Learning and Improving Alzheimer's Patient-Caregiver Relationships Via Smart Healthcare Technology

Summary

The purpose of this project is to develop a monitoring, modeling, and interactive recommendation solution (for caregivers) for in-home dementia patient care that focuses on caregiver-patient relationships. This includes monitoring for mood and stress and analyzing the significance of monitoring those attributes to dementia patient care and subsequent behavior dynamics between the patient and caregiver. In addition, novel and adaptive behavioral suggestions at the right moments aims at helping improve familial interactions related to caregiving, which over time should ameliorate the stressful effects of the patient's illness and reduce strain on caregivers. The technical solution consists of a core set of statistical learning based techniques for automated generation of specialized modules required by in-home dementia patient care. There are three main technical components in the solution. The first obtains textual content and prosody from voice and uses advanced machine learning techniques to create classification models. This approach not only monitors patients' behavior, but also caregivers', and infers the underlying dynamics of their interactions, such as changes in mood and stress. The second is the automated creation of classifiers and inference modules tailored to the particular patients and dementia conditions (such as different stages of dementia). The third is an adaptive recommendation system that closes the loop of an in-home behavior monitoring system.

Conditions

• Alzheimer Disease
• Caregiver Stress Syndrome

Interventions

BEHAVIORAL

Mood Monitoring and Behavioral Recommendation System

The purpose of this project is to develop a monitoring, modeling, and interactive recommendation solution (for caregivers) for in-home dementia patient care that focuses on caregiver-patient relationships. This includes monitoring for mood and stress and analyzing the significance of monitoring those attributes to dementia patient care and subsequent behavior dynamics between the patient and caregiver. In addition, novel and adaptive behavioral suggestions will be provided to family caregivers via text messages on project Smart phones at the right moments aimed to help improve familial interactions related to caregiving, which over time should ameliorate the stressful effects of the patient's illness and reduce strain on caregivers.

Sponsors & Collaborators

• University of Virginia

  collaborator OTHER

• The University of Tennessee, Knoxville

  collaborator OTHER

• Ohio State University

  lead OTHER

Principal Investigators

• Karen M Rose, PhD · Ohio State University

Study Design

Allocation

NA

Purpose

OTHER

Masking

NONE

Model

SINGLE_GROUP

Eligibility

Min Age

21 Years

Max Age

99 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2021-02-19

Primary Completion

2023-12-31

Completion

2024-12-31

Countries

• United States

Study Locations