Mining Heterogeneous Multivariate Time-Series for Learning Meaningful Patterns: Application to Home Health Telecare

For the last years, time-series mining has become a challenging issue for researchers. An important application lies in most monitoring purposes, which require analyzing large sets of time-series for learning usual patterns. Any deviation from this learned profile is then considered as an unexpected situation. Moreover, complex applications may involve the temporal study of several heterogeneous parameters. In that paper, we propose a method for mining heterogeneous multivariate time-series for learning meaningful patterns. The proposed approach allows for mixed time-series -- containing both pattern and non-pattern data -- such as for imprecise matches, outliers, stretching and global translating of patterns instances in time. We present the early results of our approach in the context of monitoring the health status of a person at home. The purpose is to build a behavioral profile of a person by analyzing the time variations of several quantitative or qualitative parameters recorded through a provision of sensors installed in the home

Needs and preferences for technology among Chinese family caregivers of persons with dementia: a pilot study

Background: Dementia is a major public health concern associated with significant caregiver demands and there are technologies available to assist with caregiving. However, there is a paucity of information on caregiver needs and preferences for these technologies, especially among Chinese family caregivers of persons with dementia in Canada. Objective: The purpose of this study was to examine the technology needs and preferences of Chinese family care- givers of persons with dementia with a sex and gender lens in Canada. Methods: A cross-sectional survey was conducted through the Yee Hong Centre of Geriatric Care in Canada. Frequency distributions, Wilcoxon Signed Ranks Test, and multiple regression analyses were performed. Results: The majority of the 40 respondents did not demonstrate knowledge about technology to assist with caregiving. Ease of installation and reliability were identified as the most important features when installing and using technology respectively. Respondents demonstrated a positive attitude towards the use of technology during caregiving. Controlling for age, female respondents were significantly more receptive of technology. Conclusions: Our findings suggest a need to increase awareness of technology options to assist caregiving in this ethnic population and provide insight for future development and marketing of technology that better align with caregivers’ needs

A Behaviour Monitoring System (BMS) for Ambient Assisted Living

Unusual changes in the regular daily mobility routine of an elderly person at home can be an indicator or early symptom of developing health problems. Sensor technology can be utilised to complement the traditional healthcare systems to gain a more detailed view of the daily mobility of a person at home when performing everyday tasks. We hypothesise that data collected from low-cost sensors such as presence and occupancy sensors can be analysed to provide insights on the daily mobility habits of the elderly living alone at home and to detect routine changes. We validate this hypothesis by designing a system that automatically learns the daily room-to-room transitions and permanence habits in each room at each time of the day and generates alarm notifications when deviations are detected. We present an algorithm to process the sensors' data streams and compute sensor-driven features that describe the daily mobility routine of the elderly as part of the developed Behaviour Monitoring System (BMS). We are able to achieve low detection delay with confirmation time that is high enough to convey the detection of a set of common abnormal situations. We illustrate and evaluate BMS with synthetic data, generated by a developed data generator that was designed to mimic different user's mobility profiles at home, and also with a real-life dataset collected from prior research work. Results indicate BMS detects several mobility changes that can be symptoms of common health problems. The proposed system is a useful approach for learning the mobility habits at the home environment, with the potential to detect behaviour changes that occur due to health problems, and therefore, motivating progress toward behaviour monitoring and elder's care.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT—Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

Evolution after the COVID of the invisibility of precarities (ECOVIP): Overview of an action research project to decipher the urban factory of invisibility

Due to weak economies or ill-adapted public policies aggravated by the pandemic, official services dedicated to the unconditional reception and support of people in psychosocial distress in large urban areas are often put to the test. Here is the approach of the action research “Evolution after COVid-19 of the Invisibility of Precarities” (ECOVIP) dedicated to this phenomenon, as well as its first results concerning the precarity of unemployed “young” seniors (50-64 years old) in Lyon, France. This participative research is based on workshops that bring together professionals from both the front-line psychosocial field and other fields such as employment or work, and in which they are offered a free expression of their lived situations of reception of precarious people. The first results provided by the scientific and transparent analysis of these exchanges show both a fairly precise understanding of the institutional decision leading to increasing invisibility, and the emergence of innovative professional resources capable of curbing it.Due to weak economies or ill-adapted public policies aggravated by the pandemic, official services dedicated to the unconditional reception and support of people in psychosocial distress in large urban areas are often put to the test. Here is an overview of the approach of the action research “Evolution after COVid-19 of the Invisibility of Precarities” (ECOVIP) dedicated to this phenomenon, as along with its first steps showing preliminary results concerning the precarity of unemployed pre-old people in Lyon, France.This participative research is based on workshops that bring together professionals from both the front-line psychosocial field and other fields such as employment or work, and in which they are offered a free expression of their lived situations of reception of precarious people. The first results provided by the scientific and transparent analysis of these exchanges show both a fairly precise understanding of the institutional decision leading to increasing invisibility, and the emergence of innovative professional resources capable of curbing it.

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A Multiagent Approach to Personalization and Assistance to Multiple Persons in a Smart Home

http://www.aaai.org/ocs/index.php/WS/AAAIW14/paper/download/8809/8371&sa=X&scisig=AAGBfm2W2ejiuEPthMsyGE4AgBRTA_1HfAInternational audienceLocalization, personalization, activity recognition, and cognitive assistance are key issues in research on smart homes for cognitively impaired people. Most of the current solutions rely on the presence of solely one person in the residence. To actively consider the interaction of the smart home inhabitant with their caregivers, nurses, doctors and people sharing their home, this paper proposes a multi-agent approach to transparently locate, identify, and ease the collaboration between distributed personalization and assistance services. Based on Bayesian filtering localization using anonymous sensors, the multi-person localization process provides information on each occupant presence, either incoming or outgoing. This information is then used for personalization and assistance

What Do Family Caregivers of Alzheimer's Disease Patients Desire in Smart Home Technologies?

Objectives - The authors' aim was to investigate the representations, wishes, and fears of family caregivers (FCs) regarding 14 innovative technologies (IT) for care aiding and burden alleviation, given the severe physical and psychological stress induced by dementia care, and the very slow uptake of these technologies in our society. Methods - A cluster sample survey based on a self-administered questionnaire was carried out on data collected from 270 families of patients with Alzheimer's disease or related disorders, located in the greater Paris area. Multiple Correspondence Analysis was used in addition to usual statistical tests to identify homogenous FCs clusters concerning the appreciation or rejection of the considered technologies. Results - Two opposite clusters were clearly defined: FCs in favor of a substantial use of technology, and those rather or totally hostile. Furthermore the distributions of almost all the answers of appreciations were U shaped. Significant relations were demonstrated between IT appreciation and FC's family or gender statuses (e.g., female FCs appreciated more than male FCs a tracking device for quick recovering of wandering patients: p=0.0025, N=195). Conclusions - The study provides further evidence of the contrasted perception of technology in dementia care at home, and suggests the development of public debates based on rigorous assessment of practices and a strict ethical aim to protect against misuse