關於樂睦About Lumo

為高齡照護，建立可累積、可解釋、可信任的成效基礎建設。A measurable, explainable, trustworthy outcome layer for eldercare.

樂睦把「軟硬整合、一體交付」的標準化復能服務，與可累積的互動數據結合，讓照護的價值第一次被清楚看見。Lumo unites an integrated, standardized rehabilitation service with cumulative interaction data — so the value of care is finally visible.

使命Mission

照護的成效，不該只活在帶課者的經驗與紙本裡。Care outcomes shouldn't live only in instructors' memory and paperwork.

台灣長照與日照機構，長年面對「高度依賴帶課者經驗、課後紀錄繁瑣、成效無法量化」的結構性難題。樂睦把這些痛點，轉化為一套標準化、可被信任的成效輸出，並以可累積的互動數據，撐起連結機構與教具夥伴的雙向平台。Care institutions have long depended on instructors' intuition, drowning in post-session paperwork while outcomes stay unquantified. Lumo turns this into standardized, trustworthy outcome reporting — and a two-sided platform connecting institutions and device partners on cumulative data.

挑戰The challenge

科技在照護現場，為什麼難以落地？Why technology stalls on the care floor

長者的科技焦慮Tech anxiety

面對感測器、介面與被演算法評估，長者容易卻步——任何「看得見的科技」都是門檻。Sensors, screens, and being "scored" create hesitation; visible technology becomes a barrier.

照服員的負擔Caregiver workload

照護、帶課、紙本與評鑑文書多重夾擊，任何增加負擔的系統都會被理性抗拒。Stretched across care, classes, and paperwork, staff rationally resist anything that adds work.

機構的風險迴避Institutional caution

面對評鑑、稽核與家屬監督，對可能失敗或無明確回報的導入，機構傾向觀望。Under audits and family scrutiny, institutions hold back from adoption that may not pay off.

我們的方法Our approach

三層架構，分別回應三種阻力。Three layers, one for each barrier.

隱形科技 · 感測層Invisible technology · Sensing

把輕量感測藏進溫潤的實體教具，長者在音樂律動與認知遊戲中「活動即紀錄」，化解科技焦慮。Sensors hidden in warm instruments; activity becomes record, dissolving tech anxiety.

遊戲化 · 互動層Gamification · Interaction

標準化復能任務轉為遊戲化體驗，建立在自我決定理論與雙重任務訓練之上。Rehabilitation reframed as play, grounded in Self-Determination Theory and dual-task training.

可解釋 AI · 推論層Explainable AI · Inference

彙整數據，產出個別化成效報告與符合評鑑稽核的標準化報表。Synthesizing data into individualized reports and audit-ready documentation.

★ 時間性是核心：隱形科技是過渡橋樑，遊戲化隨世代加深，而「成效與合規」的 AI 推論層，價值不隨時間褪色。★ Time is central: invisible tech is a bridge, gamification deepens across generations, while the inference layer for outcomes & compliance keeps its value.

長期願景North star

成為區域長照評鑑的標準輔助系統。Becoming the standard support system for regional long-term care.

先以雙向儀表板與評鑑報告做扎實，靠指標性機構累積成功案例；再透過講師通路擴散；長期以累積的互動數據優化演算法，串起硬體、演算法與第一線場域的長照生態系。Start with a solid dashboard and audit reports, prove value with flagship institutions, expand through instructor channels, and — over time — refine algorithms on accumulated data, connecting hardware, algorithms, and the care floor into one ecosystem.

圖片佔位Image placeholder
場域 / 照護現場照片Care-setting photo

想更了解樂睦？Want to know more?

看看我們的產品與技術，或直接與團隊聊聊。Explore the product and technology, or talk to the team.

認識產品The product 聯絡我們Contact