Dementia ambient care: a holistic approach to the management of dementia in multiple care settings

Assistive technologies that continuously monitor the person with dementia’s behavioural, cognitive, and emotional state facilitate more objective means of assessing, monitoring, and supporting the individual than that provided by traditional questionnaires. The “Dementia Ambient Care” (Dem@Care) EU-FP7-funded project investigated the use of multiple wearable (actigraphy, 2D/3D cameras, microphones) and ambient (visual and infrared cameras, sleep) sensors for the recording of daily activities, lifestyle patterns, emotions, and speech, to develop a novel approach to the holistic management of dementia, in multiple care settings. This paper presents findings from the use of Dem@Care for remote monitoring and support in the home of the person with mild dementia, and for the clinical assessment and management of Behavioural and Psychological Symptoms of Dementia (BPSD) for people in more advanced stages in a residential care setting. Four ‘home’ participant cases will be discussed; two in Greece and two in Ireland. An intervention study will also be presented comprising of residents from three specialist dementia care units in northern Sweden; two in the experimental group and one in the control group. In each setting, sensor data were analysed using state-of-the-art knowledge-driven interpretation techniques based on Semantic Web technologies. Patterns of sleep, physical activity, daily living activities, and stress/anxiety over time were identified. Through specific user interfaces, clinicians and formal caregivers were able to monitor the sensor recordings and the relevant analysis in order to propose new, or to adapt older, supports and interventions. Results indicate that such sensor-based information can have a positive impact on the assessment of BPSD in residential care settings. While at home, the person with dementia and their family caregiver could monitor summaries of their own activities, and read personalized messages, prompts and advice, thus providing timely support and enabling independent living for longer

Creating digital life stories through activity recognition with image filtering

Abstract. This paper presents two algorithms that enables the MemoryLane system to support persons with mild dementia through creation of digital life stories. The MemoryLane system consists of a Logging Kit that captures context and image data, and a Review Client that recognizes activities and enables review of the captured data. The image filtering algorithm is based on image characteristics such as brightness, blurriness and similarity, and is a central component of the Logging Kit. The activity recognition algorithm is based on the captured contextual data together with concepts of persons and places. The initial results indicate that the MemoryLane system is technically feasible and that activity-based creation of digital life stories for persons with mild dementia is possible

The Impact of Using Measurements of Electrodermal Activity in the Assessment of Problematic Behaviour in Dementia

Background: A major and complex challenge when trying to support individuals with dementia is meeting the needs of those who experience changes in behaviour and mood. Aim: To explore how a sensor measuring electrodermal activity (EDA) impacts assistant nurses’ structured assessments of problematic behaviours amongst people with dementia and their choices of care interventions. Methods: Fourteen individuals with dementia wore a sensor that measured EDA. The information from the sensor was presented to assistant nurses during structured assessments of problematic behaviours. The evaluation process included scorings with the instrument NPI-NH (Neuropsychiatric Inventory-Nursing Home version), the care interventions suggested by assistant nurses to decrease problematic behaviours, and the assistant nurses’ experiences obtained by focus group interviews. Results: The information from the sensor measuring EDA was perceived to make behavioural patterns more visual and clear, which enhanced assistant nurses’ understanding of time-related patterns of behaviours. In turn, this enhancement facilitated timely care interventions to prevent the patterns and decrease the levels of problematic behaviour. Conclusion: With the addition of information from the sensor, nursing staff could target causes and triggers in a better way, making care interventions more specific and directed towards certain times throughout the day to prevent patterns of problematic behaviours

Classifier Optimized for Resource-constrained Pervasive Systems and Energy-efficiency

Computational intelligence is often used in smart environment applications in order to determine a user’s context. Many computational intelligence algorithms are complex and resource-consuming which can be problematic for implementation devices such as FPGA:s, ASIC:s and low-level microcontrollers. These types of devices are, however, highly useful in pervasive and mobile computing due to their small size, energy-efficiency and ability to provide fast real-time responses. In this paper, we propose a classifier, CORPSE, specifically targeted for implementation in FPGA:s, ASIC:s or low-level microcontrollers. CORPSE has a small memory footprint, is computationally inexpensive, and is suitable for parallel processing. The classifier was evaluated on eight different datasets of various types. Our results show that CORPSE, despite its simplistic design, has comparable performance to some common machine learning algorithms. This makes the classifier a viable choice for use in pervasive systems that have limited resources, requires energy-efficiency, or have the need for fast real-time responses.publishedVersionnivå

