Robert Radziszewski, Hubert Kenfack Ngankam, Vincent Grégoire, Dominique Lorrain, Hélène Pigot and Sylvain Giroux
Assistive living technologies provide support for specific activities, transforming a home into a smart home. The purpose of this paper is to present how to design, implement…
Abstract
Purpose
Assistive living technologies provide support for specific activities, transforming a home into a smart home. The purpose of this paper is to present how to design, implement, deploy and install a personalized ambient support system for the elderly suffering from Alzheimer’s disease (AD) and nighttime wandering.
Design/methodology/approach
The intervention presented in this paper proceeds in two phases. During the monitoring phase, the system determines the profile of the person with AD, based on nighttime routines. Data are gathered from sensors dispatched in the smart home, coupled with physiological data obtained from sensors worn by the person. Data are then classified to determine engine rules that will provide assistance to the resident to satisfy their needs. During the second phase, smart assistance is provided to the person via environmental cues by triggering rules based on the person’s habits and the activities occurring during night.
Findings
The paper develops the architecture of a non-intrusive system that integrates heterogeneous technologies to provide a calm environment during night and limit wandering periods.
Practical implications
The goal is to help people age well at home as long as possible and recover a regular circadian cycle while providing more comfort to the caregiver.
Originality/value
The system presented in this paper offers a calm and personalized environment with music and visual icons to soothe persons with AD and encourage them to go back to bed. It is installed at the patient’s home using wireless technologies.
Details
Keywords
Mahdi Mirhoseini, Pierre-Majorique Léger and Sylvain Sénécal
In the past decade, the use of neurophysiological measures as a complementary source of information has contributed to our understanding of human–computer interaction. However…
Abstract
Purpose
In the past decade, the use of neurophysiological measures as a complementary source of information has contributed to our understanding of human–computer interaction. However, less attention has been given to their capability in providing measures with high temporal resolution. Two studies are designed to address the challenge of measuring users’ cognitive load in an online shopping environment and investigate how it is related to task difficulty, task uncertainty and shopping convenience.
Design/methodology/approach
Two experiments using behavioral and neurophysiological measures are conducted to investigate how various types of the cognitive load construct can be measured and used in an online shopping context.
Findings
Results of the first study suggest that although all cognitive load measures are influenced by task difficulty, only accumulated load (i.e. total cognitive load experienced during a task) is sensitive to task uncertainty. Results of the second study show that convenience negatively influences accumulated load, and the latter negatively influences user satisfaction.
Practical implications
Our research offers practical value by providing designers with a validated method to measure users’ cognitive load, enabling the identification of usability issues and design improvement.
Originality/value
This study contributes to the literature by developing a rich and temporally high-resolution measurement of the cognitive load construct and examining how it can inform us about users’ cognitive state in an online shopping environment.