplifies caregiver-patient management.
- Dimensions & Packaging
- App: Responsive iOS devices (iPhone SE - iPhone 16Pro Max)
Wearable: 36mm diagonal rectangular display
Speaker: 10.2in diagonal display (1.8in depth) - Tags
- Dementia, Alzheimer's, Monitoring, Mobile, Caregivers, SmartDevices, Voice, AI
- Production Technology
- For the app: The product was designed in Figma. The animations are done in Rive/SwiftUI. The v1 prototype is built specifically for iOS using Swift UI and UIKit with some parts done in React. The voice interactions and routing are done via a Large Language Model (LLM).
Wearable & Speaker: V2 additions to the ecosystem are designed in Figma and will be built on open-source libraries. - Design Challenge
- The most difficult part of this challenge was to create something that had zero learning curve for the dementia patient (achieved via voice and one-click UI) and build a comprehensive monitoring system for the caregiver while integrating their current daily routine into the caregiving workflow.
- Research
- The research was divided into 2 parts:
1. User research: I talked to 3 dementia patients' family members and caregivers to understand how their lives and daily schedules are affected while caregiving.
2. Desk Research: Extensive secondary research was done from online sources like the CDC website, caregiving.org, Alz.org, etc. - Inspiration
- Dementia caregivers are the worst-hit caregivers in the healthcare industry:
- 17 billion hours of unpaid care (mostly family)
- 60% have extreme stress levels
- 1/6 quit their jobs
Dementia is also the most expensive disease in the USA: 2.8 Trillion USD estimated societal cost by 2030.
Alz Well aims to reduce stress for caregivers by helping them:
- effectively managing the symptoms & well-being of the patient
- having a smart care framework at their fingertips
- manage their day-to-day schedules along with the caregiving responsibility using AI
- get help in emergencies - Project Duration
- Initial research and design: 6 months (May 2022 - Jul 2022)
Development: Ongoing
Location: San Francisco, CA - Operation Flow
- Alz Well is the first system designed for both dementia caregivers and patients, improving both lives. It uses AI for wandering tracking and time management, a breakthrough in dementia care. Unlike other solutions that address one issue at a time, Alz Well manages multiple dementia challenges in one system (wandering, reminiscence, home tasks, monitoring). The tech is invisible to the patient, requiring no learning curve, making it effortless to use for both patients and caregivers.
- Team Members
- Akhil Patel
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