Promotion of active ageing through interactive artificial agents in a smart environment (original) (raw)

Synergy of Distributed Agents in a Smart Home to Promote Physical Activity in Elderly Users

2018 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS 2018), Workshop on Robots for Assisted Living, 2018

This paper proposes a smart environment system aimed at promoting physical activity in elderly people, one of the three key dimensions of active and healthy aging. The system is based on the collaboration between a smart environment and two interaction devices-a social robot and an avatar. The system automatically detects sedentary behavior, promotes physical exercise through verbal interaction, and instructs and accompanies the user while performing the exercise. Pilot tests conducted with 30 users, 4 of which elderly, demonstrate: i) the system's synergistic relationship between the environment's sensors and interaction devices, ii) that the users find the system usable and acceptable, iii) how the proposed system's innovative technical features can be used to help elderly people remain physically active.

A Virtual Coach for Active Ageing Based on Sentient Computing and m-health

Lecture Notes in Computer Science, 2014

As life expectancy increases it has become more necessary to find ways to support healthy ageing. A number of active ageing initiatives are being developed nowadays to foster healthy habits in the population. This paper presents our contribution to these initiatives in the form of a conversational agent that acts as a coach for physical activities. The agent can be developed as an Android app running on smartphones and coupled with cheap widely available sport sensors in order to provide meaningful coaching. It can be employed to prepare exercise sessions, provide feedback during the sessions, and to discuss the results after the exercise. It incorporates an affective component that informs dynamic user models to produce adaptive interaction strategies.

A Multi-Agent System in Ambient Intelligence for the Physical Rehabilitation of Older People

Advances in Intelligent Systems and Computing, 2015

Ambient Intelligence (AmI) is a very active topic of research that is gaining more and more attention because of its characteristics, transparency and intelligence. Older people is one of the collectives that can take advantage of the use of AmI systems because, thanks to these characteristics, AmI systems can focus on older adults' real needs so that they satisfy one of their main motivations to adapt technological innovations: perceived benefits. And, perhaps, everything related to healthcare and home care is perceived by them as both valuable and beneficial. In this paper, it is presented the Multi-Agent architecture of a healthcare AmI system to treat older people' motor impairment problems by using specific devices to control the patient's movements. In this way, the natural relationship between AmI and MAS is being widely exploited. AmI proposes the development of context-aware systems that integrate different devices to recognize the context and act accordingly. Agents provide an effective way to develop such systems since agents are reactive, proactive and exhibit an intelligent and autonomous behavior. One of the main differences of our system is that it provides therapist with support to design new therapies, to adapt them to each specific person and to control their execution instead of using a fixed set of exercises.

Design and Evaluation of an Interactive Exercise Coaching System for Older Adults: Lessons Learned

Although the positive effects of exercise on the well-being and quality of independent living for older adults are well-accepted, many elderly individuals lack access to exercise facilities, or the skills and motivation to perform exercise at home. To provide a more engaging environment that promotes physical activity, various fitness applications have been proposed. Many of the available products, however, are geared toward a younger population and are not appropriate or engaging for an older population. To address these issues, we developed an automated interactive exercise coaching system using the Microsoft Kinect. The coaching system guides users through a series of video exercises, tracks and measures their movements, provides real-time feedback, and records their performance over time. Our system consists of exercises to improve balance, flexibility, strength, and endurance, with the aim of reducing fall risk and improving performance of daily activities. In this paper, we report on the development of the exercise system, discuss the results of our recent field pilot study with six independently-living elderly individuals, and highlight the lessons learned relating to the in-home system setup, user tracking, feedback, and exercise performance evaluation.

Designing an AI Health Coach and Studying Its Utility in Promoting Regular Aerobic Exercise

ACM Transactions on Interactive Intelligent Systems, 2020

Our research aims to develop interactive, social agents that can coach people to learn new tasks, skills, and habits. In this article, we focus on coaching sedentary, overweight individuals (i.e., “trainees”) to exercise regularly. We employ adaptive goal setting in which the intelligent health coach generates, tracks, and revises personalized exercise goals for a trainee. The goals become incrementally more difficult as the trainee progresses through the training program. Our approach is model-based—the coach maintains a parameterized model of the trainee’s aerobic capability that drives its expectation of the trainee’s performance. The model is continually revised based on trainee-coach interactions. The coach is embodied in a smartphone application, N utri W alking , which serves as a medium for coach-trainee interaction. We adopt a task-centric evaluation approach for studying the utility of the proposed algorithm in promoting regular aerobic exercise. We show that our approach ...

Towards a Robotic Personal Trainer for the Elderly

2019

The use of robots in the environment of the elderly has grown significantly in recent years. The idea is to try to increase the comfort and well-being of older people through the employment of some kind of automated processes that simplify daily work. In this paper we present a prototype of a personal robotic trainer which, together with a non-invasive sensor, allows caregivers to monitor certain physical activities in order to improve their performance. In addition, the proposed system also takes into account how the person feels during the performance of the physical exercises and thus, determine more precisely if the exercise is appropriate or not for a specific person.

Towards Social Robots that Support Exercise Therapies for Persons with Dementia

Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, 2018

Exercise therapy for dementia care helps patients improve balance, muscle strength, endurance, flexibility, and posture. Usually, a therapist develops a physical training program to help patients retain their locomotor abilities, but in many cases, the challenge is to motivate and engage participants. To assist the therapist to engage participants we introduced the anthropomorphic social robot Kiro. Aiming to support the therapist along with a predefined routine, Kiro follows the instructions of the therapist to perform several exercises moving its arms and legs while motivating patients with personalized and motivational phrases. In this work, we report a preliminary user study consisting of two sessions with seven persons with dementia in which the robot successfully engaged with the patients and kept them motivated. Finally, we discuss the intervention design, adoption, and user interaction.