REHABOT

REHABOT

Developing an AI Assistant to Support Geriatric Rehabilitation at Home

An increasing number of older people are recovering at home following a stay in a geriatric rehabilitation centre. The REHABOT project is developing a smart AI assistant that supports older people during their recovery at home and helps healthcare professionals gain a better understanding of the recovery process.

Reason 

Due to the ageing population, pressure on the healthcare system is rising rapidly. At the same time, older people are spending increasingly shorter periods in care facilities following a hospital or rehabilitation stay, meaning that a large proportion of their rehabilitation takes place at home. 

Digital rehabilitation platforms and sensor technology make it possible to support patients at home and monitor their progress remotely. However, these systems also present challenges. Healthcare professionals often lack context regarding patients’ home situations, making it difficult to interpret sensor data. Digital feedback also frequently lacks the personal nuance of face-to-face support. 

This creates a need for technology that not only collects data, but also helps to better understand it and to support patients in a way that is both clear and motivating.

Goal 

REHABOT is developing an AI-supported rehabilitation system that helps older people recover at home and supports healthcare professionals with remote monitoring and guidance. 

The project is investigating how artificial intelligence can contribute to more personalised, understandable and context-aware support during the rehabilitation process.

Expected outcomes 

The project delivers: 

  • An AI-powered home rehabilitation assistant for older people.
  • A digital platform for monitoring and support by healthcare professionals.
  • New insights into human-centred AI applications in healthcare.
  • Enhanced support for home rehabilitation and greater opportunities for personalised remote support.  

In addition, REHABOT helps to reduce the pressure on geriatric care and supports independent recovery at home. 

Image & Video

Publications

Project duration

from 01-09-2026 to 01-09-2028

Project manager

Bin Yu, associate lector, Digital Life, Hogeschool van Amsterdam

Researchers

Somaya Ben Allouch, lector, Digital Life, HvA

Michel Oey, docent-onderzoeker, Digital Life, HvA

Daniel Bossen, associate lector eHealth en Beweeggedrag, HvA

Margriet Pol. associate lector Technologie en Participatie, HvA

Shihan Wang, associate professor, Universiteit Utrecht

Marije Holwege, lector Geriatrische Revalidatie, Hogeschool Inholland & Omring

Funding

SIA RAAK Publiek

Partners