Supporting lifestories through activity recognition and digital reminiscence

This licentiate thesis discusses how lifelogging technologies can be used to build digital reminiscence systems. Lifelogging is a recent pervasive computing trend where different aspects of someone’s life are captured digitally. The aim of the proposed system is to create digital lifestories that can visualize the life of a person and provide a means for retrieving life experiences. The target users are people with mild dementia who have problems in navigating their daily life and in recalling previous events. The claim is that digital lifestories can be utilized for memory and reminiscence support as well as strengthen the bond between a person with mild dementia and his family. The main focus of the research study is about designing and developing digital reminiscence systems that can be used by people with mild dementia as aiding memory tools. Creating digital lifestories requires capturing of context data, such as places and people, and content data, such as sound and images, using pervasive lifelogging tools. The passive and continues capture of data results in the occurrence of false data and noise. For that, the system should reduce the collected data to not overload the user when reviewing the lifelogs. Another problem is that the life should be segmented in the form of activities that are searchable and accessible. Thus the collected lifelog data should be aggregated and structured into semantic activities and then represented as digital lifestories where context data can be retrieved together with related content. This licentiate thesis proposes solutions for filtering collected data to reduce the user’s efforts when reminiscing. The thesis also presents a method that uses prior knowledge of context data to improve the recognition of activities when creating the digital lifestories. In addition, locations where the user spends significant time can help in determining context parameters such as activities. This licentiate thesis proposes a novel approach that collects and clusters logged locations of the user to improve the activity recognition task. The presented approach defines possible places first, and it then identifies activities based on those places. Images, as content data, are then associated with the activities based on their timeframes so the user can review and adjust the data before saving it to his lifestory. The presented digital reminiscence system was evaluated through a field-test involving 10 people with mild dementia together with their caregivers. Healthcare professionals were also involved in the design and the evaluation of the system to improve the outcome of the study. The preliminary results indicate that the system indeed improves the quality of life for people with mild dementia, as their reminiscence processes are encouraged and that the communication with their surroundings increases in both volume and quality. The thesis shows that digital reminiscence systems, which describe life through activities, can increase the perceived quality of life for people with mild dementia. It also shows that activity recognition can be improved by using prior knowledge of context data and by automatic location clustering.Godkänd; 2011; 20110205 (basel); LICENTIATSEMINARIUM Nedanstående person kommer att hålla licentiatseminarium för avläggande av teknologie licentiatexamen. Namn: Basel Kikhia Ämnesområde: Medieteknik/Media Technology Uppsats: Supporting Lifestories through Activity Recognition and Digital Reminiscence Examinator: Professor Arkady Zaslavsky, Institutionen för System- och rymdteknik, Luleå tekniska universitet Diskutant: Professor Chris Nugent, University of Ulster, Faculty of Computing and Engineering, Northern Ireland, UK Tid: Torsdag den 10 mars 2011 kl 10.00 Plats: A109, Luleå tekniska universite

Remember me! Supporting Reminiscence through Digital Capture of Lifestories and Activity Recognition

Lifelogging is the act of digitally capturing a person’s life experiences in the form of digital lifestories. A digital lifestory is a view of the person’s life based on a single activity or a set of activities, where activities are defined by content data, such as images, and context data, such as related places and persons. An example of a digital lifestory is a wedding where a set of selected images visually represents a person’s activities at the wedding. The person can use this representation as a digital means for later review and reminiscence of the captured activities in the lifestory about the wedding. This thesis discusses how new lifelogging technologies and methods for activity recognition can be used to create such digital lifestories and how these lifestories can be utilized for digital reminiscence. Digital capture of lifestories requires a lifelogging system capable of capturing daily activities. The digital representation of the person’s life should be interpreted and organized as activities that provide an insight into: What activities did the person do, When did the activities take place, Where did the activities take place, and Who was involved in the activities. Presenting the person’s life as activities provides an overview for reminiscing and helps the person selecting the significant activities to keep in digital lifestories.This thesis proposes a system that automatically filters captured lifelog data and then organizes the filtered data in the form of activities identified by time, location, movement data, and knowledge of context. The detection of significant places is implemented based on location clustering techniques that utilizes the density of the collected location data. The time periods when the user lingers at the same place of significance are then used to identify activities. The thesis shows that the required activity recognition can be improved by using knowledge of prior context and by automatic detection of significant places. The thesis also shows that everyday activities can be recognized using a single accelerometer, for which the wrist is the best placement of the accelerometer to analyze body movements and to detect daily activities.Two important aspects of lifelogging system design are to avoid encumbering or stigmatizing a person with too many devices, and to minimize required user interaction. The proposed lifelogging system is therefore highly automated, where the pervasively captured data is filtered from noisy data, segmented into representative activities, annotated with captured images, and organized as digital lifestories. A key finding is that one accelerometer plus one device for capturing location and images constitute a sufficient set of devices required to capture digital lifestories, hence supporting a person in reminiscing past activities by using the proposed system.The work has been evaluated through proof-of-concept prototype systems, which demonstrate the potential of reminiscence tools based on capture and review of digital lifestories. This work has the potential to make digital reminiscence systems more affordable, acceptable and easy to use, which also would lead to a positive impact on utilization. This can in particular be important for persons with special needs, such as persons with mild dementia, who generally cannot cope with too complex interaction. They can thus use such digital reminiscence systems for recollecting and reflecting on past life experiences.Godkänd; 2014; 20140326 (basel); Nedanstående person kommer att disputera för avläggande av teknologie doktorsexamen. Namn: Basel Kikhia Ämne: Distribuerade datorsystem/Pervasive Mobile Computing Avhandling: Remember Me! Supporting Reminiscence through Digital Capture of Lifestories and Activity Recognition Opponent: Professor Anthony Maeder, School of Computing, Engineering & Mathematics, University of Western Sydney, Campelltown, Australia, Ordförande: Professor Christer Åhlund, Avd för datavetenskap, Institutionen för system- och rymdteknik, Luleå tekniska universitet Tid: Tisdag den 27 maj 2014, kl 13.00 Plats: A109, Luleå tekniska universite

