Smart Technologies in Healthcare

Bruno Bouchard

• Publisher: CRC Press
• Year: 2017
• ISBN:
  9781351381932
• Edition: 1
• Topic: Computer Science
• Subtopic: Software Development
• Index: Computer Science

Assistive technologies for the old and people with disabilities is now a very active field of research. It also constitutes a very profitable market (expected to reach US $60 billion p.a. by 2018). The book covers key aspects of this important field and provides guidelines for developing assistive technologies in smart environments. The book also presents the new paradigm of open innovation used by the most prolific research teams around the world. The latest developments in the field are given. Overall this book will be a reference for researchers, practitioners and engineers.

Contents

Preface

1. Ambient Smart Assistive Technologies: Challenges and Perspectives

Bruno Bouchard and Sébastien Gaboury

2. Challenges in Developing Smart Homes: Human Perspective

Julie Bouchard, Miryam Lépine El Maaroufi and Marie-Pier Dufour

3. Pervasive Computing and Ambient Physiological Monitoring Devices

Sung Jae Isaac Chang, Jennifer Boger, Jianfeng Qiu and Alex Mihailidis

4. Designing Formally-controlled Smart Home Systems for People with Disabilities

Sébastien Guillet, Bruno Bouchard and Abdenour Bouzouane

5. Context-Aware Service Provision in Ambient Intelligence: A Case Study with the Tyche Project

Charles Gouin-Vallerand

6. Applying Data Mining in Smart Home

Kevin Bouchard, Frédéric Bergeron and Sylvain Giroux

7. Preliminary Evaluation of a Digital Diary for Elder People in Nursing Homes

Laetitia Courbet, Agathe Morin, Jérémy Bauchet and Vincent Rialle

8. Monitoring Medication Adherence in Smart Environments in the Context of Patient Self-management A Knowledge-driven Approach

Patrice C. Roy, Samina Raza Abidi and Syed Sibte Raza Abidi

Index

1

Ambient Smart Assistive Technologies

Challenges and Perspectives

Bruno Bouchard and Sébastien Gaboury

1. Introduction

Today, most Western countries face an unprecedented demographic crisis caused by accelerated ageing of its population (United Nations 2013). This is made worse by a lack of resources and shortage of qualified home-care workers. Senior citizens, many of whom suffer from the loss of autonomy caused by cognitive or physical disorders, or both, wish to remain at home as long as possible. Staying in the home is clearly desirable not only from an economic point of view (Oderandi et al. 2012), but also because it offers a better quality of life by allowing the deinstitutionalization that is consistent with societal values: people should live as normal a life as possible without segregation and enjoy a dignified existence with full access to autonomy. For many seniors with moderate to severe functional dependence, however, ageing at home entails coping with numerous risks and practical challenges. The home environment has to be adapted, if not technologically enhanced, using intelligent technologies and sensors to offset cognitive and physical deficiencies, to provide assistance and guidance, to ensure safety and to support natural caregivers and professionals in their work. This vision of the future, which has now become a reality, originated in 1988 at the Xerox Palo Alto Research Center (PARC), resulting in the work entitled ‘The Computer for the 21st Century’ by American scientist, Mark Weiser (Weiser 1991). From the early 1990s, a large community of scientists developed around this specific research niche (Blackman et al. 2015), actively seeking technological solutions for these very human problems by employing such concepts as ubiquitous sensors, ambient intelligence (AmI) and assistive technologies to keep people in their homes. The idea achieved maturity in the mid-2000s and we have since seen the fruits of this research develop into tangible innovations, technologies to promote autonomy and quite substantial economic spinoffs. For instance, in the United States alone, the market for assistive technologies based on ambient intelligence will reach approximately $60 billion (US) a year by 2018, with expected annual growth of nearly 6 per cent over the next decade (BCC Research 2013).^12*

1.1What is Ambient Assisted Technologies?

In general, Ambient Assisted Technologies (AAT) refer to the use of an array of electronic devices—sensors and actuators or effectors—incorporated into everyday objects, such as cabinet doors, stoves, lamps, screens and so on in a transparent way, meaning that they are not visible to the user, in order to monitor the user’s status and provide assistance as needed, such as advice, feedback, guidance or warning—of a stove left on, for example, based on information collected and historical data (Ramos et al. 2008). In the scientifi literature (Queirós et al. 2015), the interdisciplinary challenges related to this area are regarded as hugely complex and many key questions require investigation. For instance:

• What technologies should be developed and applied in order to meet the needs of the people in need, natural caregivers and practitioners?
• What kinds of sensors and actuators are better used?
• How should the necessary models of artificial intelligence be developed in order to implement these technologies?
• How are they to be adapted to user profiles?
• How are they to be deployed and maintained?
• Can technology improve the ability of the people with diminished autonomy to perform day-to-day activities?
• What new skills will practitioners need to acquire?
• What are the productivity gains for the healthcare system?
• How to develop marketing strategies and ensure the transfer of technology to enterprises?
• What is ethically acceptable and what is not?

