School of EECS and Department of Psychology at Washington State University

NIH Training in Gerontechnology

Gerontechnology Projects


Activity Learning (AL)

CIL-VIZ: Clinician-In-The-Loop Visualization Tool

Routine Change Detection Using Estimotes

Optimization of Day Out Task Prediction

Robotic Activity Support (RAS)


Development and Usability Testing of a Digital Memory Notebook

Integration of Estimote Stickers into Smart Apartment Technology

A Personalized Prompting System

Usability Evaluation of Smart Home in a Box (SHiB)

Accelerometer Based Step Count Trackers, Are They Accurate Enough?


Digital Memory Notebook: Experimental Evaluation of Motivational Reward Strategies

Multicomponent Analysis of a Novel Digital Trail Making Task

Using Inertial Sensors to Quantify Changes Exhibited During Rehabilitation


Detecting Cognitive Decline Using Smart Home Technology

Using EEG and Machine Learning to Predict Action Goals from Data in the Human Mirror System

Development of a User-Friendly Interface Design

Machine learning Techniques for Diagnostic Differentiation of Mild Cognitive Impairment and Dementia

Predicting Activity Transitions for Prompting


CASASviz: Smart Home Web-based Visualizer System for Care-giving

Emotion Recognition Using Emotiv Sensor

PUCK on a Smart Phone

Qualifying Tremor Severity in Parkinson's and Essnetial Tremor Patients

Cerebral Vascular Responsivity and Cognitive Performance in Younger and Older Adults


This program is funded by NIA grant R25AG046114 and is carried out as a collaborative effort between the Center for Advanced Studies in Adaptive Systems (CASAS) and the Department of Psychology at Washington State University.

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