Acceptance of Ambient Intelligence (AmI) in supporting elderly people and people with dementia

Advances in communication technology have led to the growth of what is called Ambient Intelligence (AmI). AmI refers to an environment which is intelligent and has advanced computing, networking technology and specific interfaces. It is aware of the specific characteristics of human presence and personalities, takes care of what people need and is capable of responding intelligently according to different activities, and even can engage in intelligent dialogue with the user. Variability of location and system behavior is a central issue in AmI, where behavior of software has to change and re-adapt to the different location settings. AmI refers to an environment that acts on behalf of humans. It is sensitive, contextualized, responsive, interconnected, transparent, and intelligent. This environment is coupled with ubiquity of computing devices that enables it to react differently according to different actions, and even to take the initiative towards fulfilling human needs. Security, privacy, and trust challenges are amplified with AmI computing model and need to be carefully engineered. From software engineering perspective, the shift towards AmI can be seen abstractly similar to the shift from object paradigm towards agent one. Objects provide functionality to be exploited, while agents possess functionality and know how and when to use and offer it autonomously. Agent paradigm is suitable for implementing AmI considering AmI as an open complex system. Moreover, developers argue that agent paradigm is useful for engineering all aspects of such intelligent systems. These days, the large diversity of needs in a home-based patient population requires complex technology. Meeting those needs technically requires the use of a distributed approach and the combination of many hardware and software techniques. Furthermore, this service should be accepted in all scales and should be sufficient enough to meet all the requirements. In this thesis, I study the factors which can affect the acceptance of AmI especially when it is used to support elderly people and people with dementia, and I give suggestions which can improve the acceptance of this technology.Validerat; 20101217 (root

Context-aware life-logging for persons with mild dementia

The demands of introducing technology to support independent living is increasing. This is true also for persons suffering from mild dementia who may have difficulties remembering important information, such as activities, numbers, names, objects, faces, and so on. This paper presents a context-aware life-logging system, called MemoryLane, which can support independent living and improve quality of life for persons with mild dementia. The system offers both real time support as well as possibilities to rehearse and recall activities for building episodic memory. This paper also presents a mobile client to be used in MemoryLane, as well as an evaluation of the importance of different data for the purpose of memory recollection.Godkänd; 2009; 20091008 (qwazi)</p

Building digital life stories for memory support

The number of persons suffering from dementia is increasing, and there is significant human and economic value to gain by enabling them to keep living independently in their homes. The top priority unmet need is for memory support. This paper introduces context-awareness and life-logging in a system using reminiscence therapy methods, embodied as an ICT memory aid for recording past, current and future activities, which can later be recalled. The tool may help build or maintain episodic memories and self-image, although evidence in this area is lacking. It is designed to also give direct and instrumental support in other priority needs areas. A prototype design is described for a system that is by necessity extremely easy to use, with a touch screen computer in the home and mobile devices for data capture and cognitive support. The main life-log entities associated with the logged activities are places, persons, personal items, and recorded media. Privacy, trust and dignity are key ethical issues.Godkänd; 2010; 20101213 (basel)</p

Reminiscence processes using life-log entities for persons with mild dementia

In this paper we present the reminiscence process in a prototype memory support tool for persons with mild dementia. The purpose is to promote autonomy for persons with mild dementia by supporting actualization and maintenance of episodic memories, and real-time access to a context-annotated life log.  The main research challenges are defined with a user scenario, Suitable reminiscence methods and memory entitities to reperesent life logs are described, and a preliminary architecture is presented. Finally an early design of a concrete ReviewClient is shown, to solicit feedback on the reminiscence methods, entitites chosen, architecture and the usability of the proposed interface.Validerad; 2009; 20091008 (qwazi)</p