State of the art of audio- and video based solutions for AAL

Working Group 3. Audio- and Video-based AAL ApplicationsIt is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living (AAL) technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may cause to one’s activities. In addition, a single camera placed in a room can record most of the activities performed in the room, thus replacing many other non-visual sensors. Currently, video-based applications are effective in recognising and monitoring the activities, the movements, and the overall conditions of the assisted individuals as well as to assess their vital parameters (e.g., heart rate, respiratory rate). Similarly, audio sensors have the potential to become one of the most important modalities for interaction with AAL systems, as they can have a large range of sensing, do not require physical presence at a particular location and are physically intangible. Moreover, relevant information about individuals’ activities and health status can derive from processing audio signals (e.g., speech recordings). Nevertheless, as the other side of the coin, cameras and microphones are often perceived as the most intrusive technologies from the viewpoint of the privacy of the monitored individuals. This is due to the richness of the information these technologies convey and the intimate setting where they may be deployed. Solutions able to ensure privacy preservation by context and by design, as well as to ensure high legal and ethical standards are in high demand. After the review of the current state of play and the discussion in GoodBrother, we may claim that the first solutions in this direction are starting to appear in the literature. A multidisciplinary 4 debate among experts and stakeholders is paving the way towards AAL ensuring ergonomics, usability, acceptance and privacy preservation. The DIANA, PAAL, and VisuAAL projects are examples of this fresh approach. This report provides the reader with a review of the most recent advances in audio- and video-based monitoring technologies for AAL. It has been drafted as a collective effort of WG3 to supply an introduction to AAL, its evolution over time and its main functional and technological underpinnings. In this respect, the report contributes to the field with the outline of a new generation of ethical-aware AAL technologies and a proposal for a novel comprehensive taxonomy of AAL systems and applications. Moreover, the report allows non-technical readers to gather an overview of the main components of an AAL system and how these function and interact with the end-users. The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely (i) lifelogging and self-monitoring, (ii) remote monitoring of vital signs, (iii) emotional state recognition, (iv) food intake monitoring, activity and behaviour recognition, (v) activity and personal assistance, (vi) gesture recognition, (vii) fall detection and prevention, (viii) mobility assessment and frailty recognition, and (ix) cognitive and motor rehabilitation. For these application scenarios, the report illustrates the state of play in terms of scientific advances, available products and research project. The open challenges are also highlighted. The report ends with an overview of the challenges, the hindrances and the opportunities posed by the uptake in real world settings of AAL technologies. In this respect, the report illustrates the current procedural and technological approaches to cope with acceptability, usability and trust in the AAL technology, by surveying strategies and approaches to co-design, to privacy preservation in video and audio data, to transparency and explainability in data processing, and to data transmission and communication. User acceptance and ethical considerations are also debated. Finally, the potentials coming from the silver economy are overviewed.publishedVersio

User Identity Protection in Automatic Emotion Recognition through Disguised Speech

Ambient Assisted Living (AAL) technologies are being developed which could assist elderly people to live healthy and active lives. These technologies have been used to monitor people’s daily exercises, consumption of calories and sleep patterns, and to provide coaching interventions to foster positive behaviour. Speech and audio processing can be used to complement such AAL technologies to inform interventions for healthy ageing by analyzing speech data captured in the user’s home. However, collection of data in home settings presents challenges. One of the most pressing challenges concerns how to manage privacy and data protection. To address this issue, we proposed a low cost system for recording disguised speech signals which can protect user identity by using pitch shifting. The disguised speech so recorded can then be used for training machine learning models for affective behaviour monitoring. Affective behaviour could provide an indicator of the onset of mental health issues such as depression and cognitive impairment, and help develop clinical tools for automatically detecting and monitoring disease progression. In this article, acoustic features extracted from the non-disguised and disguised speech are evaluated in an affect recognition task using six different machine learning classification methods. The results of transfer learning from non-disguised to disguised speech are also demonstrated. We have identified sets of acoustic features which are not affected by the pitch shifting algorithm and also evaluated them in affect recognition. We found that, while the non-disguised speech signal gives the best Unweighted Average Recall (UAR) of 80.01%, the disguised speech signal only causes a slight degradation of performance, reaching 76.29%. The transfer learning from non-disguised to disguised speech results in a reduction of UAR (65.13%). However, feature selection improves the UAR (68.32%). This approach forms part of a large project which includes health and wellbeing monitoring and coaching

Modeling the user state for context-aware spoken interaction in ambient assisted living

