Using Robots to Help Treat Alzheimer's Disease

August 09, 2021
an older woman looks at a robot's chest computer screen

At the IHP School of Nursing, collaboration with other researchers in the field fosters innovation. For Ruth Palan Lopez, PhD, GNP-BC, FAAN, collaboration has helped find ways to enhance quality of life for people living with dementia and their family caregivers.

a little white robot that looks like a human with a wide base of three wheels for feet and a computer screen for a chest

As a collaborator with the Detection, Care, and Treatment of Alzheimer’s Disease initiative at the University of Tennessee Knoxville (UTK), Dr. Lopez has been able to work with a team of researchers to create cognitive training protocols for smart, human-like robots to evaluate and assist patients with Alzheimer’s Disease and other cognitive disabilities. The proposed robotic system can detect the emotion and cognitive state of patients, communicate with patients, and process the gathered data to assess patient needs. The project is designed to make use of the humanoid robot's capabilities to assist patients with daily living activities such as meal preparation, laundry, and self-feeding.

In addition to developing the proposed robotic system, Dr. Lopez and the team at UTK conducted an online survey to assess the acceptability of humanoid robots for Alzheimer’s Disease and related dementia care. The survey received a total of 631 responses from healthcare professionals, caregivers, people with mild cognitive impairment, and the general public. The survey garnered an overall positive response, providing insight into patient needs and requirements.

Addressing the use of robots and how their capabilities for caring can be improved in the future, the team also carried out a systematic review of 99 articles published between 2015 and 2020 that covered the development of robot-assisted cognitive training. Their review, A Systematic Review of Robotic Rehabilitation for Cognitive Training, includes a meta-analysis of cognitive training protocols. With this analysis, the team found several areas needing improvement in respect to ethical issues, safety, social development, and feasibility, and proposed new strategies to benefit robotic cognitive training and rehabilitation in the future.


Collaborator Spotlight

profile photo of xiaopeng

Xiaopeng Zhao, PhD, professor in the Department of Mechanical, Aerospace, and Biomedical Engineering at UTK and project director of the research consortium on Detection, Care, and Treatment of Alzheimer’s Disease with the University of Tennessee’s One-UT Collaboration and Innovation Grant, began exploring the application of brainwave signals for controlling robotic devices 10 years ago. Alongside Dr. Lopez, Dr. Zhao has been able to further develop this use of technology to better understand how it can benefit the health care field in the future.

“Our proposed robotic system has the capacity to help patients accomplish basic instrumental activities of daily living, as well as help caregivers by reducing their levels of burden and stress. It is worth mentioning that the proposed robotic system is not intended to replace the caregivers, but to supplement the caregivers while still providing companionship for AD patients, since the system will learn to automatically assess patients’ cognitive states to better understand and respond to patients’ needs.

There have been many examples of AI applications for the prediction and detection of diseases, but the applications of social robots and human-robot interactions are still very limited. Besides technological challenges, the research of AI and robotics in healthcare is associated with many ethical and social-cultural issues. I hope to see more breakthroughs in this area. The research of AI and robotics in healthcare is truly multi-disciplinary, and AI and robotics will lead to disruptive changes in healthcare. New educational and training programs need to be developed to prepare the next generation workforce for this emerging field.” - Xiaopeng Zhao, PhD