An Architecture for the Integration of Robots and Sensors for the Care of the Elderly in an Ambient Assisted Living Environment

Loza-Matovelle, David; Carmen, Verdugo Cabrera Alexanra del; Zalama, Eduardo; Gómez-García-Bermejo, Jaime

doi:10.3390/robotics8030076

Cited by 16 publications

(19 citation statements)

References 16 publications

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“…Loza-Matovelle et al [44] 2019 Custom bracelet: HR, body temperature, angular acceleration, and heading…”

Section: Social Robotsmentioning

confidence: 99%

“…User studies [36], [38], [39], however, uncover the importance of including robotic agents capable of social interactions with the user to provide both psychological and physical assistance to older adults. Several studies tackle using robotic agents for the care of older adults [39]- [41], while others propose taking a step further by integrating such robots in the ambient assisted living (AAL) environments with other smart sensors [42]- [44]. Integrating various sensors, actuators, and user interfaces requires rigorous work on a scalable and personalization to different user needs.…”

Section: Introductionmentioning

confidence: 99%

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Smart Healthcare in the Age of AI: Recent Advances, Challenges, and Future Prospects

Mahmoud¹,

et al. 2021

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The significant increase in the number of individuals with chronic ailments (including the elderly and disabled) has dictated an urgent need for an innovative model for healthcare systems. The evolved model will be more personalized and less reliant on traditional brick-and-mortar healthcare institutions such as hospitals, nursing homes, and long-term healthcare centers. The smart healthcare system is a topic of recently growing interest and has become increasingly required due to major developments in modern technologies, especially in artificial intelligence (AI) and machine learning (ML). This paper is aimed to discuss the current state-of-the-art smart healthcare systems highlighting major areas like wearable and smartphone devices for health monitoring, machine learning for disease diagnosis, and the assistive frameworks, including social robots developed for the ambient assisted living environment. Additionally, the paper demonstrates software integration architectures that are very significant to create smart healthcare systems, integrating seamlessly the benefit of data analytics and other tools of AI. The explained developed systems focus on several facets: the contribution of each developed framework, the detailed working procedure, the performance as outcomes, and the comparative merits and limitations. The current research challenges with potential future directions are addressed to highlight the drawbacks of existing systems and the possible methods to introduce novel frameworks, respectively. This review aims at providing comprehensive insights into the recent developments of smart healthcare systems to equip experts to contribute to the field.

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“…Loza-Matovelle et al [44] 2019 Custom bracelet: HR, body temperature, angular acceleration, and heading…”

Section: Social Robotsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Smart Healthcare in the Age of AI: Recent Advances, Challenges, and Future Prospects

Mahmoud¹,

et al. 2021

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“…Within the field of social robots, our research group has opted for the use of autonomous unmanned aerial vehicles (UAVs) as a promising alternative for the home care of dependent people, mainly elderly people living alone. The role of UAVs in ambient assisted living for the elderly is a hot topic [2][3][4]. Such UAVs, equipped with an on-board camera, provide a novel solution for navigating around the inhabitant and monitoring them.…”

Section: Introductionmentioning

confidence: 99%

Facial Emotion Recognition from an Unmanned Flying Social Robot for Home Care of Dependent People

et al. 2021

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This work is part of an ongoing research project to develop an unmanned flying social robot to monitor dependants at home in order to detect the person’s state and bring the necessary assistance. In this sense, this paper focuses on the description of a virtual reality (VR) simulation platform for the monitoring process of an avatar in a virtual home by a rotatory-wing autonomous unmanned aerial vehicle (UAV). This platform is based on a distributed architecture composed of three modules communicated through the message queue telemetry transport (MQTT) protocol: the UAV Simulator implemented in MATLAB/Simulink, the VR Visualiser developed in Unity, and the new emotion recognition (ER) system developed in Python. Using a face detection algorithm and a convolutional neural network (CNN), the ER System is able to detect the person’s face in the image captured by the UAV’s on-board camera and classify the emotion among seven possible ones (surprise; fear; happiness; sadness; disgust; anger; or neutral expression). The experimental results demonstrate the correct integration of this new computer vision module within the VR platform, as well as the good performance of the designed CNN, with around 85% in the F1-score, a mean of the precision and recall of the model. The developed emotion detection system can be used in the future implementation of the assistance UAV that monitors dependent people in a real environment, since the methodology used is valid for images of real people.

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“…The ENRICHME project [9] uses an assistive robot to support elderly people at home. Loza-Matovelle et al [10] introduce an architecture of robots and sensors for elderly in an ambient assisted living environment. Do et al [11] combine smart home sensors with robots for activity monitoring, fall detection, and rescue by the robot.…”

Section: Introduction and Related Workmentioning

confidence: 99%

Promoting Autonomy in Care: Combining Sensor Technology and Social Robotics for Health Monitoring

Neef

Richert

2020

7th International Electronic Conference on Sensors and Applications

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As the world’s population grows significantly older, there are not enough caregivers in many countries for all the elderly people in need of care. To promote their autonomy while also supporting their caregivers, we propose a health monitoring system comprised of a social robot, and various wearable and non-wearable sensors. Through the use of patient-reported outcome measures (PROMs), captured in conversation with the social robot, the subjective health status of the user is determined. This is supplemented by objective information gathered from wearable and non-wearable sensors used to measure numerous biosignals. By combining the subjective data obtained from interaction with the user and the objective data from the sensor network, a health report for both users and caregivers is generated. The data are visualized for the user and caregiver in a customizable and easily accessible health monitoring dashboard, which also warns the user and their caregivers when the data deviate from the expected values or ranges. The goal is to use this information to improve the quality of care, as changes in the user’s health status can be determined more quickly by themselves and their caregivers. The proposed system establishes a good base for further testing and optimization together with the user, to ensure a useful and appropriate combination of sensors and technological devices that the user is comfortable with.

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An Architecture for the Integration of Robots and Sensors for the Care of the Elderly in an Ambient Assisted Living Environment

Cited by 16 publications

References 16 publications

Smart Healthcare in the Age of AI: Recent Advances, Challenges, and Future Prospects

Smart Healthcare in the Age of AI: Recent Advances, Challenges, and Future Prospects

Facial Emotion Recognition from an Unmanned Flying Social Robot for Home Care of Dependent People

Promoting Autonomy in Care: Combining Sensor Technology and Social Robotics for Health Monitoring

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