Ambient Assisted Living (AAL) systems must provide adapted services easily accessible by a wide variety of users. This can only be possible if the communication between the user and the system is carried out through an interface that is simple, rapid, effective, and robust. Natural language interfaces such as dialog systems fulfill these requisites, as they are based on a spoken conversation that resembles human communication. In this paper, we enhance systems interacting in AAL domains by means of incorporating context-aware conversational agents that consider the external context of the interaction and predict the user's state. The user's state is built on the basis of their emotional state and intention, and it is recognized by means of a module conceived as an intermediate phase between natural language understanding and dialog management in the architecture of the conversational agent. This prediction, carried out for each user turn in the dialog, makes it possible to adapt the system dynamically to the user's needs. We have evaluated our proposal developing a context-aware system adapted to patients suffering from chronic pulmonary diseases, and provide a detailed discussion of the positive influence of our proposal in the success of the interaction, the information and services provided, as well as the perceived quality.This work was supported in part by Projects MINECO TEC2012-37832-C02-01, CICYT TEC2011-28626-C02- 02, CAM CONTEXTS (S2009/TIC-1485

Speech-based interaction in an AAL context

International audiencePURPOSE The number of older persons in industrialized countries is steadily increasing. Seniors living alone are more numerous, and we must find solutions that will allow them to continue to stay at home comfortably and safely. Smart housings can be one of these solutions. One of the biggest challenges in ambient assisted living (AAL) is to develop smart homes that anticipate and respond to the needs of the inhabitants. Given the diverse profiles of the older adult population, it will therefore be essential to facilitate interaction with the smart home through systems that respond naturally to voice commands rather than using tactile interfaces. METHOD The first step in our study was to evaluate how well ambient assistive speech technology is received by the target population. We report on a user evaluation assessing acceptance and fear of this new technology. The experiment aimed at testing three important aspects of speech interaction: voice command, communication with the outside world, home automation system interrupting a person's activity. Participants were 7 older persons (71-88 years old), 7 relatives and 3 professional carers; the experiments were conducted in a smart home with a voice command using a Wizard-of-Oz technique. The second step in our study was related to the adaptation of speech recognition technologies to the older adult population. Judging by the literature this has not been extensively studied. In fact, it is known that industrialized speech recognition system models are not adapted to seniors but to other categories of the population. In order to do this we recorded a specific speech corpus (voice-age) with 7 older adults (70 to 89 years old) reading sentences (a total of 4 hours of speech). A second corpus (ERES38) of free talking (18 hours of speech) was recorded by 23 speakers (68-98 years old). These corpora were analyzed in a semi-automatic manner to reveal the aged-voice characteristics. RESULTS AND DISCUSSION Regarding the technical aspect, it appears that some phonemes are more affected by age than others. Thus, a specific adaptation of the acoustic models for ASR is required. Regarding the acceptance aspect, voice interfaces appear to have a great potential to ease daily living for older adults and frail persons and would be better accepted than other, more intrusive, solutions. By considering still healthy and independent older persons in the user evaluation, one interesting finding was overall acceptance provided the system is not conducive to a lazy lifestyle by taking control of everything. This particular concern must be addressed in the development of smart homes that support daily living by stressing the ability to control the daily routine rather than altering it. This study shows the great interest of voice interfaces to develop efficient solution to enable the growing number of older persons to continue to live in their own homes as long as possible

Hardware for recognition of human activities: a review of smart home and AAL related technologies

Activity recognition (AR) from an applied perspective of ambient assisted living (AAL) and smart homes (SH) has become a subject of great interest. Promising a better quality of life, AR applied in contexts such as health, security, and energy consumption can lead to solutions capable of reaching even the people most in need. This study was strongly motivated because levels of development, deployment, and technology of AR solutions transferred to society and industry are based on software development, but also depend on the hardware devices used. The current paper identifies contributions to hardware uses for activity recognition through a scientific literature review in the Web of Science (WoS) database. This work found four dominant groups of technologies used for AR in SH and AAL—smartphones, wearables, video, and electronic components—and two emerging technologies: Wi-Fi and assistive robots. Many of these technologies overlap across many research works. Through bibliometric networks analysis, the present review identified some gaps and new potential combinations of technologies for advances in this emerging worldwide field and their uses. The review also relates the use of these six technologies in health conditions, health care, emotion recognition, occupancy, mobility, posture recognition, localization, fall detection, and generic activity recognition applications. The above can serve as a road map that allows readers to execute approachable projects and deploy applications in different socioeconomic contexts, and the possibility to establish networks with the community involved in this topic. This analysis shows that the research field in activity recognition accepts that specific goals cannot be achieved using one single hardware technology, but can be using joint solutions, this paper shows how such technology works in this regard

AI and robotics to help older adults: Revisiting projects in search of lessons learned