The great difficulty in addressing the scientific issues in a field where the needs are so pressing is attributed to a number of factors—the almost unprecedented interdisciplinarity of the questions to be researched, the substantial infrastructure and equipment requirements for prototyping, the difficulties research teams face in establishing partnerships with the public and private sectors and with users in order to carry out experiments that demonstrate the effectiveness of the proposed technological solutions and so on. A few teams actually have access to this combination of key factors, which are the basis for efficiency in developing ambient assisted technologies.

1.2 Assistive Technologies vs. Automation

Often, the term ‘assistive technology’ is used to describe what is, in fact, an ‘automated system’. For the sake of this book, we think it is important to clearly define both the concepts.

• Automated System. A system made of sensors and actuators which perform actions on behalf of the person. Most of the time, this kind of system is made for carrying out the task for a person in order to alleviate his workload. It is good in the context of a factory, for instance, where you want to execute a maximum of tasks without human interventions, in order to minimize the number of employees. In the context of assistance, this is actually bad because the system fails to increase the user’s autonomy.
• Assistive System. An assistive system is also made of sensors and actuators, like the automated one. However, we can say that the assistive system is smarter than the automated one. In this sense, instead of simply performing the task for the user, it will try to provide real-time assistance for completing activities to increase the autonomy of the person. Of course, in case of immediate danger, the system will perform actions directly, but the main purpose of the system is to help the user to carry out his activities; not to perform them on his behalf. This provides physical and psychological benefits to the user.

The difference between both the concepts may seem subtle. In fact, an assistive system is a specific form, or a more evolved form of automated systems. To be sure to understand correctly, let’s conclude this section with a small example. Let’s say that Peter, a cognitively impaired user with head trauma, is cooking a chicken on the stove. After 40 minutes, Peter is distracted by the phone and after the call; he goes to his bedroom and forgets the chicken. After a certain delay, let’s say 20 more minutes, the smart home system will take some action. The question is: Which action should the system make? In the case of an automated system, it will simply cut the power of the stove. This action is correct in order to preserve the safety of the person, but it does little to help the user in his rehabilitation process of restoring his cognitive abilities. On the other hand, an assistive system would begin by sending cues, hints and reminders to the user. For instance, it could begin by flashing lights in order to draw a path to the kitchen. Once the user is in the kitchen, it would send an audio message telling him that the chicken on the stove is ready. A screen can also show a video example of how to get the chicken out of the stove and how to turn off the power. Of course, if the user is unresponsive to a reasonable amount of prompting, or if there is an immediate danger, the system will cut off the power by itself.

2. Assistive Technologies: Open Innovation Model

Developing assistive technologies is not a simple task, especially in the academic field. As we described in Section 1, the challenge is complex because it is hugely interdisciplinary. Most of the universities tend to separate each field of research in different faculties, departments, etc. This approach by fields of research tends to complicate interdisciplinary projects. Moreover, the funding agencies also tend to field projects by specific field of research. For instance, in Canada, we have a specific national funding agency which supports research projects in the field of engineering and natural sciences. We also have another agency supporting projects in the medical field. But what about us? We are developing assistive systems with sensors and actuators (engineering), with artificial intelligence (computer sciences), which are adapted and tested with cognitively impaired patients (medical field). Another issue is related to the very applicative finality of what we are developing. Assistive technologies are not just concepts; they need to be conceptualized, prototyped and tested with real patients. To be efficient, a lab working in the field needs to be able to cover all those aspects properly. In the last decade, we saw a lot of research done in the field, but only few real assistive products came out of that good research. Often, research teams will only concentrate their efforts on the concept, or on the prototype. Teams often have difficulty in accessing real data, or having access to real users/patients to test their technologies.

To solve these issues, we deployed in our lab an innovative integrated research program covering the entire vertical process of technological development, using the ‘Open Innovation’ model developed by the renowned Harvard Business School (Cherbourg 2006) and recently adapted for assistive technologies by the British Academy of Management (Oderandi et al., 2012). In that model (Fig. 1), every technology generated by research must go through seven key steps in synergy with all the partners: users, practitioners, researchers, public agencies and private enterprises:

1. Pre-technology (for example, identification of needs)
2. Theoretical bases related to technology (for instance, data mining approaches)
3. Systems development and prototyping
4. Controlled-environment testing (laboratory...

Table of contents

• Cover
• Halftitle
• Title
• Copyright
• Preface
• Table of Contents