Practicality of Smartwatch Apps for Supporting Elderly People – A Comprehensive Survey

Lutze, Rainer

doi:10.1109/ice.2018.8436370

Cited by 8 publications

(2 citation statements)

References 16 publications

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“…In the last few years, most wearable devices have been miniaturized and have optimized their power consumption ( Cicirelli et al, 2021 ). Wearable devices, especially fitness trackers, wristbands and smartwatches ( Andò et al, 2016 ; Lutze, 2018 ; Xie et al, 2020 ), have various built-in/integrated sensors such as accelerometers, gyroscopes and orientation sensors. Smartphones represent an additional solution for their characteristics of cost effectiveness and high number of embedded sensors ( Ramanujam et al, 2021 ).…”

Section: Monitoring Solutionsmentioning

confidence: 99%

Ambient assisted living for frail people through human activity recognition: state-of-the-art, challenges and future directions

Guerra,

Torti,

Marenzi

et al. 2023

Front. Neurosci.

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Ambient Assisted Living is a concept that focuses on using technology to support and enhance the quality of life and well-being of frail or elderly individuals in both indoor and outdoor environments. It aims at empowering individuals to maintain their independence and autonomy while ensuring their safety and providing assistance when needed. Human Activity Recognition is widely regarded as the most popular methodology within the field of Ambient Assisted Living. Human Activity Recognition involves automatically detecting and classifying the activities performed by individuals using sensor-based systems. Researchers have employed various methodologies, utilizing wearable and/or non-wearable sensors, and employing algorithms ranging from simple threshold-based techniques to more advanced deep learning approaches. In this review, literature from the past decade is critically examined, specifically exploring the technological aspects of Human Activity Recognition in Ambient Assisted Living. An exhaustive analysis of the methodologies adopted, highlighting their strengths and weaknesses is provided. Finally, challenges encountered in the field of Human Activity Recognition for Ambient Assisted Living are thoroughly discussed. These challenges encompass issues related to data collection, model training, real-time performance, generalizability, and user acceptance. Miniaturization, unobtrusiveness, energy harvesting and communication efficiency will be the crucial factors for new wearable solutions.

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Section: Monitoring Solutionsmentioning

confidence: 99%

Ambient assisted living for frail people through human activity recognition: state-of-the-art, challenges and future directions

Guerra,

Torti,

Marenzi

et al. 2023

Front. Neurosci.

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show abstract

“…They have been extensively applied for different purposes, such as to assess the postural stability of a subject [35], to detect and classify falls [36][37][38][39][40], or to analyze the gait cycle [41]. Moreover, these sensors are embedded in mobile technologies, such as smartphones, smartwatches, and wristbands, which also support the continuous monitoring of biological, behavioral, and environmental data [42][43][44].…”

Section: Wearable Sensorsmentioning

confidence: 99%

Ambient Assisted Living: A Review of Technologies, Methodologies and Future Perspectives for Healthy Aging of Population

Cicirelli

Marani

Petitti

et al. 2021

Sensors

112

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Over the last decade, there has been considerable and increasing interest in the development of Active and Assisted Living (AAL) systems to support independent living. The demographic change towards an aging population has introduced new challenges to today’s society from both an economic and societal standpoint. AAL can provide an arrary of solutions for improving the quality of life of individuals, for allowing people to live healthier and independently for longer, for helping people with disabilities, and for supporting caregivers and medical staff. A vast amount of literature exists on this topic, so this paper aims to provide a survey of the research and skills related to AAL systems. A comprehensive analysis is presented that addresses the main trends towards the development of AAL systems both from technological and methodological points of view and highlights the main issues that are worthy of further investigation.

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Improving Dialogue Design and Control for Smartwatches by Reinforcement Learning Based Behavioral Acceptance Patterns

Lutze¹,

Waldhör

2020

Human-Computer Interaction. Human Values and Quality of Life

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Practicality of Smartwatch Apps for Supporting Elderly People – A Comprehensive Survey

Cited by 8 publications

References 16 publications

Ambient assisted living for frail people through human activity recognition: state-of-the-art, challenges and future directions

Ambient assisted living for frail people through human activity recognition: state-of-the-art, challenges and future directions

Ambient Assisted Living: A Review of Technologies, Methodologies and Future Perspectives for Healthy Aging of Population

Improving Dialogue Design and Control for Smartwatches by Reinforcement Learning Based Behavioral Acceptance Patterns

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