Abstract This article is a retrospective overview of work performed in the domain of Active Assisted Living over a span of almost 18 years. The authors have been creating and refining artificial intelligence (AI) and robotics solutions to support older adults in maintaining their independence and improving their quality of life. The goal of this article is to identify strong features and general lessons learned from those experiences and conceive guidelines and new research directions for future deployment, also relying on an analysis of similar research efforts. The work considers key points that have contributed to increase the success of the innovative solutions grounding them on known technology acceptance models. The analysis is presented with a threefold perspective: A Technological vision illustrates the characteristics of the support systems to operate in a real environment with continuity, robustness, and safety; a Socio-Health perspective highlights the role of experts in the socio-assistance domain to provide contextualized and personalized help based on actual people's needs; finally, a Human dimension takes into account the personal aspects that influence the interaction with technology in the long term experience. The article promotes the crucial role of AI and robotics in ensuring intelligent and situated assistive behaviours. Finally, considering that the produced solutions are socio-technical systems, the article suggests a transdisciplinary approach in which different relevant disciplines merge together to have a complete, coordinated, and more informed vision of the problem

Enhanced Living Environments

This open access book was prepared as a Final Publication of the COST Action IC1303 “Algorithms, Architectures and Platforms for Enhanced Living Environments (AAPELE)”. The concept of Enhanced Living Environments (ELE) refers to the area of Ambient Assisted Living (AAL) that is more related with Information and Communication Technologies (ICT). Effective ELE solutions require appropriate ICT algorithms, architectures, platforms, and systems, having in view the advance of science and technology in this area and the development of new and innovative solutions that can provide improvements in the quality of life for people in their homes and can reduce the financial burden on the budgets of the healthcare providers. The aim of this book is to become a state-of-the-art reference, discussing progress made, as well as prompting future directions on theories, practices, standards, and strategies related to the ELE area. The book contains 12 chapters and can serve as a valuable reference for undergraduate students, post-graduate students, educators, faculty members, researchers, engineers, medical doctors, healthcare organizations, insurance companies, and research strategists working in this area

Speech analysis for Ambient Assisted Living : technical and user design of a vocal order system

International audienceEvolution of ICT led to the emergence of smart home. A Smart Home consists in a home equipped with data-processing technology which anticipates the needs of its inhabitant while trying to maintain their comfort and their safety by action on the house and by implementing connections with the outside world. Therefore, smart homes equipped with ambient intelligence technology constitute a promising direction to enable the growing number of elderly to continue to live in their own homes as long as possible. However, the technological solutions requested by this part of the population have to suit their specific needs and capabilities. It is obvious that these Smart Houses tend to be equipped with devices whose interfaces are increasingly complex and become difficult to control by the user. The people the most likely to benefit from these new technologies are the people in loss of autonomy such as the disabled people or the elderly which cognitive deficiencies (Alzheimer). Moreover, these people are the less capable of using the complex interfaces due to their handicap or their lack ICT understanding. Thus, it becomes essential to facilitate the daily life and the access to the whole home automation system through the smart home. The usual tactile interfaces should be supplemented by accessible interfaces, in particular, thanks to a system reactive to the voice ; these interfaces are also useful when the person cannot move easily. Vocal orders will allow the following functionality: - To ensure an assistance by a traditional or vocal order. - To set up a indirect order regulation for a better energy management. - To reinforce the link with the relatives by the integration of interfaces dedicated and adapted to the person in loss of autonomy. - To ensure more safety by detection of distress situations and when someone is breaking in the house. This chapter will describe the different steps which are needed for the conception of an audio ambient system. The first step is related to the acceptability and the objection aspects by the end users and we will report a user evaluation assessing the acceptance and the fear of this new technology. The experience aimed at testing three important aspects of speech interaction: voice command, communication with the outside world, home automation system interrupting a person's activity. The experiment was conducted in a smart home with a voice command using a Wizard of OZ technique and gave information of great interest. The second step is related to a general presentation of the audio sensing technology for ambient assisted living. Different aspect of sound and speech processing will be developed. The applications and challenges will be presented. The third step is related to speech recognition in the home environment. Automatic Speech Recognition systems (ASR) have reached good performances with close talking microphones (e.g., head-set), but the performances decrease significantly as soon as the microphone is moved away from the mouth of the speaker (e.g., when the microphone is set in the ceiling). This deterioration is due to a broad variety of effects including reverberation and presence of undetermined background noise such as TV radio and, devices. This part will present a system of vocal order recognition in distant speech context. This system was evaluated in a dedicated flat thanks to some experiments. This chapter will then conclude with a discussion on the interest of the speech modality concerning the Ambient Assisted Living